A financial evaluation of natural gas as feedstock to the...
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Copyright UCT A financial evaluation of natural gas as feedstock to the Sasol gas-to-liquid initiative. A Research Report presented to The Graduate School of Business University of Cape Town In partial fulfilment of the requirements for the Masters of Business Administration Degree Leon Claassen November 2012
Transcript of A financial evaluation of natural gas as feedstock to the...
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A financial evaluation of natural gas as
feedstock to the Sasol gas-to-liquid initiative.
A Research Report
presented to
The Graduate School of Business
University of Cape Town
In partial fulfilment of the requirements for the
Masters of Business Administration Degree
Leon Claassen
November 2012
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Abstract.
There is a growing use of natural gas to replace other fossil fuels like oils and coal. The
methods of tapping natural gas is done by conventional methods like drilling into know gas
fields and unconventional methods like hydraulic fracking of shale.
The Gas-to-liquid (GTL) process is needed for natural gas to replace or supplement oil to
produce fuels. GTL converts the gas into liquid form which then can be refined into multiple
fuels.
This research determined when GTL plants are financial viable. The interest in this
research is due to the Sasol’s 2011 acquisition of 50% of Talisman Energy Inc. Cypress A
and Farrell Creek operations in the Montney shale basin. Thus the question arises: What will
happen if full GTL operation is launched in South Africa with the available shale gas as a
natural gas feedstock?
According to this research Gas-to-liquid plants are only financial viable when the external
economic factors are favourable. The factors that have a tremendous effect on the financial
viability of the plant are the price of the natural gas and the oil price. The economic factors
are favourable when the oil price is high and the price of the natural gas is low. The high oil
price determines the price of the final products, which in turns has a direct impact on the total
income of the plant. The lower gas price lowers the raw material cost/operational cost of the
plant which has a direct impact on the cost to operate the plant.
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TableofContents
Abstract. ................................................................................................................................. i
List of Figures. ...................................................................................................................... v
List of Tables. ...................................................................................................................... vii
List of abbreviations. ......................................................................................................... viii
1. Introduction. ................................................................................................................ 1
1.1. Research area and problem. ..................................................................................... 3
1.1.1. Research area. ................................................................................................... 3
1.1.2. Research problem. ............................................................................................ 5
1.1.3. Demand and supply of fuel in South Africa. .................................................... 6
1.2. Research questions. ................................................................................................. 7
1.3. Research scope limitations. ..................................................................................... 7
1.4. Research assumptions. ............................................................................................. 8
1.5. Research ethics. ....................................................................................................... 8
2. Literature review. ........................................................................................................ 9
2.1. Natural Gas economics and requirements. .............................................................. 9
2.1.1. Natural gas in general. ...................................................................................... 9
2.1.2. Shale gas. ........................................................................................................ 12
2.2. GTL plant analysis................................................................................................. 12
2.3. Literature review conclusion. ................................................................................ 17
3. Research methodology. ............................................................................................. 18
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3.1. Quantitative research vs. Qualitative research. ..................................................... 18
3.2. Research approach and strategy. ........................................................................... 19
3.3. Research design. .................................................................................................... 19
3.4. Practical application of the research methodology. ............................................... 20
3.5. Data collection. ...................................................................................................... 21
3.6. Data analysis. ......................................................................................................... 21
4. Macro-economic environmental factors. ................................................................... 25
4.1. Natural gas prices. ................................................................................................. 25
4.2. Oil prices................................................................................................................ 28
4.3. Gas price vs. oil price. ........................................................................................... 32
5. Fuel price and the significance there off. .................................................................. 35
5.1. How is the basic fuel price (BFP) determined? ..................................................... 37
6.1. The Financial performance of the plant. ...................................................................... 42
6.1.1. Basic inputs for the financial calculations. ........................................................ 43
6.1.1.1. Different plant sizes. ................................................................................... 43
6.1.1.2. Weighted average product price. ................................................................ 43
6.1.1.3. Natural gas to final product conversion rate. .............................................. 44
6.1.1.4. Summary of the basic inputs into the financial calculations. ..................... 45
6.1.2. Cash flow of an operational GTL plant. ............................................................ 46
6.1.2.1. Scenario of a GTL plant in operation since 2001. ...................................... 46
6.1.2.2. Scenario of a GTL plant in operation from 2012 to 2023. ......................... 47
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6.1.3. Net present values and the internal rate of return. ............................................. 49
6.2. Break even analysis of different sized GTL plants. .................................................. 53
6.2.1. Break even analysis of the 260 000 bbl/d plant. ................................................ 53
6.2.2. Break even analysis of the 40 000 bbl/d plant. .................................................. 54
6.2.3. Break even analysis of the 25 000 bbl/d plant. .................................................. 56
6.2.4. Break-even point at a specific year's economic values. ..................................... 57
6.3. Sensitivity analysis. ................................................................................................... 62
6.3.1. Sensitivity analysis at the break-even point. ...................................................... 62
6.3.2. Sensitivity analysis at 10 years operation .......................................................... 66
6.3.3. Sensitivity analysis at 20 years operation. ......................................................... 68
7. Summary and conclusion. ......................................................................................... 70
7.1. Research limitations. ............................................................................................. 70
7.2. Future research directions. ..................................................................................... 70
7.3. Conclusion. ............................................................................................................ 71
Appendix 1 – Fisher Tropsch process ................................................................................. 73
Appendix 2 – Descriptive statistics of the fuel prices and the oil price. ............................. 74
Appendix 3 - Declaration .................................................................................................... 75
Appendix 4 – Research ethics declaration. ......................................................................... 76
Bibliography ........................................................................................................................ 77
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ListofFigures.
Figure 1 - Shale gas fracking (Ryan, 2012). ......................................................................... 1
Figure 2 - GTL process (Sasol, 2011). .................................................................................. 2
Figure 3 - Sasol Milestones (Sasol B. , 2011). ...................................................................... 3
Figure 4 - Natural Gas production map (geology.com, 2012). ............................................. 4
Figure 5 - Natural gas reserves in the world (Baker & Huges, 2012). .................................. 5
Figure 6 - Financial margins of natural gas (Weijermars, et al., 2011). ............................. 10
Figure 7 - LNG transportation (Sweetcrude, 2011). ........................................................... 15
Figure 8 - Break-even point diagram for a GTL plant ( Bao, et al., 2012, p. 712). ............ 16
Figure 9 - The quantitative research process. ...................................................................... 19
Figure 10 - Average CPI index per year. ............................................................................ 25
Figure 11 - Natural gas price adapted from Wikiposit (Wikiposit, 2012) . ........................ 26
Figure 12 - Histogram of the gas price in dollars. ............................................................... 28
Figure 13 - Brent Crude oil price in dollars (Wikiposit, 2012). .......................................... 29
Figure 14 - Oil price in rand terms. ..................................................................................... 30
Figure 15 - Histogram of the real oil price in rand terms. ................................................... 32
Figure 16 - Brent crude oil and natural gas prices. ............................................................. 33
Figure 17 – Basic fuel price in c/l vs. the oil price in $/bbl. ............................................... 39
Figure 18 - Diesel price histogram. ..................................................................................... 40
Figure 19 - Petrol price histogram. ..................................................................................... 41
Figure 20 - Cumulative income if the plant had been operational from the year 2001. ..... 47
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Figure 21 –Cumulative income if the plants had been operational for the next 11 years. .. 48
Figure 22 - Sensitivity analysis summary regarding the NPV and the IIR. ........................ 52
Figure 23 - Break even analysis of the 260 000bbl/d plant. ................................................ 54
Figure 24 - Break even analysis of the 40 000bbl/d plant. .................................................. 55
Figure 25 - Break even analysis of the 25 000bbl/d plant. .................................................. 56
Figure 26 – Break-even analysis at a specific year's economic values. .............................. 58
Figure 27 – Break even analysis not converging. ............................................................... 59
Figure 28 - Histogram for the BEP on the 260 000bbl/d plant. .......................................... 60
Figure 29 - Histogram for the BEP on the 40 000bbl/d plant. ............................................ 60
Figure 30 –Oil- gas price ratio vs. BEP. ............................................................................. 61
Figure 31 - Sensitivity analysis of the BEP. ....................................................................... 64
Figure 32 - Sensitivity analysis of the BEP (May 2010 onwards). ..................................... 65
Figure 33 - Sensitivity analysis with a constant operation horizon of 10 years. ................. 66
Figure 34 – Maximum and minimum range in the sensitivity analysis. ............................. 67
Figure 35 - Sensitivity analysis for the 260 000bbl/d plant after 20 years of operation. .... 68
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ListofTables.
Table 1 - Demand/refining capacity in South Africa in 2009. (SAPIA, 2012) ..................... 7
Table 2- Descriptive statistics of the real gas price. ............................................................ 27
Table 3 - Descriptive statistics of the real oil price. ............................................................ 31
Table 4 – Correlation between the oil and gas price (2001 to 2012). ................................. 34
Table 5 – The results of a correlation analysis between the different fuel prices and the oil
price.......................................................................................................................................... 40
Table 6 - General information relating to plant sizes. (Kruger, 2012) ................................ 43
Table 7 - Product price structure derived from the BFP ..................................................... 44
Table 8 - GLT conversion rate (Chandra , 2012). ............................................................... 45
Table 9 - Sensitivity analysis on the NPV and IIR (changing income). ............................. 50
Table 10 - Sensitivity analysis on the NPV and IIR (operation horizon). .......................... 51
Table 11 – Sensitivity analysis summary. ........................................................................... 63
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Listofabbreviations.
ASU: Air separation Unit.
ATR: Auto-Thermal reformer.
B: Barrel.
Bbl/d: Barrels per day.
BEP: Break-even point.
BFP: Basic Fuel price.
BPD: Barrels per day.
Bcf/d: Billion cubic feet per day.
Bcm/a: Billion cubic meters per annum.
CAPEX: Capital expenditure.
CA: Correspondence analysis.
CPI: Consumer price index.
CTL: Coal-to-liquid.
Cf: Cubic feet.
GTL: Gas-to-liquid.
EVA: Economic-value-add.
GAAP: Generally Accepted Accounting Principles.
IRR: Internal Rate of Return.
LNG: Liquid natural Gas.
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Mcf: 1000 cubic feet.
MMcfd: Millions of cubic feet per day (gas)
MMBtu: Million British thermal units.
MSCMD: Million Standard Cubic Metres per Day.
NPV: Net present value.
OPEX: Operational expenditure.
ROE: Return on Equity.
ROI: Return on Investment.
SAPIA: South African Petroleum Industry Association.
SCF: Standard cubic feet.
Tcf: Trillion cubic feet.
th.scf: Thousand standard cubic feet.
WACC: Weighted average cost of capital.
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Chapter1–IntroductionandBackground.
1. Introduction.
GTL (gas-to-liquids) is an alternative process to the traditional oil refining processes to
produce synthetic fuels. GTL is a cleaner technology than CTL (coal-to-liquid) and both
these technologies are used by Sasol.
From engineering perspectives shale gas is extracted from shale in the crust in the earth.
This is done by means of fracking (which is currently a highly controversial subject in many
countries). The fracking process is demonstrated in Figure 1 - Shale gas fracking ; the process
shown here is horizontal drilling. A hydraulic fracture is formed – point number 1 in figure 1-
by pumping the fracturing fluid into the well bore at a rate sufficient to increase pressure in
the bore hole to exceed that of the fracture gradient of the rock. Due to the pressure the rock
cracks and the fracture fluid continue further into the rock, extending the cracks. The fluids
that is pumped into the borehole contains materials such as grains of sand, that prevent the
fractures from closing when the injection is stopped and the pressure of the fracturing
material fluid is reduced. At this stage all the free trapped gas in the rock is released through
the cracks –see point number 2 in Figure 1-, this gas is transported to the surface through the
bore well for collection.
Figure 1 - Shale gas fracking (Ryan, 2012).
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The overall GTL process is show in Figure 2 - GTL process, the process in this diagram is
over simplified. Oxygen that are produced by an air separation unit (ASU) is introduced to
the natural gas in a reactor known as a reformer (there are a couple of type if reformers and
the on in this figure is the ATR – Auto thermal reformer). The reforming process produce
synthesis gas which is transformed to oil in s Fisher-Tropsch reactor (the on in the figure 2 is
the Sasol Slurry phase Distillate Fisher- Tropsch reactor). The oil from the reactor is then
refined in a refining section of the plant were the fuels are produced. The main products of
the process are GTL diesel and GTL naphtha.
Figure 2 - GTL process (Sasol, 2011).
Sasol is an alternative fuels and chemicals company; the company is technology driven
and currently this includes the GTL process. The company started in 1950 in Sasolburg.
Currently Sasol is the leading fuel provider company in South Africa with interests in the
international energy arena. Sasol converts, coal and natural gas into fuels components and
chemicals through the propriety Fisher-Tropsch process. Sasol has manufacturing and
marketing operations in South Africa, Asia, Europe and North America. In the South African
market Sasol also refines crude oil (imported) at the Natref plant in Sasolburg, South Africa
(Sasol B. , 2011).
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Sasol also focuses on commercialising their gas-to-liquids (GTL) and the coal-to-liquids
(CTL) technology internationally. In partnership with Qatar Petroleum, Sasol started their
first GTL operation in 2007, see Figure 3.
Figure 3 - Sasol Milestones (Sasol B. , 2011).
Currently Sasol is exploring CTL plant opportunities in China and GTL plant
opportunities in Uzbekistan. Sasol is also advancing their upstream oil and gas opportunities
in all their current operations in Nigeria, Gabon, Papua New Guinea, Canada, Australia and
Mozambique. (Sasol B. , 2011).
1.1. Researchareaandproblem.
1.1.1. Researcharea.
Energy sources are the lifeblood of modern economies. Boyer et al (2011) stated in their
article that 20 years ago the demise of natural gas was predicted and that alternative sources
were and would be needed. In the Americas an aggressive plan was developed to import
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liquid natural gas (LNG) for countries with accessible supplies. Boyer et al also said in 2011
that the current situation is vastly different, in terms of the United States has an abundance
supply of natural gas and that the long-term supply is more secure that ever due to the
operators learned how to tap gas from more unconventional sources, of which one is shale
gas (Boyer, Clark, Jochen, Lewis, & Miller, 2011).
