Engineering - NTNU

31/10/2005 Course AT-327 1

UNIS – University Courses on Svalbard

ArcticOffshoreEngineering

31/10/2005 Course AT-327 2

Exploration and Production

Part 1

Anatoly ZolotukhinStavanger University/Statoil/Russian State University of Oil and Gas

31/10/2005 Course AT-327 3

IntroductionBasic properties of hydrocarbonsAn overview on petroleum geologyDeciding on drillingUncertainty of our estimatesForecasting productionHow to estimate an undiscovered potential?


31/10/2005 Course AT-327 4


Geologic Time Scale

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Exploration and

Production

Hyd

roca

rbon

reso

urce

s

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Basic Hydrocarbon Series in Petroleum

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The Four Major Hydrocarbon

Series in Petroleum

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Chemical Composition of Crude Oil and Natural Gas

Natural Gas Crude Oil

Natural gas is composed ofmolecules from 1 to 4 carbons in length.

Crude oil is a mixture of moleculesfrom 5 to over 60 carbons in length, forming straignt chains, chains with branches and circles.

Source: IHRDC

31/10/2005 Course AT-327 9


Source: IHRDC

Element Crude Oil, % by weight

Natural Gas, % by weight

C 82-87 65-80

H 12-15 1-25

S 0.1-5.5 0-0.2

N 0.1-1.5 1-15

O 0.1-4.5 -

31/10/2005 Course AT-327 10


Source: IHRDC

Saturated ethane Unsaturated ethylene

Straight-chained Pentane Branch-chained Isopentane

Molecular structures of the paraffin molecules

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Source: IHRDC

Cyclopentane C5H10 Cyclohexane C6H12

Molecular structures of the naphthene molecules

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Source: IHRDC

Benzene C6H6 Toluene C7H8

Molecular structures of the aromatic molecules

Ethylbenzene C8H10

Alkylbenzene series of the aromatic group

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Source: IHRDC

Naphthalene C10H8 Anthracene C14H10

Molecular structures of the aromatic molecules

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Source: IHRDC

Molecular structure of a typical asphaltine

NSO impurities

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Classification of Oils(after Tissot and Welte, 1978)

Source: IHRDC

Prirazlomnoye,Medyn-More,Varandey-More

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General Scheme of Crude Oil Alteration Processes

(after Bailey et al., 1974)

Source: IHRDC

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Gas chromatographs showing disappearance of n-paraffin peaks during incubation of Saskatchewan crude oil with a mixed microbe population at 300C (after Jobson et al., 1972)

Source: IHRDC

Biodegradation of Crude Oil

Retention time ----

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The process of cracking: a less valuable, longer-chain hydrocarbon called cracking stock, is used to produce

gasoline

Source: IHRDC

Maturation of Crude Oil

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Source: IHRDC

Composition of Natural Gas and Crude Oil

Avearge molecular compositionof crude oil

Natural gas composition

Molecular Type % by Weight

Paraffin 30

Naphthene 49

Aromatic 15

Asphaltic 6

Molecule % by Weight

Methane (CH4) 88

Ethane (C2H6) 5

Propane (C3H8) 2

Butane (C4H10) 1

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Source: IHRDC

Properties of Some Crude Streams

APIcmg

+=

5.1315.141)/( 3ρ 5.131

)/(5.141

3 −=cmg

APIρ

API – American Petroleum Institute

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Relationship between the density and API gravity

APIcmg

+=

5.1315.141)/( 3ρ 5.131

)/(5.141

3 −=cmg

APIρ

0

20

40

60

80

100

0,6 0,7 0,8 0,9 1 1,1Density, t/m3

API g

ravi

ty

31/10/2005 Course AT-327 22

Source: IHRDC

Crude Oil Distillation

A fractionating tower:different fuels and lubricants and distilledout of crude oil at different temperatures

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Drilling Operations in a Field Development

Data exchangeExploration and Production (E&P)Navigation and global positioningsystemsData collection

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Assumed subsurface key datafor selecting production strategy

ReservoircharacteristicsFluid properties

Resources estimate

Drainage strategy

Improved recovery methods

Development drilling

Horizontal drilling

Production rate

Reserves estimate

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Drilling OperationsDrilling Operations