The rest of the world is catching up and they are the tapping into natural gas resources,
this includes shale gas mining that is becoming more conventional and well spread. Figure 4
(geology.com, 2012) refers to the natural gas production per country in the world. This figure
shows that most of the natural gas production is done in the northern hemisphere, with the
exception of Australia and Argentina. This correlates with Figure 5 which refers to the
natural gas reserves in the world according (Baker & Huges, 2012) where Russia, North
America, North Africa and the middle east has the biggest natural gas reserves. One of the
exceptions in this scenario is South Africa which does not have a large natural gas reserve,
but they are producing over 1 000 000 000 m3 per annum which can be used for a gas to
liquids (GTL) plant.
Figure 4 - Natural Gas production map (geology.com, 2012).
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Figure 5 - Natural gas reserves in the world (Baker & Huges, 2012).
1.1.2. Researchproblem.
This research was concerned to determine if there a financial benefit in the conversion of
natural gas into fuels for a company that uses the current GTL process at their disposal.
As mentioned above Sasol entered the natural gas business as an alternative feedstock for
oil (normal refinery) and coal (coal to liquid – CTL), as a gas to liquid (GTL) operation. As
an expansion on their current gas operations Sasol entered Canada in early 2011 with a $2
billion acquisition of 50% of Talisman Energy’s natural gas assets in Montney shale gas in
British Columbia. Currently Canada is one of the world leaders in global energy. Sasol sees
considerable growth opportunities in Canada complementing its current technology and
aspirations. The new unconventional technology for drilling and exploration set the stage for
a possible game changing energy resource in North America, and world-wide.
Sasol seems to be committed to a long future in Canada; with the shale gas investment and
the world class technology expertise. Sasol Canada sees a future for creating high value-
added opportunities in Canada (Sasol explore - Sasol Canada, 2012).
Gas-to-liquid (GTL) is an ideal monetization opportunity for all large natural gas
producers, by means of conventional or unconventional methods. A nominal 96 000 barrel
per day GTL plant would require approximately 1 billion cubic feet per day (bcf/d) of natural
gas as feedstock. By stepping on the Canadian market Sasol opened two doors; 1) producing
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natural gas by means of fracking and supplying the gas to the current local market (via the
current pipeline network) and 2) converting the natural gas into GTL naphtha (a number of
flammable liquid mixtures of hydrocarbons) and GTL diesel. As a new industry, GTL has the
potential to add significant long term value to Canada, its provinces, and local communities
(Sasol explore - Sasol Canada, 2012).
Currently it is forecasted by Henry Hub (Hub, 2012) and Alexander Green that natural gas
prices will remain consistently low in North America for the foreseeable future, given the
rapid increase in supply caused by improved shale gas production technology via current and
possibly new unconventional methods. With low feedstock prices and high end product
prices (given strong crude oil price projections, although it is currently low), there is an
attractive business opportunity for GTL in Canada.
With the current Sasol propriety technology, for which Sasol is globally recognised as a
commercial and technical pioneer, natural gas has the potential to add financial value by
transforming natural gas into a range of products, which includes transport fuels (which are
seen as cleaner burning fuels). Sasol states that “GTL offers gas owners the opportunity to
diversify gas monetisation to a degree considered impossible just a decade ago, achieving a
product value significantly above that of a feedstock for power generation” (Sasol explore -
Sasol Canada, 2012).
The main problem that this research was concerned with relates to the question if natural
gas will become available in South Africa (i.e. Karoo Shale gas), and Sasol would invest in
the natural gas fields, will this be beneficial to Sasol. As described above Sasol is and will
stay interested the natural gas environment, but will it be financial viable to convert this gas
in to liquid fuels?
1.1.3. DemandandsupplyoffuelinSouthAfrica.
The South African Petroleum Industry Association (SAPIA) indicates that in 2009 there
was an under supply of petrol and an oversupply of diesel in South Africa – see Table 1 for
the detail. However South Africa consumed approximately 11 300 million litres of petrol and
9 100 million litres of diesel during 2009, this was a 2.2% increase in petrol and a 6.6%
decrease in diesel consumption from the 2008. During 2008 there was a 4.2% decrease in
petrol consumption and a 0.1% increase in diesel consumption from 2007 (SAPIA, 2012).
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This indicates that there might be a shift in the dominant fuel that is consumed in the market
– moving from petrol to diesel, although petrol is still the preferred fuel in South Africa.
Millions of liters
Refining
capacity
Demand
actual
Surplus
(shortfall)
actual
% of the total
(demand)
Petrol 10 571 11 313 -742 48.85%
Diesel 9 205 9 116 89 39.36%
Kerosene 3 261 2 731 530 13.37%
Table 1 - Demand/refining capacity in South Africa in 2009. (SAPIA, 2012)
Table 1 indicates that the petrol (inclusive of all the grades) had 48.85% of the fuels
marker share and diesel had a 39.36% market share. Kerosene has a 13.37% of the market
share. These figures were important as an input into the calculation of the breakeven point
and the sensitivity analysis of Chapter 7 and Chapter 8.
1.2. Researchquestions.
1. Is it financially viable to convert natural gas to a liquid fuel with the current known gas-
to-liquids process in the case where there would be a gas supply in South Africa and
Sasol would decide to convert the local gas into liquid products?
2. Is there a breakeven point on a specific size of the plant?
3. What is the influence of the prices of the feedstock on the outcome of the study?
4. At what gas price will it be more financial advantageous to sell the raw gas and not the
refined gas?
1.3. Researchscopelimitations.
The scope of this research will be limited to the involvement of the Sasol in the natural gas
market and the conversion of natural gas into liquid fuels. This is not an analysis of the total
gas market although the bigger gas market will have an influence on the gas price. The
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implications of these boundaries are that this research will be limited by the approach and
scope of Sasol in terms of the cost of capital and the capital investment assumptions that
would be made.
1.4. Researchassumptions.
The following research assumptions are made:
1. Other forms of feed stocks (oil and coal) are not viable or might be on the downward side
of the depletion curve or the costs of the feedstock are becoming more expensive. The
environmental impact of the technology is not understood fully yet and the financial
“cost” might not be known and will lean towards future research.
2. Shale gas and natural gas are both the same feed stocks (no additional/different process is
required between natural gas and shale gas) except for the method that the gas is extracted
earth.
3. Assume a hurdle rate of 13 % was used in the net present values (NPV) an internal rate of
return calculations.
4. A minimum acceptable payback period of 5 years was used in the analysis.
5. All the data that are collected will be current and accurate as far as the student can
determine, if the data is not current, then the most recent accurate data will be used in the
research.
6. Net present values (NPV) an internal rate of return calculations was done over a time line
of 20 years.
7. All the products that will be produced by the GLT plant will be sold. Thus there will
always be an over demand and a under supply in the market.
1.5. Researchethics.
Ethical clearance is required by the South African government for all research directly
involving human or animal subjects conducted by faculty and students in universities. In this
case no humans or animal research will be conducted and therefore no prior ethical clearance
is needed to continue with the research.
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Chapter2‐Literaturereview.
2. Literaturereview.
The focus of the literature review is on the financial benefits of natural gas in the world
economy and the economic drivers behind the GTL process in general. This was done by
studying the financial and economic aspects of natural gas. Starting with natural gas in
general then moving to shale gas (a sub section of natural gas). This is followed by a section
on GTL plant financial analysis.
2.1. NaturalGaseconomicsandrequirements.
The following section looks at the literature about the financial and economic benefit of
natural gas in general and natural gas extracted by means of fracking.
2.1.1. Naturalgasingeneral.
Compared to the other fossil fuels, natural gas is a relative clean fossil fuel. According to
Weijermars (2011) natural gas must bridge the transition period, in other word provide a
replacement energy source, required for renewable energy technologies to mature to such an
extent that the renewable energies can economically meet energy demands. (Weijermars, et
al., 2011) Weijermars also indicated that in Europe for instance the natural gas demand in
2020 will reach 650 bcm/a (billion cubic meters per annum) and 780 bcm/a in 2030.
Although the demand in the EU will decline to 230 bcm/a in 2020 to 140 bcm/a in 2030.
According to Weijermars (Weijermars, et al., 2011) this means that the dependency on
intercontinental liquid-natural-gas (LNG) and pipeline imports will increase further and by
2030 will account for 80% of the total gas supply to EU. Consequently, the development of
European unconventional gas resources could reduce to the required gas imports and would
improve security of supply and also reduces the risk of price shocks.
Weijermars states that that North American companies that engaged in unconventional gas
projects (such as shales gas extraction with fracking) had an economic disadvantage
compared to gas production companies operating in conventional gas reservoirs (Berman,
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2009a,b; Weijermars, 2010a, 2011a). A variety of benchmarks all reveal consistently - that
the unconventional gas operators have produced (at least over the past few years) their gas at
a loss. Figure 6 shows the financial margins of companies that are in the conventional and the
unconventional natural gas business. All but one of the unconventional companies - XTO
ernergy, a subsidary of ExxonMobil - made a loss. In contrast all the companies that
Weijermars analised showed a positive margin, all between 30% and 50%.. These negative
margins are due to the prevailing depressed United States of America gas prices since 2008,
added to the poor gas price, the expected supply rate from the unconventional gas rigs, was
fastly over estimated. The incurred expenses, which must come down to improve the
profitmargins were also higher than antisipated (Weijermars, et al., 2011).
Figure 6 - Financial margins of natural gas (Weijermars, et al., 2011).
Weijermars is also of the opinion that the poor margins of unconventional gas operations
has urged many US independents to move from gas to oil drilling, under the expectation that
higher margins may be earned from oil and conventional gas operations
The major contributing factor to the financial difficulties faced by unconventional gas
operators is that they operate under high uncertainty at every stage of the upstream value
chain (this includes the pipeline production system and the customer’s demand). For
unconventional gas projects to eventually rival or outperform conventional oil and gas
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projects the technology must be of such a standard that the extraction of gas with an
unconventional method will result in flow rates that increase per well and that the cost must
come down. In addition the environmental impact must be mitigated. Considering that these
stakeholder issues (especially environmental stakeholders) must be adequately addressed
with these mitigation actions. (Weijermars, et al., 2011)
According to Weijermars there are financial challenges in the production of natural gas:
“Typical well cost for well completion is build up as follows: 20-25% drilling rig, 30-35%
frac job, 10-15% tubulars (Godec et al., 2007). Slim hole technology using 53/4 inch (or even
micro-holes diameters ranging from 1.25 to 2.38 inches, instead of 83/4 inch conventional
completion size and cheaper horizontal drilling, geo-steering and coiled tubing help bring
down well costs. Some unconventional shale plays (e.g., Marcellus shale) may even be
produced without expensive well stimulation techniques.” (Weijermars, et al., 2011, p. 410)
Kaiser states that “[f]or $6/Mcf (1000 cubic feet) gas, average producers are expected to
generate pre-tax returns between 1 and 11.5% for 1 to $0.5/Mcf operating expenses and $7.5
million capital expenditure. Wells are expected to generate a pre-tax return of 52% to 25%
for $7.5 to $10 million capital expenditures and post-tax returns of 40% to 20%. We show
that gas prices in the first year of production are an important determinant of well
profitability” (Kaiser, 2012, p. 75).
In relation to this Kaiser (2012) mentions that Haynesville shale is marginally financially
viable at prevailing gas prices and unlikely to be sustainable at current levels unless gas
prices increase in the future and/or technological advances reduce development cost (Kaiser,
2012). This reemphasizes the importance of the gas price in the financial evaluation of the
production of natural gas.
The most important factors in project evaluation are the future prices of the commodities
that will be used in the production facility. In the case of natural gas the price of natural gas
has a tremendous effect on the financial viability of a project of a production facility. Gas
prices follows the old economic relation of supply and demand which in turn is impacted by
general economic conditions, storage volumes, weather and other seasonal events, including
hurricanes and tropical storms in North America. Kaiser stated that due to the high levels of
volatility, it is common to calculate an average price and standard deviation over a specific
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time period – for instance 10 years - and adjust for inflation effects to get to the real gas
prices and the analysis on the real gas prices instead of the current gas prices (Kaiser, 2012).
Shale gas productions are exposed to the same price uncertainty impacting conventional
natural gas wells but because of high initial production rates and steep decline, exposure is
concentrated within a smaller time window. Thus the high profitability stage of the
unconventional gas fields per well are short lived. Keiser states that the shale gas prices are
assumed to be flat over the life cycle of production in the well (due to the short live span of
the specific well)) and to vary between $4/Mcf (1000 cubic feet) and $10/Mcf reflecting the
5-year historic range. Gas prices are not adjusted for inflation nor are they modelled
stochastically. Modelling gas prices stochastically will increase the uncertainty in project
returns. (Kaiser, 2012).
2.1.2. Shalegas.
The catalysis in the recent Shale gas boom is the exploration in the Barnett shale Texas, it
took 20 years of experimentation before the operations was considered to be financially
viable. Two technologies led to the success of shale gas exploration; fracture simulation and
horizontal drilling. (Boyer, Clark, Jochen, Lewis, & Miller, 2011).
Advancements in horizontal drilling and hydraulic fracturing, demonstrated successfully
in the Barnett shale and first applied in the Marcellus shale in 2004, have enabled the
recovery of financially viable levels of Marcellus shale gas. After vertical drilling reaches the
depth of the shale, the shale formation is penetrated horizontally with lateral lengths
extending hundreds of metres to ensure maximum contact with the gas-bearing seam.
Hydraulic fracturing is then used to increase permeability that in turn increases the gas flow.