Seismic SurveyingProcurement of acreage

Exploration Drilling

Apprailsal Drilling

Development Drilling

Well Planning

Start of Field Production

Interpretation of drilling resultsWell Planning

Interpretation of drilling resultsField PlanningWell Planning

Production Drilling & Workover

End of Field Production

Searching for Hydrocarbons

Abandonment


Reservoir Management


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Data exchange

Geology

Well planning proposition

Advise & information

Drilling resultsDrilling Engineering

Planning Drilling

Advise & information

Drilling Engineering

Geology

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Data Collection

OutcropsBore holesGraviM agW ell info: Logs Cores etcSeism ic: 2D/3D

Positioning system

Process & Interpret

Prospect definition

W ell location

D rilling results

W ell inform ation Seism ic inform ationSedim entology StructureFacies, Palaeo FaultingSource Unconform ities & m aturity Tectonic historyFluids Depths & Volum es

Exploration and Production (E&P)

Data exchange and analysis

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Data collection

Geophysical DataSeismic Survey Design and Acquisition

Seismic Data Processing

Subsurface Data

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stream er

E nergysource

O il

A coustic w aves propagate through the earth’s

surface layers and are reflected by rock boundaries

sea

rock layer 1

rock layer 3

rock layer 2

rock layer 3

Data collection

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Seismic Data Processing

Demultiplex field data

Wavelet processing and filtering

Velocity analysis

Stacking

Filtering and deconvolution

Migration and display

Seismic data processing

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Subsurface data collection

Various downhole tools are used to analyse fluid/rock properties

Logs: Porosity, permeability, density, velocity, resistivity, neutron and gamma activity, bed dip, mineral content, grain size and sorting

Cuttings: HC shows, fossils, minerals

RFT’s: Fluid content, pressure, permeabilityboundaries, TOC

Cores: Palaeontology, facies, lithology, mineralogy, fluids and all physical properties

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An Overview onPetroleum Geology

Oil and gas windowPhase diagram and chances of finding petroleumGeneration, migration and accumulation of petroleumGeological and Geophysical (G&G) interpretationPlay and Prospect definition

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An Overview onPetroleum Geology

Rock TypesLayeringStructural DeformationsSedimentary StructuresSource Rock and Generation of PetroleumPetroleum Migration and Accumulation

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RockTypes

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Habitat of Associated and Non-associated gas

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Types of Traps

Porous Rock

GAS

OIL

WATERIl

mpeerm ab e Rock

Il

mpeerm ab e Rock

Porous Rock

Il

mpeerm ab e Rock

Il

mpeerm ab e Rock

GAS

OIL

WATER

Dome

Anticline

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Types of Traps

Gas

Gas Gas

Oil

Oil

Oil

Water

WaterWater

Water

Water

Salt Diapir

Impermeable

Impermeable

Impermeable

Oil Oil

GasOil

Water

Fault

Impermeable

Impermeable

Salt tectonics Faults tectonics

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Types of Traps

GasOil

Water

ImpermeableBedsOil

Oil

Gas

Water

Sandstone body

Mudrocka)

Mudrock

Oil

Gas

Water

A "multistorey" sandbodyformed by paleochannel

sandstone bodiesb)

Stratigraphic traps

31/10/2005 Course AT-327 39

Types of Traps

Typical features associated with salt tectonics

Salt

Normal faulting and traps

Erosional unconformity

1

3

2

Thrust faults and traps

Unconformity

1

2

3

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Generation, migration andaccumulation of petroleum

Basinalkitchenarea Migration path

Sourcerock

Generation, Migration and Accumulation of Petroleum

To find petroleum the following “components”should be in-place:

Source rockMigration pathReservoirTrapSeal

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GENERATION OF PETROLEUMVS. TEMPERATURE

Generation of Petroleum versus Temperature

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Pre

ssur

e

Temperature

0 204060

80100

Phase Diagram and Chances to Find Petroleum…

Cp

CT

C

Oil

Gas

Gas + Oil

Gas-Condensate

Depth in

crease

s

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Geological and Geophysical Interpretation

LogsCutting materialRepeated Formation Tests (RFT)Core Analysis

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Play and Prospect Definition

A Play is a hypothetical geological framework that contains all the elements necessary to find petroleum

A Prospect is a particular example of:

A pre-conceived play type, orAn entirely new play that is invented to describe the particular observed data

Play

Prospect

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Play and Prospect Definition

Minimal components of a structural prospect will be a Depth map at or near the top of reservoir formation interval showing:

Faults through the reservoirStructural roll-oversCritical closure pointsSpill point

Depth map

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Uncertainty of Our Estimates