(Jinang, et al., 2011)
2.2. GTLplantanalysis.
Natural gas is a clean-burning and abundant energy resource. Much of the current gas
reserves are in remote locations and most of the time there is no economic/financial means of
transporting the gas to a market. A logical solution for the problem would be to liquefy the
natural gas, although this option requires very low temperatures (cryogenic temperatures: -
161.5°C) and involves considerable costs. Another solution is to convert the natural gas into
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hydrocarbon liquids using chemical processing. Fischer-Tropsch technology converts the
natural gas into ‘‘syngas’’ (a mixture of carbon monoxide and hydrogen) followed by
reaction to liquid fuels. Unfortunately, Fischer-Tropsch technology is expensive. (Hall,
2005).
Hall indicates that Fisher-Tropsch plant economics dictates that FT plants must be large
with capacities greater than 3 Million Standard Cubic Metres per Day (MSCMD) (Hall,
2005).
Hall arrived at a cost per barrel by assuming:
remote gas at $0.018/m3 (in terms of Kaiser’s $6/Mcf = $0.212/m3),
a 10-year straight-line amortization,
25%fixed costs,
US$ 1–3 per barrel operating costs.
For a 1.4 MSCMD size plant, this result is US$ 25 per barrel of liquid product. (Hall,
2005)
According to Morita liquid fuels such as those produced by a Fischer-Tropsch synthetic
fuel processes, are collectively called GTL (Gas to Liquid). These fuels are an
environmentally clean fuel, free of sulphur and aromatics. Morita states that a GTL project
based on a relatively small-sized gas field producing 1-3 Tcf (1 Tcf = 28.32 billion m3) of
natural gas is economically justifiable, Morita also believes this to be one of the best
measures of promoting a move to obtain alternative liquid fuel by making use of the most of
an untapped natural gas resources (ever more so with the advantage of the addition of
unconventional natural gas resources). Due to this supposed financial benefit of the GTL
process, a number of GTL projects have been either placed on-stream or announced one after
another at many locations over the world since the latter half of the 1990’s (Morita, 2001).
According to Chedid et al, the United states Department of Energy (DOE) suggests that
GTL can only be financially viable if oil prices constantly stays above $20/barrel and gas is
available at prices of the order of $0.50/MMBtu (in terms of the above mentioned costs in
recent paragraphs this relates to $0.17/m3). According to Chedid, Kobrosly and Ghajar
forecasts suggested in 2007 that oil prices may remain at US$40/B or higher (which is
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currently the case), but the availability of gas feedstock at very low price is not
straightforward. Chedid et al also states that the important gas sources for GTL industries are
likely to be those that are remote or stranded. (Chedid, Kobrosly, & Ghajar, 2007).
For the financial consideration of natural gas Chedid el al said that one can sell the natural
gas in its natural form, sell the gas in a liquid form or convert the natural gas to refined liquid
products via a GTL process.
According the Chedid et al to decide on a GTL investment, it is important to determine its
internal rate of return (IRR) or a different hurdle rate must be applied if IRR is not applicable.
Chedid et al (2007) identified a set of parameters and assumptions to enable them to
financially evaluate a GTL project. They considered the following assumptions (Chedid,
Kobrosly, & Ghajar, 2007, p. 4806):
Stranded NG (feedstock) price: 0.75US$/th.scf.
CO price: 21.9US$/B
Capital cost: US$28,000 for each B/d capacity.
Operation and maintenance (O&M): 4US$/B.
Diesel incremental cost over CO: 8US$/B
Days of operations per year: 340.
The availability of production units: 90%.
Life time of GTL plants is 15 years starting 2006
Operation and maintenance cost.
GTL plant capital cost.
The analysis done by Chedid et al is based on the consideration that 10,000 cf (cubic feet)
of natural gas is required to produce one barrel of GTL products (Chedid, Kobrosly, &
Ghajar, 2007). In conclusion Chedid refers to the IRR of between 16.4% and 18% for the
case in Qatar. In their final conclusion Chedid et al states the following: “Finally, it can be
said that the success of Qatar’s GTL industry will open up a global market for both Qatar and
other gas rich countries, and since the middle distillate market at present is around 20 times
the size of the current LNG market, the potential market for GTL is almost unlimited”
(Chedid, Kobrosly, & Ghajar, 2007, p. 4811).
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Reddy et al looked at the GTL technologies in India and found natural gas deposits
(containing 65–95% methane) located in the remote areas of India can be converted to liquid
products on site using direct route and that would make transportation of these natural gas
deposits much more economical and practical. The reviews on recent developments in syngas
technologies through direct routes of methane conversion and status of both existing and
future developments of GTL industry are presented below. (Reddy Keshav & Basu, 2007).
Reddy analysed the different technologies relevant to GTL and concluded that the most
attractive technology would be oxygen blown auto-thermal reforming (ATR) process. Thus
Reddy showed that the technology type in the GTL process also makes a difference in the
financial viability of the GTL plant which is fed by natural gas.
This is underlined by Bao et al when they state that in many cases, there is a financial
incentive to ship the gas in liquid form which occupies less volume than the gaseous form
and the transportation method is much easier, with less risk. In this regard two main
approaches have been adopted: liquefaction leading to liquefied natural gas (LNG) and
chemical conversion to convert natural gas to liquid (GTL). ( Bao, El-Halwagi, & Elbashir,
2012). The LNG is transported via a ship which is shown in Figure 7. Liquid fuels are
transported in normal road and ship tankers.
Figure 7 - LNG transportation (Sweetcrude, 2011).
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Bao et al developed a case study to assess a GTL plant using 900 000kg/h of natural gas to
produce 118,000 bbl/d of products. Depending on the price of natural gas, the return on
investment ranges from 7.4% to 19.4% for the cost of natural gas being $8/1000 SCF
(standard cubic feet) and $5/1000 SCF of natural gas, respectively. With a reduction in the
cost of natural gas (because of market conditions, production conditions, or special
contractual terms) or the increase in the selling prices of the liquid fuels, the process can
make higher profit. A break-even point analysis indicates that under current market
conditions, the production capacity should be at least 57,000 BPD (barrels per day) to make
profit. ( Bao, El-Halwagi, & Elbashir, 2012).
Bao et al did a detailed techno-economic evaluation/simulation of GTL plant. They looked
at the capital investment, ROI, fixed cost and variable cost, all in relation the size of the plant
-to determine the break-even point. Thus the conclusion that can be drawn from Bao et al is
that the larger the plant the more profit the plant will make and the more economic/financial
value adding the operations will be. The break-even analysis result is shown in Figure 8. This
figure shows that there is a significant impact of the size of the plant that processes the gas on
the financial benefit. This is mainly due the divergence of the total income and the variable
cost lines in the diagram.
Figure 8 - Break-even point diagram for a GTL plant ( Bao, et al., 2012, p. 712).
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2.3. Literaturereviewconclusion.
Weijermars states financial recovery of gas fields becomes realistically possible when oil-
linked gas prices continue to rise and when cost of technology comes down, aided by
improved field development strategy and workflow (Weijermars, et al., 2011).
It is evident that the size of the operations and the macroeconomics has an enormous effect
on the financial viability on of GLT plant.
Due to a low gas price since 2008, there is tremendous pressure on the production
fraternity to produce natural gas form a low cost base. The question that still remains is: what
is the impact on the production of liquids in a GTL plant. It is evident that the selling of
natural gas in it unrefined form is marginally economic, but there might be a case for the
refined gas.
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Chapter3–Researchmethodologyanddesign
3. Researchmethodology.
The chosen research methodology for this research is a quantitative research. The
following sections relates to the description of the major areas of the research methodology
that were used in the research. The following sections describe the information in more detail.
3.1. Quantitativeresearchvs.Qualitativeresearch.
The main difference between quantitative research and qualitative research is explained in
the following paragraphs (Bryman & Bell, 2007);
Quantitative research can be construed as a research strategy that accentuates the
quantification and the collection of data, analysis thereof and that (Bryman & Bell, 2007):
Follows a deductive approach to the relationship between theory and research, where
the emphasis is place on the testing of theories and not the development of theories.
“[H]as incorporated the practices and norms of the neutral scientific model and the
positivism in the particular” (Bryman & Bell, 2007, p. 28)
Embodies a view of social reality as an external, neutral reality.
In contrast to the quantitative research lies the qualitative research that constitutes the
approach of accentuating words rather than the quantification in the collection of the data and
the analysis thereof and that (Bryman & Bell, 2007):
Follows an inductive approach to determine the relationship between theory and the
research, where the possible emphasis is place on the generation of new theories.
“[H]as rejected the practices and norms of the neutral scientific model and of
positivism in particular in the preference for an emphasis on the ways in which
individuals interpret their social world” (Bryman & Bell, 2007, p. 28).
Embodies a view of social reality as a changing emergent property of the individual’s
creation.
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3.2. Researchapproachandstrategy.
The research approach and strategy was dictated by Figure 9. The research was based on
the data collected from one company; Sasol and the relating economic environment. This
analysis was subjected to sensitivity analysis and the hypothesis was related to the operations
of the GTL process in Sasol (fed by either Shale gas or natural gas), which lets the research
leans to the side of a case study.
Figure 9 - The quantitative research process.
3.3. Researchdesign.
The research design followed the path of a qualitative research approach based on a case
study. There were different types of case studies that could have been followed and they are
listed as follow (Bryman & Bell, 2007):
• Theory
• Hypothesis
• Research design
• Device measures and concepts
• Select research sites
• Select research subjects/respondents
• Collect data
• Process data
• Analyse data
• Findings/conclusions
•Write up findings/conclusions
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The critical case; There is a clear hypothesis and the case is chosen to allow a better
understanding of the circumstances in which the hypothesis will or will not be true
The unique case; this is an unique or extreme case (one of a kind)
The revolutionary case; “when an investigator has an opportunity to observe and
analyse a phenomenon previously inaccessible to scientific investigation” (Bryman &
Bell, 2007, p. 64)
The representative or typical case; this case attempts to typify the everyday situation
or form of organization.
The longitudinal case; this case are concerned with the change over time in a specific
case.
Analysing the types of cases above it is clear that this research followed combination
of a critical case and a unique case (due to the unique impact of the feedstock price on the
unique process of Sasol).
3.4. Practicalapplicationoftheresearchmethodology.
This section will address the practical application of the research methodology
represented in the rest of this section.
Capital expenditure of a new plant was determined for all the different sizes of plants.
Taking the different sizes of the plant into consideration is very important as indicated
in the literature review section.
Obtain the variable cost for operation of the different size plants from Sasol. This will
be a prediction of the variable cost to operate the GTL plant.
Calculate the breakeven point of the different sizes plant taking into account the
variable and fixed cost of the plants.
Calculate the payback period of the different sized new GLT plants. This information
will be depicted with descriptive statistical methods like histograms, means, medians
and standard deviations.
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Natural gas cost will be part of the variable cost of the plant, but the projected price of
the natural gas will have an influence on the financial viability of the GTL plant. To
determine if the new plants (all the different sizes) are a better investment than selling
the raw natural gas by means if the internal rate of return (IRR) and net present value
(NPV) comparisons. The return on investment (ROI) will also be calculated for the
different sized plants. This information will also be summarised and described with
descriptive statistical methods.
All of the above results will undergo a sensitivity analysis regarding the relation of the
variability of the variables.
The different methods mentioned in section 3.6 will be used to analyse the data, the
methods that will be used is dependent on the type of data that will be gathered in the
data collection part of the research.
3.5. Datacollection.
Secondary data instead of primary data was collected for this research. Secondary data is
data that are collected by someone else and not by the researcher. The data that was used in
this research came from the case or from economic sources i.e. the price of natural gas (the
researcher did not collect the data first hand, but used sources of data). The secondary data
was used to do appropriate analysis and deductions.
The internet and economic web pages were mostly used for the collection of the data;
these data was substantiated by the internal data received from Sasol.
3.6. Dataanalysis.
The data was analysed by statistical (where needed), and financial processes namely:
Descriptive statistics. Descriptive statistics describe data that have been collected.
Commonly used descriptive statistics include frequency counts, ranges, means,
modes, median scores, and standard deviations (Tredoux & Durrheim, 2009).
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Inferential statistics. Inferential statistics are used to draw conclusions and make
predictions based on the descriptions of data. With inferential statistics you are trying
to reach conclusions that extend beyond the immediate data alone (Tredoux &
Durrheim, 2009).
Correspondence analysis (CA). Correspondence analysis is an exploratory data
analytic technique designed to analyze simple two-way and multi-way tables
containing some measure of correspondence between the rows and columns. As
opposed to traditional hypothesis testing designed to verify hypotheses about relations
between variables, exploratory data analysis is used to identify systematic relations
between variables when there are no expectations as to the nature of the relations.
Correspondence analysis (CA) is a method of data visualization that is applicable to
cross-tabular data such as counts, compositions, or any ratio-scale data where relative
values are of interest. All the data should be on the same scale and the row and
column margins of the table must make sense as weighting factors because the
analysis gives varying importance to the respective rows and columns according to
these margins. (Greenacre, 2010).
Cluster analysis. Cluster analysis is a collection of statistical methods, which
identifies groups of samples that behave similarly or show similar characteristics. In
common phrasing it is also called look-a-like groups. The simplest mechanism is to
partition the samples using measurements that capture similarity or distance between
samples.
IRR (internal rate of return). The internal rate of return is a rate of return used in
capital budgeting to measure and compare the profitability and viability of
investments. In general investments are accepted if they can outperform the hurdle
rate of the company which in turn is calculated from the weighted average cost of
capital (WACC). The internal rate of return does not consider the time value of
money and also does not take into account the risks of the future cash flows.
(Gallagher , 2009)
NPV (Net present value). The net present value of a project is the sum of discounted
future cash flows brought down to reflect their worth as of present day The future
cash flows is discounted at the WACC of the company or the hurdle rate of the
company if it is not the same. In general a positive NPV shows that the total cash
flows in the future will add value to the company. A net present value analysis is
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sensitive to the reliability of future cash inflows that an investment or project will
yield. To take into account this possible drawback a sensitivity analysis must be
performed to determine the possible variability of the future cash flows and the hurdle
rate (Gallagher , 2009).
Break-even analysis. Break-even analysis is a technique used by production
management and management accountants. Break-even analysis is based on
categorising production costs between variable cost (costs that change when the
production output changes) and fixed cost (costs not directly related to the volume of
production). To calculate the break-even point the total variable and fixed costs are
compared with sales revenue in order to determine the level of sales volume, sales
value or production at which the business makes neither a profit nor a loss. If a
facility/project can operate above the break-even point the facility/project will be
favourable at that production point and beyond (Cafferky & Wentworth, 2010).
Payback time. Payback time is the time it takes to pay off the in initial capital (or
depth) investment with a favourable production volume. In other words how long
does it take (in any unit of time) to reach the breakeven point in the production facility
(Cafferky & Wentworth, 2010).
Return on investment ROI. Return on investment relates price not only to the
operating expenses of product development and development but also to the capital
investment required for the production and distribution of the product. The extension
of ROI is economic value add (EVA) that make corrections to the accounting figure to
make the adjustments introduced by the generally accepted accounting principles
(GAAP). The return on investment should be looked ad from a couple of directions
which includes the return on assets (ROA) and the return on equity (ROE), where
possible (Kaplan & Atkinson, 1998).
Sensitivity analysis (for the different variables). Sensitivity analysis is a technique
used to determine how different values/outcomes of an independent variable will
impact a particular dependent variable under a given set of assumptions. Sensitivity
analysis is used within specific boundaries that will depend on one or more input
variables, such as the effect that changes in interest rates will have on a bond's price.
(Levine & Renelt, 1992)
Regression analysis. Regression analysis includes techniques for modelling and
analysing several different variables, the focus should be on the relationship between
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a dependent variable and one or more independent variables (multiple or singular
regressions). Regression analysis helps one to understand how the typical value of the
dependent variable changes when any one of the independent variables is varied or
changed, while the other independent variables are fixed. The end result of a
regression is a single equation that describes the relationship between the variables.
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Chapter4–Economicenvironment.
4. Macro‐economicenvironmentalfactors.
This chapter looks at the major macro-economic environment factors that played a major
role in the outcome of the research. The focus was on the commodities that played a
significant role in the results of the research. The main role players were:
1) The gas price, which determines the input cost of the GTL plant.
2) The oil price which has a major influence on the fuels price, which in term determine
the income of the GTL plant. The relationship between the fuel price and the oil price
as well as how the fuel price is determined in South Africa is discussed in Chapter 5.
4.1. Naturalgasprices.
The gas price that was used in the data analysis was the regulated United States industrial
gas price. Figure 11 depicts the natural gas price in real and normal terms. The real gas price
was adapted with the average CPI (consumer price index) index of the specific year and
converted to rands from dollars with the current rand/dollar exchange rate. The average CPI
that was calculated for this research is shown in Figure 10. The CPI was the highest in 2008
and the lowest in 2004.
Figure 10 - Average CPI index per year.
0%2%4%6%8%10%12%14%
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The last eleven year’s gas prices were taken into account to show the trend of the gas price
over time. Figure 11 clearly shows that the gas price steadily increased up to July 2008 and
then dropped drastically until July 2009. There were some price spikes in March 2003,
October 2005 and July 2008. From July 2008 the gas price declined steadily up to the current
price in 2012 (Wikiposit, 2012). Thus it is clear that for the past 3 years the gas became
cheaper in real and nominal terms. Figure 11 depicts the nominal and the real gas price, the
price was adjusted with the average CPI (calculated as depicted in Figure 10) for each year.
Figure 11 - Natural gas price adapted from Wikiposit (Wikiposit, 2012) .
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United States Natural Gas Industrial Price (Rands per Thousand Cubic Feet)
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Table 2 shows the descriptive statistics of the real gas price, this shows a rather large
standard deviation of R27 on a median of R77. The gas price also had a massive range of
R129 per thousand cubic feet of natural gas with a minimum price of R25/1000cf and a
maximum price of R154/1000cf in real terms.
Descriptive statistics of the real gas
price
Mean 75.65
Standard Error 2.35
Median 77.19
Standard Deviation 27.59
Sample Variance 761.03
Kurtosis 0.08
Skewness 0.54
Range 129.08
Minimum 25.12
Maximum 154.20
Sum 10 439.91
Count 138
Table 2- Descriptive statistics of the real gas price.
Histograms show the frequency of a certain range of data in a data set, in this case a
histogram was used to show the frequency of the gas price between $1-$2, $2-$3 etc. The
histogram in Figure 12 shows a normal distribution curve with a tail to the right hand side.
The line in the curve shows that 50% of the time the price was above $6 (approximately R50)
per thousand cubic feet of natural gas. This data analysis was used to determine the different
realistic scenarios; this will be elaborated on in Chapter 8 where the sensitivity analysis is
discussed.
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Figure 12 - Histogram of the gas price in dollars.
4.2. Oilprices.
The price of crude oil is mostly “regulated by the OPEC via their quota systems that they
implemented to regulate the supply of oil to the world. Currently the United States is the
world’s biggest consumer of oil but China’s and India’s demand for oil are growing rapidly.
Over the past few year the oil price has seen a tremendous range in pricing, a high price of
over $140 and a low piece in the range of $25, a mere 17% of the highest price.
Figure 13 shows the trend of the oil price since 2000. Over the past 12 year the oil price
has steadily increase to the current price of $110 (if the massive spike and drop in 2008 is
ignored).
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Histogram ‐ gas price
Frequency Cumulative %
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Figure 13 - Brent Crude oil price in dollars (Wikiposit, 2012).
The massive drop in the oil price in 2008 was due to the economic crisis in 2008. From
January 2009 there was a steady increase in the oil price.
Figure 14 shows the real and nominal rand oil price, in this case the average exchange rate
of the specific year was used to cover the dollar price to the rand price. The same CPI index
shown in Figure 10 was used to express the prices in real terms. It is clear that oil became
remarkably more expensive over time (CPI and exchange rate changes). The exchange rate
also had an effect on the oil price in rand terms. The exchange rate was at its worst in January
2002 when the exchange rate was over R11.63 to the dollar. The lowest exchange rate of
R5.75 to the dollar was in December 2004.
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Real and Nominal oil price in $ terms
Average Dated Brent Crude real price of oil in $
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Figure 14 - Oil price in rand terms.
The average oil price during this time was R592. The summary of the descriptive statistics
are shown in Table 3, the volatility of the oil prices is also shown with a standard deviation of
R223 on a median price of R559 per barrel. The range of the oil price was also remarkable
with a range of R1059 per barrel in real terms.
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Real and Nominal oil price in rand terms
Brent crude in rands
real price in rands with South African inflation
Exchange Rate Rands/US$
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Descriptive statistics of the real oil
price
Mean 592.53
Standard Error 18.08
Median 559.97
Standard Deviation 223.64
Sample Variance 50 014.28
Kurtosis 0.85
Skewness 1.01
Range 1 059.87
Minimum 305.70
Maximum 1 365.58
Sum 90 657.33
Count 153
Table 3 - Descriptive statistics of the real oil price.
The histogram in Figure 15 shows the volatility of the oil price over the past 12 years.
Shown in the graph in red line is the upper 50% of the price, thus 50% of the time the price
was above $400 with a maximum price of more than R1350 and the lowest price of R305 (in
real terms and R154 in nominal terms – this was in January 2000). The effect of this on the
financial viability of the GTL plant will be discussed and elaborated on in Chapter 8 where
the sensitivity analysis is discussed.
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Figure 15 - Histogram of the real oil price in rand terms.
4.3. Gaspricevs.oilprice.
Combining the oil and the gas price into on graph shows that there are remarkable
differences in the trends of these prices (in dollar terms) over time. Table 4 shows the
correlation between the oil price and the gas price, a correlation of 0.193 is very low and
shows there are no correlation between the prices. Up to mid-2008 both the oil and the gas
price increased over time. From mid-2008 up to mid-2009 both dropped drastically and only
the oil price recovered to $110, the gas price had a short recovery and then dropped further to
current $3 per 1000 cf. The effect of these prices will be illustrated in later sections where the
gas price is used to determine the operation cost of the GTL plant and the oil price has an
influence on the price of the final product (see Chapter 5) of the GTL plant.
0%10%20%30%40%50%60%70%80%90%100%110%
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Histogram ‐ oil price
Frequency Cumulative %
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Figure 16 - Brent crude oil and natural gas prices.
A correlation analysis is done to determine the similarity in two or more data sets. Table 4
shows the correlation between the gas price in $ per 100cf and the oil price in $ per barrel.
The closer the correlation is to 1 the close the two date set follows one another. The two data
sets do not need to have the same magnitude; the correlation indicates if the ones set of data
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Average Dated Brent Crude price
United States Natural Gas Industrial Price (Dollars per Thousand Cubic Feet)
10 per. Mov. Avg. (Average Dated Brent Crude price)
10 per. Mov. Avg. (United States Natural Gas Industrial Price (Dollars per Thousand Cubic Feet))
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is increasing do the second data set also increases. Referring to the table, the correlation
between the gas price and the gas price is naturally 1, and the same for the oil price. But the
correlation between the gas price and the oil price is very low, indicating that these prices do
not follow each other.
Natural gas
price [$]
Brent crude oil
price [$]
Natural gas price [$] 1
Brent crude oil price [$] 0.193 1
Table 4 – Correlation between the oil and gas price (2001 to 2012).
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Chapter5–Fuelprice.
5. Fuelpriceandthesignificancethereoff.
In a GTL plant environment the majority of the products that will be sold will be liquid
fuels. This section of the report looks how the fuel price is determined in South Africa and
looked at the correlation of the oil price to the fuels price. This analysis was done to
determine the selling price of the GTL products, which will lead to the total income of the
plant; where total income is the volume of products sold times the price of the product.
According to the department of energy (Department of Energy, 2012) the fuel price
determines the total income of a liquid fuels business. This chapter looked at the fuel price
and the significance of the fuel price on the research outcome.
In South Africa the Department of Energy's Hydrocarbons and Energy Planning Branch is
responsible for coal, gas, liquid fuels, energy efficiency, renewable energy and energy
planning in general, including the energy database in South Africa.
The liquid fuels industry was licensed in 2005 for the first time in South Africa. According
to the Department of Energy’s web site, the objectives of the licensing framework as detailed
in the Petroleum Products Amendment Act 2003, Act 58 of 2003, include the following:
“Promoting an efficient manufacturing, wholesaling and retailing petroleum industry”
“Facilitating an environment conducive to efficient and commercially justifiable
investment”
“Promoting the advancement of historically disadvantaged individuals”
“Creating employment opportunities and small businesses in the petroleum sector.”
(Department of Energy, 2012)
In 2005 South Africa produced 23 571 million litres of liquid fuel products, according to
SAPIA (SAPIA, 2012) – there are no more recent figure available for 2012. In South Africa
approximately 36% of the liquid fuel demand is met by synthetic fuels which are produced
locally, largely by Sasol and Mosgas. These synthetic fuels are mainly produced from coal
and from natural gas. The remainder of the fuel demand is produce locally from imported oil
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The Department of energy states that the fuel price – which includes the petrol, diesel and
paraffin price - in South Africa is linked to the price of crude oil in international markets. The
international oil price is quoted in US dollars (US$) per barrel. International fuel prices are
essentially driven by supply and demand for product in a particular market. (Department of
Energy, 2012)
The crude oil prices combined with the Rand/Dollar exchange rate therefore have a major
impact on fuel prices in South Africa. In order for a refinery to make a profit, the price for the
product manufactured from crude oil has to be higher than that of the crude oil price. When
crude oil prices increase - as they have over the past months - the fuel price has to increase so
that crude oil refineries are able to cover their own costs. (Department of Energy, 2012). The
fuel price in South Africa is regulated by the government and the prices are not determined
by the retailers (SAPIA, 2012). The fuel price consists of (SAPIA, 2012):
Basic fuel price.
Transport costs.
Delivery costs.
Petroleum pipelines levy.
Equalisation fund levy.
Customs and excise levy.
Wholesale margin.
Retail margin.
Fuel tax.
Road accident fund.
The basic fuel price is discussed in the following section.
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5.1. Howisthebasicfuelprice(BFP)determined?
South African Petroleum Industry Association (SAPIA) states that the In Bond Landed
Cost (IBLC) was first introduced in the 1950s with the establishment of the first refinery in
South Africa, and was subsequently revised in 1995, when a market spot price component
was introduced. IBLC lost credibility in the market as a reasonable substitution for
international fuel prices. This was due to the use of refinery gate prices posted by
international refiners (known as postings) has become somewhat outdated in world trade as
these no longer tracked international market prices consistently. Thus the gate prices of the
refineries did not give a true reflection of the international fuel prices. The solution to the
problem was the introduction of the basic fuel price (BFP) formula on 2 April 2003.
SAPIA further states that his formula was negotiated in a positive spirit, with government
and industry– African Minerals and Energy Forum (AMEF) and the South African Petroleum
Industry Association (SAPIA) – agreeing on the new pricing formula. One of the main drives
was to maintain an import parity price structure with the international market. The BFP
formula reflects the realistic cost of importing a litre of product from international refineries
worldwide with products of a similar quality compared to local South African government
specifications on a sustainable basis (SAPIA, 2012).
The fuel price changes on the first Wednesday of every month based on the BFP formula.
The formula incorporates the average daily international price movements and exchange rates
(rand to US dollars) fluctuations based on the ‘3-working day optimization’ mechanism. This
means that the number of days between the first Wednesday of each month when fuel prices
are adjusted and the last working day in which fuel price data is collected to determine price
changes, will be restricted to 3 working days prior to the price change.
According the SAPIA the components of the BFP includes the following (SAPIA, 2012):
International petroleum market spot prices.
Freight cost to bring product to South African ports.
Insurance costs.
Ocean loss allowance.
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Cargo Dues.
Coastal Storage.
Stock Financing Cost.
Thus the BFP is the price that the local fuel manufacturer must compete against. The
added on cost discussed in the previous chapter will be the same for all the parties involved -
local, international and the BFP is independent of the feedstock type but are dependent on the
oil price.