Uncertainty versus timeMethods of estimating uncertainty

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Evaluating uncertainty…

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P has

e

1-st well drilled

Met

hod

ofev

alua

tion

Uncertainty intervalin the oil recoveryestimate

Actual recovery

Analogy method

Pre-drillingphase Production phase

Volumetric estimates

Production performance analysis

Simulation

Material balance calculations

Decline curve analysis

Time

Uncertainty of Estimates at Different Phasesof Field DevelopmentUncertainty of Estimates at Different

Phases of Field Development

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P90

P50

P10

400 80 120In place volume of hydrocarbons (in million barrels)

Cum

ulat

ive

prob

abili

ty o

f occ

urre

nce

160 200

Example: 50% chance that there is 72 million barrels

of hydrocarbons in placeat least

PROBABILISTIC ASSESSMENTOF

IN-PLACE VOLUMES OF HYDROCARBONS

Probabilistic Assessment of In-Place Volumes of Hydrocarbons

31/10/2005 Course AT-327 50

0.0

1.0C

umul

ativ

e pr

obab

ility

Resources

Pre-drilling

Min Max0.0

1.0 Discovery

Min Max0.0

1.0 Appraisal

Min Max

0.0

1.0

Cum

ulat

ive

prob

abili

ty

Delineation/early production

Min Max0.0

1.0

Mature production

Min Max0.0

1.0

Late time depletion

Min Max

Change in Uncertainties of Resources Estimate vs. Time

Ref: Archer and Wall, 1991

31/10/2005 Course AT-327 51

Time

Р50

Р10

Р90

Exploration Production

Change in Uncertainties of Resources Estimate vs. Time

Ref: FUN seminar, April 2000

Р50

Р10

Р90

Exploration Production

Rel

ativ

e re

serv

es

31/10/2005 Course AT-327 52

0

1

2

3

4

-10 -5 0 5 10 15 20

Year after start of production

GullfaksVeslefrikkOsebergTroll OljeStatfjord(Norw. part)Tommel. GHeimdalMurcihsonSnorreAlbuskjellCodEddaEkofiskEldfiskTorVest EkofiskUlaGyda30/6 Gamma Nord1,300,75

Reserve Estimates of Norwegian Fields Relative to Estimate at the Start of Production

Uncertainty in Reserves Estimate

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Example of bias (1)

Volumetric analysis ofa single reservoir

1. no spatial correlations, only volume-averaged statistical distributions (= common practice)

2. with spatial correlations (TOS, res. properties)

3. with spatial correlations (TOS only)

1

2

3


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Volumetric analysisof multiple reservoirs

3 stacked reservoirsdependent prob. summation: proven (P90) uneconomicindependent prob. summation: proven (P90) economic

stacked reservoirs

0

0.2

0.4

0.6

0.8

1

0 5 10 15 20 25 30

reserves (million m3)1

- cdf

P90 uneconomic

P90 economic

Rules are still poorly known!

Ref: FUN seminar, 2000

Example of bias (2)


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Deterministic, Probabilistic and Fuzzy Estimateof Resources and Reserves

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Volumetric estimate of reserves

Reserves = Rock Vol N/G PorOil Sat Oil Shrinkage Rec Factor

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Input data

Rock volume 0.7x109 m3 (0.2-1.5)x109

Porosity 0.14 (0.12-0.17)N / G 0.50 (0.4-0.7)Oil saturation 0.75 (0.65-0.80)Shrinkage coeff 0.81 (0.78-0.85)Oil recovery factor 0.4 (0.35-0.45)

31/10/2005 Course AT-327 58

Deterministic estimate

Rock volume 0.7x109 m3 (0.2-1.5)x109

Porosity 0.14 (0.12-0.17)N / G 0.50 (0.4-0.7)Oil saturation 0.75 (0.65-0.80)Shrinkage coeff 0.81 (0.78-0.85)Oil recovery factor 0.4 (0.35-0.45)

Reserves 11.9x106 m3

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Probabilistic estimate – stochastic simulation (method Monte Carlo)

pdf

Rock vol Porosity N / G

pdf

Oil sat Shrinkage Recovery

Reserves

X X

X X

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Probabilistic estimate – stochastic simulation (method Monte Carlo)

Reserves

pdf

CC

PC

Reserves

0.0

1.0

There are 50% chancesthat reserves will be at least 11.9 million m3

31/10/2005 Course AT-327 61

Fuzzy estimate of reserves

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Application of Interval/Fuzzy Analysis Technique to E&P tasks

Fuzzy and Interval Numbers

μA μA

α

α - spread

x x

1.0 1.0

a1a1 a2a2 a3a3

h -

Interval ofconfidence

Level ofconfidence

a) b)