The BFP is dependent on the international price of fuel (if South Africa would import
fuel). The main driver of fuel price abroad is the oil price, where oil is the main feedstock for
fuel refineries worldwide. Figure 17 shows the relationship between the international oil price
and the local price of the different grades of fuel. Although there is a remarkable difference in
the scales the “following” of the fuel price after the oil price is obvious. In Figure 17 the fuel
price is the BFP over the past 12 years (per month). The measurement of the fuel price in this
graph is cents per litre and the measurement for the oil price is dollars per barrel (Brent
crude). It is clear that there is a strong relationship between the fuel price and the oil price.
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Figure 17 – Basic fuel price in c/l vs. the oil price in $/bbl.
Table 5 shows the correlation analysis results between the different grades of the fuel
prices and the oil price, the petrol price used in this correlation analysis was the average price
of the different grades of the petrol (i.e. 93 unleaded, 95 unleaded etc.). This correlation was
done over the same time span as depicted in Figure 17, which relates to 153 data points per
commodity. The average oil price for the specific month was used in Figure 17 and in Table
3. See Appendix 3 for the full descriptive statistical results of the fuel prices and the oil price.
0
20
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100
120
140
160
0
100
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300
400
500
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1000
Jan‐2000
Aug‐2000
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Jul‐2003
Feb‐2004
Sep‐2004
Apr‐2005
Nov‐2005
Jun‐2006
Jan‐2007
Aug‐2007
Mar‐2008
Oct‐2008
May‐2009
Dec‐2009
Jul‐2010
Feb‐2011
Sep‐2011
Apr‐2012
Nov‐2012
Brent crude oil price in
$
Fuel price in
cents per litre
Basic Fuel Prices (BFP) vs oil price
Petrol 97 Petrol 93
Petrol 93 Unleaded Petrol 95 Unleaded
91 Unleaded Diesel
Illum Paraffin Average Dated Brent Crude
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Average
petrol
price
Diesel
price
Paraffin
price
Average
Brent
Crude
price
Average petrol price 1
Diesel price 0.999 1
Paraffin price 0.998 0.999 1
Average Brent Crude
price
0.956 0.958 0.959 1
Table 5 – The results of a correlation analysis between the different fuel prices and the oil price.
Figure 18 and Figure 19 shows the histogram of the basic diesel price and the average
basic petrol price (average between the different grades of petrol). The histogram of the
diesel price shows that there is no real normal distribution if at all the distribution is to the
left. Figure 18 also shows that 50% of the time the basic diesel price was less than 360c/l.
The histogram also shows the volatility of the diesel price, which is related to the volatility of
the oil price.
Figure 18 - Diesel price histogram.
0%10%20%30%40%50%60%70%80%90%100%110%
0
2
4
6
8
10
12
14
16
Frequency
Bin [c/l]
Histogram ‐ Diesel price
Frequency Cumulative %
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Figure 19 depict the histogram of the basic petrol price and this graph indicates that the
50% of the time the basic average petrol price was below 340c/l. The average basic petrol
price also follows the volatility of the oil price as discussed in relation to Figure 17.
Figure 19 - Petrol price histogram.
The histogram analysis results relation to the basic petrol and diesel prices were used in the sensitivity analysis section which follows later in the report.
0%10%20%30%40%50%60%70%80%90%100%110%
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Frequency
Bin [c/l]
Histogram ‐ Petrol price
Frequency Cumulative %
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Chapter6–Researchresults.
The presentation of the research results is done under three main headings; 1) The
financial performance of the GTL plant, 2) Break-even analysis of different sized GTL plants
and 3) a sensitivity analysis.
The financial performance results looked at the basic calculations and results that related
to the plant size (amount of products produced), the relationship between the different
products, thus the ratio of petrol to diesel and paraffin/kerosene, the price of the feedstock
(cost of the natural gas) and the price of the final products (basic fuel price). Part of this
section shows the results of the sensitivity of the NPV and the IRR under certain conditions.
The results of the break-even analysis follow the financial performance results. The break-
even analysis of the 260 000bbl/d plant was calculated followed by the 40 000bbl/d and the
25 000bbl/d plants. In this research break even analysis is determining the break-even point
(BEP), the BEP is defined as: the point at which cost or expenses and revenue are equal, thus
at the BEP there is no net financial loss or gain.
The sensitivity analysis concludes the presentation of the research results. The sensitivity
analyses looked at the impact of changing some of the crucial assumptions and/or some of the
variable. This was done to see the sensitive the results were to the assumptions and possibility
of changing the variable in the calculations.
6.1.TheFinancialperformanceoftheplant.
In this section of the chapter the analysis was focused on the basic calculations that were
needed to do the financial calculations followed by the results of the financial viability
calculations. These calculations include the operation expenditure (OPEX) calculations,
capital expenditure (CAPEX) calculations, conversion rations, total income (total loss) and
net present value (NPV) calculations.
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6.1.1. Basicinputsforthefinancialcalculations.
6.1.1.1. Differentplantsizes.
Different size plants were analysed to see if there are any relevance to the size of the plant
and the financial viability of the plant. Three different sized plants were used in the analysis
calculations. These are a 260 000 bbl/day, 40 000 bbl/day and a 25 000 bbl/day plant. These
are currently plants that are under design review in the Sasol group. A summary of the basic
financial attributes of the different sized plants are summarized in Table 6. The CAPEX
(capital expenditure) relates to the capital expenditure that must be incurred to build the plant
(inclusive of all the costs). The OPEX (operational expenditure) relates to the operational
costs, excluding the feedstock, to operate the plants. Table 5 shows the information regarding
the capital expenditure, the operational expenditure for the different size plant that was taken
into account in the research. The information in Table 6 was provided by Nadine Kruger at
Sasol Technology (Kruger, 2012).
Plant size information
BBL/day CAPEX OPEX OPEX per year [bR]
Project A 260 000 $19bn $6/barrel R4.78bn
Project B 40 000 $8bn $4.50/barrel R0.55bn
Project C 25 000 $4bn $5.5/barrel R0.422bn
Table 6 - General information relating to plant sizes. (Kruger, 2012)
Due to the confidentiality of the projects, the projects cannot be named and therefore the
projects are labelled Project A, B and C.
6.1.1.2. Weightedaverageproductprice.
The total sales/revenue of any production plant is the amount of products sold times the
price of the products. In the fuel conversion plant this works the same. The approach in this
case was to determine the weighted average product price times the amount of products
produced/sold, due to the closely matched supply and demand – as indicate in Table 1. The
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weighted average product price was calculated and the information is summarised in Table 7;
this price is based on the BFP in September 2012. The weights were derived from the
consumption averages of the different fuels as discussed Table 1.
Product price in cents
Product petrol diesel
paraffin/kerosene
products
Weighted percentage
(manufacturing) 50% 40% 10%
Current price per commodity [c/l] 700.8 c/l 723.0 c/l 709.1 c/l
Weighted price [c/l] 350.4 c/l 289.2 c/l 70.91 c/l
Weighted price [c/b] 42 050c/b 34 705 c/b 8 509 c/b
Total income [c/b] 85 265.5 c/b
Table 7 - Product price structure derived from the BFP
Table 7 also indicates that that the product manufacturing distribution between petrol
diesel and kerosene is 50%, 40% and 10%. Next the BFP price per commodity is indicated in
cents per litre. This price is multiplied by the manufacturing weight which leads to the
weighted price in cents per litre for each product. The price in cents per litre was converted to
the weighted price in cents per barrel, because the plant’s capacity is shown in barrels.
Finally the three weighted prices were added to get to a single final price per barrel of
products. The final price is 85 265.5 cents per barrel or R852.26 per barrel of final product.
6.1.1.3. Naturalgastofinalproductconversionrate.
In order to determine the input cost of the GTL plant, the conversion rate between natural
gas and a barrel of final product must be known. Table 8 shows a summary of the conversion
rates (gas to liquid) of different plants word wide. In the table Syntroleum estimates, Sasol
(Oryx), Shell (Pearl) and World Bank estimates are shown. For each of the above mentioned
plant the relationship between the barrels per day output and the feed gas ratio were
calculated. For instance the Sasol (Oryx) plant delivers 34 000 barrels of final product with a
feed stream of 97 million cubic feet of gas per day (MMcfd). This in turn leads to feed price
of R256.9 per barrels if the Gas price of July 2012 is used. If the above mentioned
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calculations are average out between Syntroleum estimates, Sasol (Oryx), Shell (Pearl) and
World Bank estimates; an average plant will need 10 100 cubic feet of natural gas to produce
1 barrel of final products (Chandra , 2012). This feed equates to a feed price of R267.5 to
produce on barrel of final product.
Table 8 - GLT conversion rate (Chandra , 2012).
6.1.1.4. Summaryofthebasicinputsintothefinancialcalculations.
The main inputs in the basic financial calculation are:
Plant size (amount of products produced).
Relationship between the different products, thus the ratio of petrol to diesel and
paraffin/kerosene.
The price of the feedstock (cost of the natural gas).
The price of the final products (basic fuel price).
Gas to liquid conversion rate (cubic feet gas to barrel liquid)
GTL gas requirements
Project
Plant size
[b/d]
Feed gas
[MMcfd]
Estimated
MMcfd
per 10
000 bpd
feed needed
per barrel
output [Cf]
feed cost per
barrel
output at
July 2012
price [R]
Syntroleum
estimates 100 1 100 10 000 R 264.87
Sasol (Oryx)
34 000 330 97 9 700 R 256.9
Shell (Pearl)
140 000 1600 114 11 400 R 301.9
World Bank
estimates 20 000 136 93 9 300 R 246.3
Average
101 10 100 R 267.5
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These four points were discussed in section 6.1.1 to section 6.1.4. Section 6.2 will look at
the first result of these inputs.
6.1.2. CashflowofanoperationalGTLplant.
This section of the research looked at the cash flow scenarios of the different sized GTL
plant. Two scenarios were looked at; the first scenario was if the plant was operation from
2001, the second scenario is looking at what the cash flow will be if a GTL plant will be
operated and the current (2012) oil price and gas prices will stay constant into the future. The
second scenario was looked at to see what will happen to the cash flow of a GTL plant with
favourable gas and oil prices.
6.1.2.1. ScenarioofaGTLplantinoperationsince2001.
The first step is to calculate the cumulative cash flow over time. This was done by adding
the negative investment value (CAPEX) to the negative OPEX and the positive sales value.
This value is added to the following year’s OPEX and sales (CAPEX is a once off cost). The
results of these calculations for the different plant sizes are shown in Figure 20. The OPEX
and sales values were calculated using the changing gas and oil price. For instance the OPEX
in February 2003 were calculated by using the gas price of February 2003. In the same
manner the selling price of the final product was calculated by using the weighted average
price of fuel in February 2003.
Figure 20 shows the cumulative income for the three different sized plants. The figure
shows that the negative trend turns between March 2009 and April 2010 for the different
plants. This is dues to the high oil price (determining the basic fuel price) and the low gas
price (which is used as the feedstock cost) as shown in Figure 16 which tends to be
favourable for the GTL plants. The conclusion for the figures is that none of the plant would
have made any money (shown a positive cash flow) if the plant were built in 2001. The
second conclusion that can be made from Figure 20 is that there was a positive cash flow for
the first time in middle 2010, year on year,
The figure also shows a significant difference in the performance of the different sized
plant. The 260 000bbl/d plant showed the biggest loss, this is due to the high operation cost
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and the huge capital investment in the beginning. It can also be concluded that the capital
expenditure is only a fraction of the negative cash flow; for the 260 000 bbl/d plant the
CAPEX was only R159b versus the R2630b cumulative impact up to 2010of the operational
cost that could not be recovered by the total income up to mid-2010.
Figure 20 - Cumulative income if the plant had been operational from the year 2001.
6.1.2.2. ScenarioofaGTLplantinoperationfrom2012to2023.
This section shows what will happen if a GTL plant will operate at the current oil price
and gas price. This section is not intended to predict what the oil and gas price will be in the
future, merely the result if the plant is built now and operated for the next 11 years.
‐3000
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0
Jan‐2001
Jul‐2001
Jan‐2002
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Jul‐2007
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Jul‐2008
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Jul‐2009
Jan‐2010
Jul‐2010
Jan‐2011
Jul‐2011
Jan‐2012
[Rb]
Scenario if the plants were operational for the past 11 years
cumlative income (260 000bbl/d) cumlative income (40 000bbl/d)
cumlative income (25 000bbl/d)
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If these plants had been built under the current favourable economic conditions in terms of
the low gas price and the high oil price which in turn relate to high fuel prices, the outcome
will be vastly different. Figure 21 depicts the results of these favourable conditions. It is
evident from Figure 20 and Figure 21 that the economic conditions have a tremendous impact
on the financial outcome of the plants. The gas price that was used in this calculation was
$3.27 per 1000cf and the oil price was $113 per barrel which relates to fuel prices of over
720c/l. In contrast to Figure 20, Figure 21shows a favourable result. Figure 21 can be
interpreted that the negative CAPEX is made up by the positive income of the operations
within the firsts 2 to 3 years of the plants; it is also similar for the three different sized plants.
It is also evident form Figure 21that the larger plant will make significantly more money,
despite of the larger CAPEX in the beginning. Thus sit can be concluded that under the right
conditions the all the different sized plants can make a tremendous amount of money.
If one would look at Figure 20and Figure 21together it can be concluded that he external
factors, in this case the gas and oil price, has a tremendous effect on the financial viability
and cash flow of the plants.
Figure 21 –Cumulative income if the plants had been operational for the next 11 years.