, ,

λA λA

Fuzzy Number (FN) Interval Number (IN)

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μA

x

1.0

0.0a2

t=0

μA

x

1.0

0.0a1 a2 a3

t>1

μA

x

1.0

0.0a1 a2 a3

0<t<1 μA

x

1.0

0.0a1 a2 a3

t=1

μA

x

1.0

0.0a1 a2 a3

t>>1

)ty10,(max(x)Aμ −=

⎪⎪⎩

⎪⎪⎨

⎧

>−−

≤−−

=2

23

2

212

2

ax,aaax

ax,aaxa

y


Examples of Fuzzy and Interval Numbers

31/10/2005 Course AT-327 64

[ ] [ ] [ ][ ] [ ] [ ][ ] [ ][ ] [ ] [ ]13313131

1,3ji,ji

1,3ji,ji3131

13313131

33113131

/ba,/bab,ba,a

)bamax(,)bamin(b,ba,a

ba,bab,ba,aba,bab,ba,a

=÷

⎥⎦⎤

⎢⎣⎡

∏∏=×

−−=−++=+

==

NB: FN and IN do not posessgroup properties:

A - A ≠ 0A / A ≠ 1A + B - A ≠ B

Example: [-3,-1]+[1,3]=[-3+1,3-1]=[-2,2]


Operations on Fuzzy and Interval Numbers

31/10/2005 Course AT-327 65

Example: [-3,-1]+[1,3]=[-3+1,3-1]=[-2,2]


Operations on Fuzzy and Interval Numbers

1.0

-3 -2 -1 0 1 2 3

31/10/2005 Course AT-327 66

0

50

10

70

0.3

30

0.5

60

12

75

0.4

35

1.0

70

14

80

0.5

40

1.5

80

16

85

0.6

45

2.0

90

18

90

0.7

50

0

0

0

0

0

0

0.2

0.2

0.2

0.2

0.2

0.2

0.4

0.4

0.4

0.4

0.4

0.4

0.6

0.6

0.6

0.6

0.6

0.6

0.8

0.8

0.8

0.8

0.8

0.8

1

1

1

1

1

1

μ

Rock volume, 10 m9 3

Oil saturation, %

Porosity, %

Oil shrinkage, %

N/G ratio, fraction

Oil recovery, %

1

1

1

1

0.8

0.8

0.6

0.6

0.4

0.4

0.2

0.2

0

0

10

10

100

100

Reserves, 10 m6 3

Reserves, 10 m6 3

Leve

l of c

onfid

ence

, hC

umul

ativ

e po

ssib

ility

Fuzzy Estimate of Reserves

31/10/2005 Course AT-327 67

Concept of Uncertainty in Resources/Reserve Estimate

5 10 15 20 25 30 350

0.2

0.4

0.6

0.8

1C

um. D

istri

butio

n Fu

nctio

n

Oil Reserves, 10 Sm6 3


Deterministic estimateProbabilistic estimateFuzzy/interval estimate

31/10/2005 Course AT-327 68

Similarities:Volumetric calculationsAppreciate uncertainties of input data

Differences:Way of operating with uncertaintiesWay of presenting results (based on same input data)

Resources andReserve Estimate

Comparing different estimating methods:

31/10/2005 Course AT-327 69

ExampleEstimating gas and condensatereserves of the Poima license area of the Astrakhan gas-condensatefield (Russia)

From V.I. Poroskun (VNIGNI), A.B. Zolotukhin (Statoil)”Estimating reserves of the Poima area of the Astrakhan gas-condensate field by means of probabilistic and fuzzy nethods”, Russian-Nprwegian seminar ”Resources and Reserves Classificationand Means of Their Evaluation”, Moscow, 31.10 – 2.11, 2001.


31/10/2005 Course AT-327 70

I

II

III

IV

VVI

VIIVIII

IXX

XIXII

XIII

XIV

2928

30

31

6

23

2425

27

26

1-Правобережная

А-2

АСТРАХАНЬ

4

20

15

22

19

181716

13

21

2-Володарская

12

1

89

1110

3

2

14

46

47

48

48

49

47

46

49

48

47

46

47

46

48

р.Ахтаба

р.Волга

КАСПИЙ

СКОЕ

МОРЕ

С А Р П И Н С К И Й

П Р О Г И Б З А В О Л Ж С К И Й

П Р О Г И Б

А С Т Р А Х А Н С К И ЙС В О Д

К Р Я Ж К А Р П И Н С К О Г О

КАРАКУЛЬСКО-СМУШКОВСКАЯ ЗОНА ДИСЛОКАЦИЙ

Список лицензионных участков,площадей и структур.