‐200
0
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400
600
800
1000
1200
Jun ‐2012
Dec ‐2012
Jun ‐2013
Dec ‐2013
Jun ‐2014
Dec ‐2014
Jun ‐2015
Dec ‐2015
Jun ‐2016
Dec ‐2016
Jun ‐2017
Dec ‐2017
Jun ‐2018
Dec ‐2018
Jun ‐2019
Dec ‐2019
Jun ‐2020
Dec ‐2020
Jun ‐2021
Dec ‐2021
Jun ‐2022
Dec ‐2022
Jun ‐2023
[Rb]
Scenario if the plants will be operational for the next 11 years
cumlative income (260 000bbl/d) cumlative income (40 000bbl/d)
cumlative income (25 000bbl/d)
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6.1.3. Netpresentvaluesandtheinternalrateofreturn.
Using the current favourable economic conditions (current oil and gas price) the net
present values (NPV) and the internal rate of return (IIR) was calculated; the current NPV for
the 260 000bbl/d plant will be R356b. This relates to an IIR of 46%. Due to the volatility in
this market a sensitivity analysis was also done (see Table 9, Table 10 and Figure 22 for the
results). Two sensitivity analyses were done; the first sensitivity analysis that was done
incorporated he change in the hurdle rate and the total income of the plants, the second
sensitivity analysis related to the change of the operation horizon of the plant.
The first sensitivity analysis looked at what will happen if the income per year will vary,
additionally looking at what will happen if the hurdle rate would change. The results of this
sensitivity analysis are shown in Table 9. Table 9 shows the scenarios that were created to
test the sensitivity of the calculations. Five scenarios were created, namely: 1) low income
scenario where the income was lowered to R10b per year, 2) high income scenarios where the
income of R100b per year was used, 3) an average income scenario, where an income of
R45b per year was used. In the fourth and fifth scenario the income was kept at the original
value of R73.4b per year but the hurdle rate was changed to 5% and 20 % respectively.
On the low income (only R10b per year) scenario the NPV is negative and leads to a loss
making plant, even the average income plant of R45b lead to a positive NPV of R156b. By
changing the discount rate the NPV also varied tremendously as expected. On a discount rate
of 5% and using the original values of R73b the NPV was R755b. Even with a high discount
rate of 20% the calculations showed a favourable NPV of R197b.
In conclusion Table 9 shows that low income scenario lead to a negative NPV and an IRR
under the hurdle rate, both shows that this will not be a favourable sensation to operate at.
The high income scenario leads to a NPV of R542b and an IRR of 63%, the average income
scenario leads also to favourable results of R156b for a NPV and an IRR of 28%. As
expected the two scenarios where the hurdle rate was changes, the NPV was also impacted,
although both the scenarios showed a favourable positive NPV of R197b and R755b
respectively.
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Table 9 - Sensitivity analysis on the NPV and IIR (changing income).
By changing the operations horizon also had a significant impact on the NPV. In this
sensitivity analysis everything stayed constant except the operation horizon changed between
2 years and 20 years. This approach developed another 3 scenarios to test the sensitivity of
the length of the term on the results. The three additional scenarios are shown in Table 10 are;
1) very short term where a 2 year operational horizon was used, 2) short term where a 4 year
operation horizon was used, 3) medium term where the operational horizon was set at 10
years.
Table 10 shows the results of the sensitivity analysis, the results shows that only the 2 year
operation horizon (which was the very short term horizon) gave a negative NPV. The short
term and medium term scenarios both indicated a positive NPV if the plant would operate
under the current oil and gas prices over the respective operational horizons. In all there the
scenarios the total income per years was unchanged and the original hurdle rate was used.
Scenario SummaryCurrent
Values: low income
high
income
average
income
high hurdle
rate
low hurdle
rate
Changing Cells:
income 73.4 10 100 45 73.4 73.4
hurdle rate 0.13 0.13 0.13 0.13 0.2 0.05
years 20 20 20 20 20 20
Result Cells:
NPV R 356.02 R ‐89.35 R 542.88 R 156.51 R 197.83 R 755.13
IRR 46% 2% 63% 28% 46% 46%
Notes: Current Values column represents values of changing cells at
time Scenario Summary Report was created. Changing cells for each
scenario are highlighted in gray.
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Table 10 - Sensitivity analysis on the NPV and IIR (operation horizon).
By combining the previous two sensitivity analysis that was discussed in relation to Table
9 and Table 10, twenty four scenarios were created altogether. The results of the twenty four
scenarios are depicted in Figure 22.
Figure 22 shows that with a low income plant (R10b per year) almost none of the
scenarios are favourable, the low income will be due to a low oil price which inherently leads
to a low BFP as discussed earlier. In contrast the high income scenario (R100b per year)
shows all but one negative NPV, the negative NPV of –R6.8b is the most conservative
scenario where the hurdle rate is 20% and the operational horizon is only 2 years. By
interpreting the average income per year scenario (R45b per year), the results was only
positive if the operation horizon was the medium scenario (10 years) or long term scenario
(20 years) operation horizon. Both the short term and very short term scenarios had a
negative NPV.
In conclusion Figure 22 shows that the maximum NPV was obtained with the scenario of
long term operation with a high income and a low discount rate, which resulted in a NPV of
R1086b. The lowest NPV was calculated with the low income very short term operation
horizon and a high discount rate, the NPV was –R144b. Both the average income and the
high income scenarios resulted in an IRR’s of 63% and 28% respectively, which is above the
Scenario SummaryCurrent
Values:
very short
term short term
medium
term long term
Changing Cells:
income 73.4 73.4 73.4 73.4 73.4
hurdle rate 0.13 0.13 0.13 0.13 0.13
years 20 2 4 10 20
Result Cells:
NPV R 356.02 R ‐37.16 R 58.73 R 238.69 R 356.02
IRR 46% 46% 46% 46% 46%
Notes: Current Values column represents values of changing cells at
time Scenario Summary Report was created. Changing cells for each
scenario are highlighted in gray.
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original hurdle rate. In contrast to this the low income scenario resulted in an IRR of 2%
which is below the original assumed hurdle rate of 13%.
Figure 22 - Sensitivity analysis summary regarding the NPV and the IIR.
0%
10%
20%
30%
40%
50%
60%
70%
‐400
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0
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800
1000
1200
long term
med
ium term
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ium term
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ium term
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ium term
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ium term
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ium term
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high hurdle rate
low hurdle rate
high hurdle rate
low hurdle rate
high hurdle rate
low hurdle rate
average income high income low incomeIIR
NPV in
Rb
Sensitivity analysis on the NPV and the IRR values
NPV IIR
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6.2. BreakevenanalysisofdifferentsizedGTLplants.
This section of the report looked at the break-even analysis to determine the break-even
point of the operation of the different sized plants. As described in the methodology section a
break-even analysis is a technique used by production management and management
accountants. Break-even analysis is based on categorising production costs between variable
cost (costs that change when the production output changes) and fixed cost (costs not directly
related to the volume of production). To calculate the break-even point the total variable and
fixed costs are compared with sales revenue in order to determine the level of sales volume,
sales value or production at which the business makes neither a profit nor a loss. If a
facility/project can operate above the break-even point the facility/project will be favourable
at that production point and beyond (Cafferky & Wentworth, 2010). First the break-even
analysis of the 260 000bbl/d plant was calculated followed by the 40 000bbl/d and the
25 000bbl/d plants. In this research break even analysis is determining the break-even point
(BEP), the BEP is defined as: the point at which cost or expenses and revenue are equal, thus
at the BEP there is no net financial loss or gain.
Firstly the BEP for the plant was calculated using the current economic conditions (as if
the plant will be operational from now on into the future) and secondly the BEP was
calculated using the oil and gas price of a specific year to calculate the BEP for the specific
year.
6.2.1. Breakevenanalysisofthe260000bbl/dplant.
The break even analysis was calculated by looking when the income surpasses the total
expenses, including the CAPEX. All the calculation was done at the current economic values.
The total cost to operate is the CAPEX plus the OPEX cost plus the cost of the feedstock (the
OPEX in this graph does not include the feedstock price). The red line in Figure 23 represents
the total operating cost. The income was determined by using the BFP (as discussed in
Chapter 5). The “total income” line in Figure 23 does not include tax payment. The income
after tax was only calculated after the plant shows a profit (after the break-even point). This is
illustrated by the line “total cumulative income after tax”. The total income surpassed the
total cumulative cost to operate in year 3 of operation.
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Figure 23 - Break even analysis of the 260 000bbl/d plant.
Figure 23 can be interpreted by determining when the total income line surpasses the total
cumulative cost – the total cumulative cost includes the variable cost, fixed cost and the
CAPEX of the plant. Referring to Figure 23; the total cumulative operating cost is the sum of
the CAPEX, feedstock price per year and the cumulative OPEX. In Figure 23 is clearly
shown that the break-even point in between 3 and 4 years of operation. In conclusion Figure
23 shows break-even point of 3-4 years if the 260 000bbl/d plant will be operation under
current economic conditions (the current oil and gas price)
6.2.2. Breakevenanalysisofthe40000bbl/dplant.
The break even analysis was calculated by looking when the income surpasses the total
expenses, including the CAPEX. All the calculation was done at the current economic values.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
1 3 5 7 9 11 13 15 17 19 21 23
Rb
Years
Break even analysis for a 260 000 bbl/day plant (current economic values)
capex
cumilative opex
feedstock price per year
Total cumilative operating cost
Total cumilative income after Tax
total income
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The total cost to operate is the CAPEX plus the OPEX cost plus the cost of the feedstock (the
OPEX in this graph does not include the feedstock price). The red line in Figure 24 represents
the total operating cost. The income was determined by using the BFP (as discussed in
Chapter 5). The “total income” line in Figure 24 does not include tax payment. The income
after tax was only calculated after the plant shows a profit (after the break-even point). This is
illustrated by the line “total cumulative income after tax”. The total income surpassed the
total cumulative cost to operate in year 9 of operation
Figure 24 - Break even analysis of the 40 000bbl/d plant.
Figure 24can be interpreted by determining when the total income line surpasses the total
cumulative cost – the total cumulative cost includes the variable cost, fixed cost and the
CAPEX of the plant. Referring to Figure 23; the total cumulative operating cost is the sum of
the CAPEX, feedstock price per year and the cumulative OPEX. Figure 23 is clearly shown
that the break-even point in between 9 and 10 years of operation. Figure 24 shows break-even
0
50
100
150
200
250
300
1 3 5 7 9 11 13 15 17 19 21 23
Rb
Years
Break even analysis for a 40 000 bbl/day plant (current economic values)
capex
cumilative opex
feedstock price per year
Total cumilative operating cost
Total cumilative income after Tax
total income
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point of 9-10 years if the 400 000bbl/d plant will be operation under current economic
conditions (the current oil and gas price)
6.2.3. Breakevenanalysisofthe25000bbl/dplant.
The break even analysis was calculated by looking at when the income surpasses the total
expenses, including the CAPEX. All the calculation was done at the current economic values.
The total cost to operate is the CAPEX plus the OPEX cost plus the cost of the feedstock (the
OPEX in this graph does not include the feedstock price). The red line in Figure 25 represents
the total operating cost. The income was determined by using the BFP (as discussed in
Chapter 5). The “total income” line in Figure 25 does not include tax payment. The income
after tax was only calculated after the plant shows a profit (after the break-even point). This is
illustrated by the line “total cumulative income after tax”. The total income surpassed the
total cumulative cost to operate in year 7 of operation.
Figure 25 - Break even analysis of the 25 000bbl/d plant.
0
20
40
60
80
100
120
140
160
180
200
1 3 5 7 9 11 13 15 17 19 21 23
Rb
Years
Break even analysis for a 25 000 bbl/day plant (current economic values)
capex
cumilative opex
feedstock price per year
Total cumilative operating cost
Total cumilative income after Tax
total income
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Figure 25 can be interpreted by determining when the total income line surpasses the total
cumulative cost – the total cumulative cost includes the variable cost, fixed cost and the
CAPEX of the plant. Referring to Figure 25; the total cumulative operating cost is the sum of
the CAPEX, feedstock price per year and the cumulative OPEX. In Figure 25 is clearly
shown that the break-even point in between 7 and 8 years of operation. In conclusion Figure
25 shows break-even point of 7-8 years if the 25 000bbl/d plant will be operation under
current economic conditions (the current oil and gas price)
Interpreting Figure 23, Figure 24 and Figure 25 together it is clear the 260 000bbl/d plant
will reach the BEP far quicker than the other 2 plant. The conclusion from Figure 23, Figure
24 and Figure 25 is that it will be better to build the 260 000bbl/d plant if the capital is
available and if the plant will be operational with the current oil and gas price in tot the
future.
6.2.4. Break‐evenpointataspecificyear'seconomicvalues.
The previous section looked at the break-even point at the current economic values, i.e. the
current oil and gas price (July 2012). This section looked at the break-even point if a plant
would have operated at a specific year’s economic values. Thus the BEP was calculated using
the oil price, gas price and the average BFP of that year, for instance if the BEP was
calculated for a plant operating in 2009 the oil price, gas price and the BFP for 2009 was used
and it was assumed the data will stay constant over time. This resulted in in a BEP for each
year.
The results of the break-even calculations are illustrated in Figure 26. If there was no
break-even point the graph shows a zero (i.e. the break even calculation did not converge).
This happen because there is no converging point between the total costs to operate the plant
and the total income of the plant, meaning the plant keep on making a loss. This is illustrated
in Figure 27 where the red line (total operating cost always stays above the “total income”
line). Figure 26 shows that there was really only an applicable break-even point from early
2011 onwards. This was due to the economic values that started to be favourable, a low gas
price and a high oil price that lead to high fuel prices.
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Figure 26 – Break-even analysis at a specific year's economic values.
Figure 26 shows the results of the BEP calculations for each year. This figure can be
interpreted as that there was no significant BEP before early-2009; this is also evident for the
period from end-2009 to mid-2010. In conclusion Figure 26 shows that the BEP improves
from mid-201o up to mid-2012. This improvement in the BEP can be contributed to the fact
that the oil price is high which leads to an increase in the BFP, which in turn lead to a greater
income, secondly to the lower gas price which lead to a lower feedstock cost which in turns
leads to lower total costs.
Figure 27 is an example of the BEP depiction of a year that did not converge to a BEP,
thus the total operating cost always stayed above the total income line. Thus the interpretation
of Figure 27 is that the plant will keep on making a loss if the oil price and the gas price stay
constant at the 2009 values; concluding that a plant must have a BEP to be able to make a
profit over time.
0
10
20
30
40
50
60
70
80Jan ‐2001
Jul ‐2001
Jan ‐2002
Jul ‐2002
Jan ‐2003
Jul ‐2003
Jan ‐2004
Jul ‐2004
Jan ‐2005
Jul ‐2005
Jan ‐2006
Jul ‐2006
Jan ‐2007
Jul ‐2007
Jan ‐2008
Jul ‐2008
Jan ‐2009
Jul ‐2009
Jan ‐2010
Jul ‐2010
Jan ‐2011
Jul ‐2011
Jan ‐2012
Years to break even point
Years to operate to break even at a specific year's economic factors
break even years (260 000bbl/d) break even years (40 000bbl/d)
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Figure 27 – Break even analysis not converging.
Figure 28 and Figure 29 shows the histograms for the 260 000bbl/d and the 40 000bbl/d
plant’s break even analysis. Figure 28 and Figure 29 should be interpreted by looking at the
frequency of the “zero” years. As previously said if there was no conversion of the total
income and total operation costs, no BEP could be calculated and then the BEP value was set
to zero for practical purposed. Thus the frequency of the zero years is indicative of the
frequency when there is no BEP, thus the frequency of the year when it would have been
impossible for the plant to show a profit over time. .
What should be highlighted in Figure 28 is that in the case of the 260 000bbl/d plant is
78.8% of the past 12 years there was no possibility to reach a break-even point.
0
200
400
600
800
1000
1200
1400
1600
1800
1 3 5 7 9 11 13 15 17 19 21 23
Rb
Years
Break even analysis for a 260 000 bbl/day plant (economic values of early 2009)
capex
cumilative opex
feedstock price per year
Total cumilative operating cost
Total cumilative income after Tax
total income
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Figure 28 - Histogram for the BEP on the 260 000bbl/d plant.
In Figure 29 one can concludes that in the case of the 40 000bbl/d plant there were 83.21%
of the cases that did not have a break-even point.
Figure 29 - Histogram for the BEP on the 40 000bbl/d plant.
0%
20%
40%
60%
80%
100%
0
20
40
60
80
100
120
0 2 4 6 8 10 12 16 20 24 28 32 40 48 56 70 84
Frequency
break even years
Histogram for the BEP on the 260 000bbl/d plant
Frequency Cumulative %
0%
20%
40%
60%
80%
100%
0
20
40
60
80
100
120
0 2 4 6 8 10 12 16 20 24 28 32 40 48 56 70 84
Frequency
break even years
Histogram for the BEP on the 40 000bbl/d plant
Frequency Cumulative %
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The conclusion drawn from Figure 28 and Figure 29 is that for an overwhelming
frequency of the time none of the plants in question were able to reach a BEP.
By combining the break-even analysis graph with the ratio between the gas price and the
oil price in Figure 30, it is evident that if there is a high ratio between the oil price and the gas
price (i.e. oil price divide by the gas price) there is low break-even point for the different
plants. In Figure 30 it is clearly shown that in January 2010 the ratio dropped after a steady
decrease in 2009, this resulted in no break-even point. From January 2011 the ratio increased
from just over 16 to the current ratio of over 32. This resulted in a drop in the break-even
point from 9 to 4 years for the 260 000bbl/d plant and positive result from 25 to 9 years for
the 40 000bbl/d plant.
Figure 30 –Oil- gas price ratio vs. BEP.
The conclusion drawn from Figure 30 it that if there is a significantly high ratio between
the oil price and the gas price, there is a BEP that can be calculated, if the BEP could not be
0
5
10
15
20
25
30
35
40
0
10
20
30
40
50
60
70
80
Jan ‐2001
Jul ‐2001
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Jul ‐2003
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Jul ‐2005
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Jul ‐2007
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Jul ‐2009
Jan ‐2010
Jul ‐2010
Jan ‐2011
Jul ‐2011
Jan ‐2012
Ration beteen the oil an
d gas price
Years to break even point
Oil ‐ gas price ratio and BEP plot
break even years (260 000bbl/d) break even years ‐ 40 000bbl/d
oil price to gas price ratio
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calculated the ration between the oil and the gas price was low. The ration between the oil
and the gas price must be above 16 to be able to calculate a BEP.
6.3. Sensitivityanalysis.
This section looks at the different scenarios of changing some of the variables in the
previous calculations to determine the effect on the outcome. For instance the OPEX used in
the original calculation was R4.78/b, what will the effect on the calculations be if this
variable (others) are increased or decreased. Firstly scenarios were developed to determine
the sensitivity of the total income at the BEP (BEP from the previous section was used.
Secondly the scenarios were developed to determine the sensitivity of a plant that would be in
operation for 10 years and lastly scenarios were developed to determine the sensitivity of a
plant that would be in operation for 20 years.
6.3.1. Sensitivityanalysisatthebreak‐evenpoint.
In the original calculations the financial analysis and the break even analysis figures of
50% petrol production and 40% diesel production and 10% kerosene/paraffin production
were used from Table 1 to calculate the product distribution and weighted average product
price Furthermore the OPEX for the 260 000bbl/d plant was calculated as R4.78/b per year.
This sensitivity analysis was done to see what the effect was if these values were changes.
Table 11 shows the 8 scenarios that were created to determine the sensitivity of the
calculations. Mainly the ratios between the different types of fuels were changed together
with the operational cost was changed. The eight scenarios that were developed were:
1. A high diesel scenario where the percentage diesel was changed to 50% from the
original 40%.
2. An equal diesel and petrol manufacturing scenario where the diesel percentage was
changed to 45% form 40% and the petrol was changed form 50% to 45%.
3. A scenario where only diesel and kerosene would be manufactured; changing the
diesel percentage from 40% to 90%.
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4. A scenario where only petrol and kerosene would be manufactured; changing the
petrol percentage from 50% to 90%.
5. A scenario here the original distribution between petrol, diesel and kerosene was used
but the operation cost was changed from R4.78b per year to a high operational cost of
R6b per year.
6. A scenario here the original distribution between petrol, diesel and kerosene was used
but the operation cost was changed from R4.78b per year to a low operational cost of
R3b per year.
7. A scenario here the original distribution between petrol, diesel and kerosene was used
but the operation cost was changed from R4.78b per year to a very high operational
cost of R10b per year.
Table 11 – Sensitivity analysis summary.
The BEP years used for the calculations are the same as the results in Figure 26, except for
when there was no converging value in the break-even analysis; a 100 year BEP was used for
the calculations. This was done to see the effect of the different scenarios (different than in
the previous section zero was not used because this would have nullified the equations) which
would have resulted in zero values due to the multiplication with zero. The values that were
Scenario
Summary
Current
Values:
high
diesel
equal
diesel
and
petrol
only
diesel
only
petrol
high
operating
cost
low
operating
cost
very high
operating
cost
Changing Cells:
% petrol sales 0.5 0.4 0.45 0 0.9 0.5 0.5 0.5
% diesel sales 0.4 0.5 0.45 0.9 0 0.4 0.4 0.4
% paraffin/
kerosene sales
0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1
OPEX
[RB/year]
R4.78b R4.78b R4.78b R4.78b R4.78b R6b R3b R10b
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calculated in the sensitivity analysis are the total income of the 260 000bbl/d plant. The
feedstock price and the selling price of the fuels are still the values that are specific to a
specific year as in the previous sections.
The results of the sensitivity analysis are represented in Figure 31. The zero line is the
break-even point in the graph. Thus at the current values and if there is a converging break-
even point the value of the line will be close zero (no loss neither no gain).
Figure 31 - Sensitivity analysis of the BEP.
Figure 31 can be interpreted as: by selling only petrol, operating with high operation cost
or by operating with very high operation cost had an impact between September 2010 and
March 2011. After March 2011 only the very high operating cost had a significant impact on
the income around the BEP. The far negative values in Figure 31 can be ignored due to the
sensitivity analysis calculations were done with a 100 year BEP if there was no converging
‐4500
‐4000
‐3500
‐3000
‐2500
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‐1500
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‐500
0
500
1000
Mar ‐2007
Jun ‐2007
Sep ‐2007
Dec ‐2007
Mar ‐2008
Jun ‐2008
Sep ‐2008
Dec ‐2008
Mar ‐2009
Jun ‐2009
Sep ‐2009
Dec ‐2009
Mar ‐2010
Jun ‐2010
Sep ‐2010
Dec ‐2010
Mar ‐2011
Jun ‐2011
Sep ‐2011
Dec ‐2011
Mar ‐2012
Jun ‐2012
Total cumilative income [Rb]
Sensitivity analysis @ BEP
Current Values: high diesel equil diesel and petrol
only diesel only petrol high operating cost
low operating cost very high operationg cost
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value found (which in real term the BEP is at infinity and the calculations would have been
out if range, anything time infinity is infinity). These values just show the impact of the
different scenarios on the total income in a specific year.
Figure 32 is a focused view of Figure 31. By interpreting Figure 32 it can be seen that the
very high operation cost scenarios is the only scenario out of the eight scenarios described
above that had a significant impact on the total income around the BEP from March 2011
onwards. The conclusion drawn from the Figure 31 and Figure 32 is that the sensitivity
around the BEP is very low in all the scenarios except in the scenarios of very high operation
cost.
Figure 32 - Sensitivity analysis of the BEP (May 2010 onwards).
‐200
‐150
‐100
‐50
0
50
100
May ‐2010
Jun ‐2010
Jul ‐2010
Aug ‐2010
Sep ‐2010
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Oct ‐2011
Nov ‐2011
Dec ‐2011
Jan ‐2012
Feb ‐2012
Mar ‐2012
Apr ‐2012
May ‐2012
Jun ‐2012
Total cumilative income [Rb]
Sensitivity analysis @ BEP form may 2010
Current Values: high diesel equil diesel and petrol
only diesel only petrol high operating cost
low operating cost very high operationg cost
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6.3.2. Sensitivityanalysisat10yearsoperation
In the previous the total income was calculated around the BEP, which cannot be used for
comparison purposes between the different year’s economical values, because the BEP are
different for each year and the BEP value are used to calculate the total income. Thus if the
BEP is lower the total income will be lower.
This section looked at what will the total income be for each of the sensitivity analysis
after 10 years of operation using the economical values for each specific year (thus using the
oil price and gas price of a specific year and calculating the cash flow after 10 years of
operation).
Figure 33 - Sensitivity analysis with a constant operation horizon of 10 years.
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‐400
‐300
‐200
‐100
0
100
200
Mar ‐2007
Jun ‐2007
Sep ‐2007
Dec ‐2007
Mar ‐2008
Jun ‐2008
Sep ‐2008
Dec ‐2008
Mar ‐2009
Jun ‐2009
Sep ‐2009
Dec ‐2009
Mar ‐2010
Jun ‐2010
Sep ‐2010
Dec ‐2010
Mar ‐2011
Jun ‐2011
Sep ‐2011
Dec ‐2011
Mar ‐2012
Jun ‐2012
Total cumulative
income [Rb]
Sensitivity analysis @ 10 year operation
Current Values: high diesel equil diesel and petrol
only diesel only petrol high operating cost
low operating cost very high operationg cost
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Figure 33 depicts the total income values for each scenario after 10 years of operation.
Figure 33 can be interpreted that from March 2011 all the scenarios show a positive income
after 10 years of operation except for the very high operational cost scenario which only
shows a constant positive income after 10 years of operation using the favourable oil and gas
price form September 2011 Figure 34 shows the range between the best and the worst
scenario and the small block indicates the standard scenario (current economic values). What
is significant is the small range in the latter part of the graph, from March 2011 onwards.
From Figure 33 and Figure 34 the conclusion is that the different scenarios did not have a
significant impact on the total income of the 260 000bbl/d plant. Thus if the oil gas price
ration is big the impact of the different scenarios are less due to the overwhelming impact of
the profit versus the cost to make the product. Thus the calculations are insensitive to the
changes that were made to the calculations.
Figure 34 – Maximum and minimum range in the sensitivity analysis.
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‐300
‐200
‐100
0
100
200
Mar ‐2007
Jun ‐2007
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Dec ‐2010
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Jun ‐2011
Sep ‐2011
Dec ‐2011
Mar ‐2012
Jun ‐2012
Totalcumilative income [Rb]
Range of the maximum and minimum values in the scenario analysis
standard scenario value
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6.3.3. Sensitivityanalysisat20yearsoperation.
This section of the research looked at what the effect would be if the plant was not only
operational for 10 years but for 20 years. The same sensitivity analysis that was done for the
10 year operations was done for 20 year operation with the only difference of the operational
time span. After the calculations were done it was evident that there were no significant
difference in the results for the 10 year operation, the only difference being the scale of the
loss or profit.
Figure 35 - Sensitivity analysis for the 260 000bbl/d plant after 20 years of operation.
Figure 35 depicts the total income values for each scenario after 20 years of operation.
Figure 35 can be interpreted that from March 2011 all the scenarios show a positive income
‐1200
‐1000
‐800
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‐400
‐200
0
200
400
Mar ‐2007
Jun ‐2007
Sep ‐2007
Dec ‐2007
Mar ‐2008
Jun ‐2008
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Mar ‐2009
Jun ‐2009
Sep ‐2009
Dec ‐2009
Mar ‐2010
Jun ‐2010
Sep ‐2010
Dec ‐2010
Mar ‐2011
Jun ‐2011
Sep ‐2011
Dec ‐2011
Mar ‐2012
Jun ‐2012
[Rb]
Sensitivity analysis @ 20 year operation
Current Values: high diesel equil diesel and petrol
only diesel only petrol high operating cost
low operating cost very high operationg cost
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after 20 years of operation, including the very high operational cost scenario which is in
contrast with the results after 10 years of operation; where the positive cash flow in the very
high operation cost only showed a positive cash flow with the oil and gas price from
September 2011 which was more favourable than the values used form March 2011. From
Figure 35 the conclusion is that the different scenarios did not have a significant impact on
the total income of the 260 000bbl/d plant. Thus if the oil gas price ration is big the impact of
the different scenarios are less due to the overwhelming impact of the profit versus the cost to
make the product. Thus the calculations are insensitive to the changes that were made to the
calculations.