I Баритово-Удачный участокII Никольская площадьIII Верблюжья площадьIV Георгиевская структураV Северо-Астраханский участокVI Еленовская структураVII Пойменный участокVIII Правобережный участокIX Южно-Астраханский участокX Южно-Безымянная структураXI Бешкульский участокXII Наримановский участокXIII Бахчевая структураXIV Новогеоргиевский участок

Список месторождений1* Верблюжье2 Бугринское3* Северо-Шаджинское4* Еленовское5а* Астраханское (левобережная часть)5б Астраханское (правобережная часть)6* Бешкульское7* ПромысловскоеПримечание: 1* - месторождения, по которым выданы лицензии на добычу.

Список локальных структур8. Бурундинская9. Баритовая10. Выропаевская11. Зап.Выропаевская12. Капьярская13. Северная14. Северо-Ольховская15. Альтернативная16. Харабалинская17. Ю.Харабалинская18. Михайловская19. Заволжская

20. Филинская21. Сейсмическая22. Табаковская23. Нижнекрасносельская24. Перестроечная25. Балаевская26. Николаевская27. Ивановская28. Анатольевская29. Рябовская30. Сокольническая31. Вост.-Краснохудукская

Условные обозначенияГраницы тектонических элементов.Локальные структуры и их номера посписку подготовленные и выявленные(выборочно).

В бурении.

Сверхглубокие скважины, находящиесяв бурении.

Месторождения

нефтяные

газовые

газоконденсатные

Объекты лицензированияУчастки, по которым выданы лицензиина геологическое изучение недр.

Участки, по которым выданы лицензиина геологическое изучение недр с по-следующей добычей УВ.

км 10 0 10 20 30 40 км

Рис. 1 Обзорная карта


ExampleEstimating gas and condensate reserves of the Poima licensearea of the Astrakhan gas-condensate field(Russia)

31/10/2005 Course AT-327 71

Input data

Parameter Мин Вероятно Макс

Area, km2 600 690 720

Net pay, m 75 80 85

Porosity, % 9 9 10

Initial gas saturation, % 75 80 83

Correction on temperature, fraction 0.77 0.77 0.77

Initial reservoi pressure, bar 610 610 610

Correction on compressibility (at initial pressure)

0.81 0.81 0.81

Final reservoir pressure, bar 1.6 1.6 1.6

Correction on compressibility (at final pressure)

1.0 1.0 1.0

Gas recovery factor 1.0 1.0 1.0

Condensate content in gas, g/Sm3 0.22 0.22 0.22

Condensate recovery factor 0.69 0.69 0.69

Estimating gas and condensate reserves of the PoimaArea of the Astrakhan gas-condensate field

31/10/2005 Course AT-327 72

( ) ( ) Tffiigg ppSGNhFV γαα ⋅−⋅⋅⋅⋅= /

cggc CVV η⋅⋅=

Equations used for estimating:

Gas reserves

Condensate reserves

Estimating gas and condensate reserves of the PoimaArea of the Astrakhan gas-condensate field

31/10/2005 Course AT-327 73

Estimating gas and condensate reservesof the Poima Area ofthe Astrakhan gas-condensate field

Gas reserves

0.0

0.2

0.4

0.6

0.8

1.0

1000000 1200000 1400000 1600000 1800000 2000000

Reserves, mill Sm3

Cum

ulat

ive

dist

ribut

ion

P90

P50

P10

Condensate reserves

0.0

0.2

0.4

0.6

0.8

1.0

150 200 250 300

Reserves, mill tones

Cum

ulat

ive

dist

ribut

ion

P90

P50

P10

Fuzzy estimateProbabilistic estimate

31/10/2005 Course AT-327 74

Estimating gas and condensate reserves of thePoima Area of the Astrakhan gas-condensate field

STGOIP Reserves% %3.0 3.05.4 5.4

10.9 10.9

STCOIP Reserves% %4.5 4.53.7 3.68.7 8.8

Differences in estimates

Gas Condensate

P90P50P10

31/10/2005 Course AT-327 75

Deciding on Drilling

To drill or not to drill…Deciding on drilling locationG&G in the well designWell site geologyDrill stem testing

31/10/2005 Course AT-327 76


To drill or not to drill…

Decision on drilling depends on how much the uncertainty in reserve estimate can be reduced

)1( CECV −⋅≥⋅

V – value of informationC – chance of successE – risk expenditure

Risk = 1 – C

31/10/2005 Course AT-327 77


Definition of Risk:

The term “Risk” can be defined as a possibility of obtaining an unwanted result due to the existing uncertainty in the problem under analysis expressed numerically as a certain number from the interval [0, 1] and identified as a chance of getting an unwanted result

Risk = 1 – C

31/10/2005 Course AT-327 78

Deciding on a Drilling Location

Probability of HC being present in the prospect, i.e.

Presence of mature source rock, migration path, reservoir trap and seal

Prospect size, controlled by:Area, vertical roll-over, integrity of closure, depth-to-crest and HC column

Reservoir and its N/G, porosity and permeability, reservoir pressure and temperatureHC fluids

Oil, gas, condensate and their respective saturations

Objective: to maximize in-place HC volumes controlled by:

31/10/2005 Course AT-327 79

Total depthLithologyPressurePrediction of oil and/or gas

Geology and Geophysics in the Well Design

The well prognosis will attempt to provide the following details:

31/10/2005 Course AT-327 80

Analysis of the cuttingsGas determination from the drilling mudHC evaluationWireline logsCore samplingDrill stem testing

Well Site Geology

During the drilling operation the geologist job is to ensure proper testing of HC shows and to observe if the formation drilled is according to the drilling prognoses

31/10/2005 Course AT-327 81

< 15 Brown15 – 25 Orange25 – 35 Yellow to cream35 – 45 White> 45 Blue-white to violet

Well Site Geology

Hydrocarbon Evaluation

Each sample is examined under ultraviolet light for evidence of fluorescence. Ultraviolet light (wave length 3600 Å=3.6 10-7m) causes fluorescence of almost all crude oils over the entire range of gravities. The colour of fluorescence is generally characteristic of the gravity of the crude oil:

Gravity (API) Colour of fluorescence

31/10/2005 Course AT-327 82

Forecasting Production

Approaches and methods used in forecastingSome examples

31/10/2005 Course AT-327 83

Forecasting Production

Darcy’s equation for production forecast of a single well…

( )SrrBkh

pqPI

weoo ++=

Δ=

75.0)/ln(2

μπ

k – reservoir permeabilityh – net pay thicknessBo – oil formation volume factorλo – viscosity of oilre – drainage area radiusrw – well bore radiusS – skin factor

31/10/2005 Course AT-327 84

Well production rate evaluation (steady state solutions)

Fully penetrated vertical well: Dupuit (1863)Horizontal well: Merkulov (1958), Borisov (1964), Ciger (1983), Joshi (1986), Renard and Dupuy (1990)…Fully penetrated slant well: Cinco et al. (1975), Van der Vlis et al. (1979)…Partly penetrated vertical well: Muskat (1937), Brons and Marting (1961)…Partly penetrated slant well: not well described in literature

31/10/2005 Course AT-327 85

Problem Set Up

No cross-flowReservoir top

Reservoir bottom

Horizontalwell

Drainage areacontour

pw = const

pe = const

Plan view

Top

Bottom

Vertical section

31/10/2005 Course AT-327 86

Mathematical Problem Set Up

02 =∇ p

0)2

,,(

0)2

,,(

=+∂∂

=−∂∂

hyxzp

hyxzp

wpzyxp =),,(

epzyxp =),,(

Steady state conditions of flow

No cross-flow boundary conditionsat the reservoir top/bottom

22);( 222 LxLrzy w ≤≤−=+at

22);( 222 hzhryx e ≤≤−=+at

31/10/2005 Course AT-327 87

Arbitrary Well as a Chain of Spheres(after Michelevichius and Zolotukhin, 2003)

Spherical well Horizontal well

Well with complex geometry

Length of the well: L=(2n+1)2rw

31/10/2005 Course AT-327 88

Spherical well in an infinite reservoir

Solution for a single spherical well in an infinite reservoir:

Czzyyxxk

BqMp +−+−+−

⋅−=2

02

02

0 )()()(1

4)(

πμ

⎟⎟⎠

⎞⎜⎜⎝

⎛−⋅

−=

ew

werrB

ppkq 11)(4

μπ

psxz

Pressure distribution:

31/10/2005 Course AT-327 89

Spherical well in a finite reservoirSolution for a spherical well in a middle of finite reservoir(obtained applying method of images):

( )∑∞

−∞= −−+−+−⋅−=

j

i

zjhzyyxx

qk

Bzyxp2

02

02

0 )()(4),,(

πμ

αμπ

Bppkq we )(4 −

=( ) ( )