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Chapter7–Summary,conclusionandrecommendations.
7. Summaryandconclusion.
This last section of the report addresses the limitations of the research, what possible
future research can sprout from this research report and what are the main conclusions of this
research.
7.1. Researchlimitations.
There are a couple limitations that should be mentioned or considerations that was not
included in this research:
Future Carbon tax possibilities and or environmental law impacts.
The renewal program (replacement of main equipment when they reach end of life)
for the plant was not included, which will lead to addition OPEX in the long term.
This research did not include the effect of inflation on the calculations.
Increase of the energy cost (this will have a negative effect on the outcome, because
the OPEX will increase as the energy cost increases.
This research was also limited to only 3 different plant sizes, and the bulk of the
calculation was done on the 260 000bbl/d plant.
7.2. Futureresearchdirections.
Further research may look at comparing the results of a GTL plant to selling the raw gas
without converting the gas to liquid products. The same analysis should be done in terms of
the CAPEX, and OPEX of a gas field and then selling the gas at the industrial gas price. This
could be extended by combining the results of the two
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7.3. Conclusion.
Natural gas can be extracted via conventional and unconventional methods. Previously the
unconventional methods were very expensive, but this changed due to recent breakthroughs
in technology namely horizontal drilling and hydraulic fracking. The hydraulic fracking gave
rise to the possibilities of extracting natural gas from gas fields previously seen as
unreachable or too expansive to extract. Due to this increase of gas to the market the gas price
dropped significantly over the recent period. Selling gas at the current gas price, presents a
dilemma in terms of the return on investment. An opportunity presents itself in the form of
gas-to-liquid technology. It is believed that it will be financial viable in the long and short
term to convert the natural gas, specifically shale gas, into the liquid fuels. This research
looked at aspects of the breakeven point on a specific size of the plant, the influence of the
prices of the feedstock on financial viability of such an investment.
Sasol recently bought 50% of a shale gas field in Canada and is in partnership with
Talisman in this endeavour. The current gas price does not make this investment very
lucrative and has an impact on the share price of the company (which is difficult to quantify).
This indicates that Sasol is interested in the perusing the natural gas market. The research
specifically focused on the South African marker if Sasol would introduce the GTL
technology with a feed stock of natural gas.
Due to the recent volatility in the gas prices that this research looked at the impact of the
gas price over time on the outcome of the viability of GTL plant and to determined what gas
price it would be more viable to sell the raw gas and not the refined gas, due to the fixed and
variable cost coupled to the refining of the gas.
The expected plant life is in excess of 20 years (which is possible with normal operations)
with incorporating the correct maintenance strategies to maintain the health of the plant. With
a healthy plant the research indicates that a GTL plant will be financial viable with natural
gas as the feedstock to the GTL plant if the gas price is low and the oil price is high. The gas
price must be low to limit the input cost to the plant and the oil price must be high, because
the oil price inherently determines the basic fuel price which is the selling price of the fuel.
The second research deduction that can be made is that if the economic factors are favourable
for the GTL plant, the sensitivity analysis indicates that the different variable in the
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calculation have little to no impact on the end results. It is only the gas price and the oil price
that has a significant impact on the financial viability of the plant. The contrary is also true;
if the economic factors are unfavourable the variability in the variables does have a
significant impact on the financial viability of the plant.
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Appendix1–FisherTropschprocess
The following is a very short description of the basic Fischer-Tropsch process:
The Fischer-Tropsch process involves the conversion of syngas, a mixture of hydrogen
and carbon monoxide, into liquid fuels.
Syngas is produced from coal (via a gasification process, which involves coal, steam and
oxygen), natural gas or biomass.
The syngas is passed at high temperature and pressure (after the gas went through a couple
of cleaning process to remove all the unwanted chemical in the feed stream such as sulphur)
over a catalyst which speeds up the reaction of the gases together to form larger products.
The catalyst used is often iron in high temperature Fischer-Tropsch reactors or cobalt/nickel
in low temperature Fischer-Tropsch reactors.
In the reaction a number of products are forms of which one is water but the most
important in the hydrocarbons chains that forms. The longer the hydrocarbon chains the
heavier the fuel (i.e. Diesel has a longer hydrocarbon chain than petrol after it has been
refined). The lightest product is methane (CH4); longer chains give liquid fuels such as petrol
and diesel.
The products are separated, cleaned and may be processed further to increase yields of
desirable products, then are ready to use. The whole process is summarised in the diagram
below.
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Appendix 2 – Descriptive statistics of the fuel prices and the oil
price.
Average petrol
price (c/l)
Diesel
price (c/l)
Paraffin
Price (c/l)
Average Brent Crude
price ($/b)
Mean 364.47 370.093 363.789 59.71
Standard Error 14.82 14.883 14.474 2.56
Median 338.63 351.63 345.128 56.37
Mode 307.63 424.03 222.618 31.4
Standard
Deviation
183.42 184.144 179.104 31.71
Sample Variance 33 644.10 33 910.56 32 076.91 1 005.97
Kurtosis -0.247 -0.2661 -0.2206 -0.785
Skewness 0.78 0.74 0.78 0.58
Range 773.413 779.203 737.318 115.12
Minimum 119.217 118.827 131.81 18.52
Maximum 892.63 898.03 869.12 133.64
Sum 55 764.62 56 624.09 55 659.77 9 136.37
Count 153 153 153 153
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Appendix3‐Declaration
1. I know that plagiarism is wrong. Plagiarism is to use another‘s work and pretend that
it is one‘s own work.
2. I have used the APA convention to citation and referencing. Each contribution to, and
quotation in, this project from the work(s) of other people has been attributed, and has
been cited and referenced.
3. This project is my own work.
4. I have not allowed, and will not allow, anyone to copy my work with the intention of
passing it off as his or her own work.
Leon Claassen
Date: November 2012
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Appendix4–Researchethicsdeclaration.
All research conducted in the Graduate School of Business (GSB), which includes the
research conducted for academic credit by GBS students; must be approved by the GSB
ethics committee if the research involves the participation of human beings.
There are no humans involved in the intended research as stipulated in the above section,
therefore no approval of the ethics committee is needed to progress with the intended
research.
Leon Claassen
Date: November 2012
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77
Bibliography
Bao, B., El-Halwagi, M., & Elbashir, N. (2012). Simulation, integration, and economic
analysis of gas-to-liquid processes. Fuel Processing Technology, 91, 703–713.
Masih, M., Albinali, K., & DeMello, L. (2010). Price dynamics of natural gas and the
regional methanol markets. Energy Policy, 38, 1372–1378.
Sasol explore - Sasol Canada. (2012, June 5th). Retrieved from Sasol:
http://www.sasol.com/sasol_internet/frontend
Baker, & Huges. (2012). Natural Gas. Retrieved June 29, 2012, from Baker Hudges:
http://public.bakerhughes.com/shalegas/
Barndorff-Nielsen, O., & Shephard, N. (2004). Econometric analysis of realized covariation:
high frequency based covariation, regression, and correlation in financial economics.
Econometrica, 72, 885–925.
Boyer, C., Clark, B., Jochen, V., Lewis, R., & Miller, C. (2011). Shale Gas: A global
Resource. Schlumberger.
Bryman, A., & Bell, E. (2007). Business Research Methods. New York: Oxford University
Press.
Cafferky, M., & Wentworth, J. (2010). Break Even Analysis : a definitive quide to cost-
volume-profit analysis (1ste ed.). New York: Business Expert press.
Chandra , V. (2012, September 02). Gas to liquids - GTL. Retrieved from The independant
natural gas information site: http://www.natgas.info/html/gastoliquids.html
Chedid, R., Kobrosly, M., & Ghajar, R. (2007). The potential of gas-to-liquid technology in
the energy market: The case of Qatar. Energy Policy, 35, 4799–4811.
Cohen, D. (n.d.). A shale gas boom?
Demirbas, A. (2009). Political, economic and environmental impacts of biofuels: A review.
Applied Energy, 86, S108–S117.
Copyright UCT
78
Department of Energy. (2012, October 2). Energy. Retrieved from Department: Energy -
Republic of South Africa: http://www.energy.gov.za/files/petroleum_frame.html
Djakovic, D. (2011). Gas to Liquids - An Ideal Gas monetisation option.
Gallagher , T. (2009). Financial Management; Principles and Practice (5th ed.). Colorado
State University: Tectbook/Media press.
geology.com. (2012). Natural Gas production Map. Retrieved June 29, 2012, from
geology.com: http://geology.com/oil-and-gas/natural-gas-production-map/
Greenacre, M. J. (2010). Correspondence analysis.
Hall, K. (2005). A new gas to liquids (GTL) or gas to ethylene (GTE) technology. Catalysis
Today, 106, 243–246.
Hub, H. (2012). ForecastChart.com. Retrieved from Natural Gas forecast:
http://www.forecast-chart.com/forecast-natural-gas.html
Jarramillo, P., Griffen, W., & Matthews, H. (2008). Comparative Analysis of the Production
Costs and Life-Cycle GHG Emissions of FT Liquid Fuels from Coal and Natural Gas.
Pittsburgh: American Chemical Society.
Jinang, M., Griffin, M., Hendrickson, C., Jaramillo, P., VanBriesen, J., & Venkatesh, A.
(2011). Life cycle greenhouse gas emissions of Marcellus shale gas.
ENVIRONMENTAL RESEARCH LETTERS, 6, 9.
Kaiser, M. (2012). Haynesville shale play economic analysis. Journal of Petroleum Science
and Engineering, 82-83 , 75–89.
Kaplan, R., & Atkinson, A. (1998). Advanced mamagement accounting (3de ed.). New Jersy:
Prentice-Hall.
Knottenbelt, C. (2002). Mossgas “gas-to-liquid” diesel fuels—an environmentally friendly
option. Catalysis Today, 71, 437–445.
Koenker, R., & Hallock, K. F. (2001). Quantile Regression. The Journal of Economic
Perspectives, 15(4), 143-156.
Copyright UCT
79
Kretzschmar, G., & Kirchner, A. (2009). Oil price and reserve location—Effects on oil and
gas sector returns. Global Finance Journal, 20, 260–272.
Kruger, N. (2012, August 29). Pricing structure of the GTL plant in Sasol. (L. Claassen,
Interviewer)
Levine, R., & Renelt, D. (1992). A Sensitivity Analysis of Cross-Country Growth
Regressions. American Economic Association, 82(4), 942-963.
Liang, F.-Y., Ryvak, M., Sayeed, S., & Zhao, N. (2012). The role of natural gas as a primary
fuel in the near future, including comparisons of acquisition, transmission and waste
handling costs of as with competitive alternatives. Chemistry Central Journal, 6.
Masih, M., Albinali, K., & DeMello, L. (2010). Price dynamics of natural gas and the
regional methanol markets. Energy Policy, 38, 1372–1378.
Mauger, S., & Bozbiciu, D. (2011). How changing gas supply costs leads to surging
production. Calgary.
Morita, Y. (2001). Marketability of GTL from Natural Gas.
Reddy Keshav, T., & Basu, S. (2007). Gas-to-liquid technologies: India's perspective. Fuel
Processing Technology, 88, 493–500.
Rogers, H. (2011). Shale gas—the unfolding story. Oxford Review of Economic Policy, 27,
117–143.
Ryan, J. (2012). Environment vs. jobs: Lancashire’s shale gas drilling investigated. Retrieved
from Blog preston: http://blogpreston.co.uk/2011/02/environment-vs-jobs-
lancashire%E2%80%99s-shale-gas-drilling-investigated/
SAPIA. (2012, 10 1). South African Petroleum Industry Association. Retrieved from South
African Petroleum Industry Association: http://www.sapia.co.za
Sasol. (2011). value through excellence. unlock the full value of natural gas. gas-to-liquids.
Copyright UCT
80
Sasol, B. (2011). Explore Sasol. Retrieved June 24, 2012, from Sasol.com:
http://www.sasol.com/sasol_internet/frontend/navigation.jsp?navid=1600033&rootid
=2
Stevens, P. (2010). The ‘Shale Gas Revolution’: Hype and Reality. A Chatham House Report
. Retrieved from www.chathamhouse.org.uk
Sweetcrude. (2011, August 16). Sweet Crude Reports. Retrieved July 01, 2012, from Nigeria
introduces gas transportation network code:
http://sweetcrudereports.com/2011/08/16/nigeria-introduces-gas-transportation-
network-code/
Terre Blanche, M., Durrheim, K., & Painter, D. (2010). Research in Practice. Cape Town.
Tredoux, C., & Durrheim, K. (2009). Number, Hypothesis & Conclusions. Cape Town.
U.S. Energy Information Administration, .. (2012). Monthly Energy Review March 2012.
Retrieved June 17, 2012
Udaeta, M., Burani, G., Maure, J., & Oliva, C. (2007). Economics of secondary energy from
GTL regarding natural gas reserves of Bolivia. Energy Policy, 35, 4095–4106.
Viljoen, J. (2012, March 12). Bloomberg News. Retrieved June 26, 2012, from Bloomberg:
http://www.bloomberg.com/news/2012-03-12/sasol-of-south-africa-first-half-
operating-profit-grew-70-to-2-7-billion.html
Weijermars, R., Drijkoningen, G., Heimovaara, T., Rudolph, E., Weltje, G., & Wolf, K.
(2011). Business Analysis. Journal of Natural Gas Science and Engineering, 402-
412. Retrieved 2011, from http://bizanalyst.com/articles/benefits-of-inflation-for-
business.htm
Wikiposit. (2012, September 05). U.S. Natural Gas Prices. Retrieved from Wikiposit:
http://wikiposit.org/w?filter=Energy/US%20Department%20of%20Energy/Natural%
20Gas/U.S.%20Natural%20Gas%20Prices/