∑∞

−∞= ⎥⎥⎦

⎤

⎢⎢⎣

⎡

+−

+=

j ew jhrjhr 2222

11α

Final approximation:

⎥⎦

⎤⎢⎣

⎡+−

Δ=

hr

rh

rhB

pkhqe

ew

ln22

2

μ

π

psxy psyz psxz


31/10/2005 Course AT-327 90

Arbitrary well in a finite reservoir

Solution for any well in a finite reservoir(as an interference of spherical wells):

( )( )C

zjhzyyxx

qk

Bzyxpj

n

nii

jii

i +∑ ∑−−−+−+−

⋅−=∞

−∞= −= 222 1)()(4

),,(πμ

∑ ==

n

ik qq

2

0∑

Δ=⋅

=

n

ikik B

pkq2

0

4μπα

( )( ) ( )( )∑∞

−∞= ⎥⎥

⎦

⎤

⎢⎢

⎣

⎡

−+++−

−−+++−=

ji

jeiki

jwki

ik

zjhrxzzjhrxx222222 1

1

1)(

1α

31/10/2005 Course AT-327 91

Horizontal Well

MZ-solution (2003):

⎥⎥

⎦

⎤

⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛ −+

Δ=

w

ee

hC

rh

Lh

LLrr

B

phkq

πμ

π

2ln

2/)2/(

ln

222

Ciger (1983):

⎥⎥⎦

⎤

⎢⎢⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎠⎞

⎜⎝⎛ +

Δ=

w

hJ

rh

Lh

LbaB

phkq

2ln

2/ln

2

μ

πJoshi (1986):

x_z y_z x_y


0 500 1000 1500 20000

500

1000

1500

20001.525 10 3×

264.358

q_MZ L( )

q_C L( )

q_J L( )

2 10 3×50 L

Comparison of solutions:

0 2 4 6 8 100

0.001

0.002

0.003

0.0043.389 10 3−×

1.246 10 4−×

q_MZ L( )

q_C L( )

q_J L( )

100.5 L

⎪⎪⎪⎪⎪

⎩

⎪⎪⎪⎪⎪

⎨

⎧

≥

⎥⎥

⎦

⎤

⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛+⎟

⎠

⎞⎜⎝

⎛

Δ

<

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛++⎟

⎠

⎞⎜⎝

⎛

Δ

=hL

erh

Lh

rL

Lr

Lr

B

pkh

hL

rL

rL

Lh

hr

B

pkh

q

we

ee

ww

e

2ln

2arctan

21

2ln

2

122

lnln

2

2

2

μ

π

μ

π

31/10/2005 Course AT-327 92

A Fully Penetrated Vertical Well

w

eMZ

rrB

pkhqln

2

μ

π Δ=MZ-solution:

Dupuit (1863):

w

eD

rrB

pkhqln

2

μ

π Δ=

psxy psyz psxz


31/10/2005 Course AT-327 93

A Fully Penetrated Slant Well

MZ-solution:

VVw

eVV

Srr

B

pkhq+

Δ=

ln

2

μ

π α

α

cos0360sin454.0

cos4 ⎥⎥⎦

⎤

⎢⎢⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛=

hrhS w

VV

Van der Vlis et al. (1979):

CCw

eCC

Srr

B

pkhq+

Δ=

ln

2

μ

π

wCC r

hS100

log5641

865.106.2

⎟⎠⎞

⎜⎝⎛−⎟

⎠⎞

⎜⎝⎛−=

αα

Cinco et al. (1975):

x_z y_z x_y


0 20 40 60 80 1000

0.02

0.04

0.060.057

4.772 10 4−×

q_MZ2 h( )

q_CC h( )

q_VV h( )

1002 h

Comparison of solutions:⎪⎪⎪⎪⎪

⎩

⎪⎪⎪⎪⎪

⎨

⎧

≥

⎥⎥

⎦

⎤

⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛+⎟

⎠

⎞⎜⎝

⎛

Δ

<

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛++⎟

⎠

⎞⎜⎝

⎛

Δ

=hL

erh

Lh

rL

Lr

Lr

B

pkh

hL

rL

rL

Lh

hr

B

pkh

q

we

ee

ww

e

ααα

ααμ

π

α

μ

π

sin

2sinln

2sinarctan

sin2

1sin2

ln

2

sin

122

lnln

2

2

2

31/10/2005 Course AT-327 94

A Partially Penetrated Vertical Well

MZ-solution:

ξμπ

BpkhqMus

Δ=

2⎟⎟⎠

⎞⎜⎜⎝

⎛−

⎥⎥⎦

⎤

⎢⎢⎣

⎡−⎟⎟

⎠

⎞⎜⎜⎝

⎛=

ew rhb

rh

b4ln)(4ln2

21 ϕξ

)125.01()875.01()125.0()875.0(ln)(

bbbbb

−Γ⋅−ΓΓ⋅Γ

=ϕ

Muskat (1937):

[ ]⎭⎬⎫

⎩⎨⎧

−⎟⎠⎞

⎜⎝⎛ −+

Δ=

)(ln11ln

2

bGhbr

rB

pkhq

Dw

eBM

μ

π

wvD r

hkkh ⋅⎟⎟⎠

⎞⎜⎜⎝

⎛=

5.0

32 675.445.11363.7948.2)( bbbbG −+−=

Brons and Marting (1961):

x_z y_z x_y


1 2 3 4 5 6 7 8 9 105 .10 4

0.001

0.0015

1.693 10 3−×

5.239 10 4−×

q_MZ L( )

q_MUS L( )

q_BM L( )

101 L

Comparison of solutions:

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡−+

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛++⎟

⎠

⎞⎜⎝

⎛

Δ=

21

21

22lnln

22

Lh

rL

rL

Lh

hr

B

pkhq

ww

eμ

π

31/10/2005 Course AT-327 95

A Partially Penetrated Slant Well

MZ-solution:

Not well described in literature

x_z y_z x_y


⎪⎪⎪⎪⎪

⎩

⎪⎪⎪⎪⎪

⎨

⎧

≥

⎥⎥

⎦

⎤

⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛+⎟

⎠

⎞⎜⎝

⎛

Δ

<

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛++⎟

⎠

⎞⎜⎝

⎛

Δ

=hL

erh

Lh

rL

Lr

Lr

B

pkh

hL

rL

rL

Lh

hr

B

pkh

q

we

ee

ww

e

ααα

ααμ

π

α

μ

π

sin

2sinln

2sinarctan

sin2

1sin2

ln

2

sin

122

lnln

2

2

2

31/10/2005 Course AT-327 96

An Arbitrary Straight Well

⎪⎪⎪⎪⎪

⎩

⎪⎪⎪⎪⎪

⎨

⎧

≥

⎥⎥

⎦

⎤

⎢⎢

⎣

⎡

⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛+⎟

⎠

⎞⎜⎝

⎛

Δ

<

⎥⎥⎥

⎦

⎤

⎢⎢⎢

⎣

⎡

⎟⎟⎟

⎠

⎞

⎜⎜⎜

⎝

⎛+⎟⎟

⎠

⎞⎜⎜⎝

⎛++⎟

⎠

⎞⎜⎝

⎛

Δ

=hL

erh

Lh

rL

Lr

Lr

B

pkh

hL

rL

rL

Lh

hr

B

pkh

q

we

ee

ww

e

ααα

ααμ

π

α

μ

π

sin

2sinln

2sinarctan

sin2

1sin2

ln

2

sin

122

lnln

2

2

2

31/10/2005 Course AT-327 97

Vertical fracture(Fractured vertical well)

( )( ) ⎥

⎥

⎦

⎤

⎢⎢

⎣

⎡⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛

+

+

Δ=

e

e

w

e

rL

Lr

LrLr

B

pkhq

2arctan

22/2/

ln

2

22

22

μ

π

31/10/2005 Course AT-327 98

Well Interference

D

- vertical well

- horizontal well

Wells in linea) b) Wells in grid

D

D

rere

31/10/2005 Course AT-327 99

Well interferenceD

re

( ) ( )( ) ⎥

⎥

⎦

⎤

⎢⎢

⎣

⎡−⎟

⎠

⎞⎜⎝

⎛−⎟⎟⎠

⎞⎜⎜⎝

⎛+⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛

+

++

+Δ=

85.1lnarctan2

ln12

)12(2

22

22

Dr

rnD

Dr

nDrnDr

nB

npkhqw

e

e

w

eμ

π

Vertical wells in line (with a distance D between them)

erDn 8.1)12( ≤+

31/10/2005 Course AT-327 100

psyzpsxy psxz

Pressure distribution(for 2 horizontal wells in line)

31/10/2005 Course AT-327 101

Well interference

D

D

re

( ) ⎥⎦

⎤⎢⎣

⎡⎟⎠

⎞⎜⎝

⎛−⎟⎟⎠

⎞⎜⎜⎝

⎛+

+

+Δ=

Dr

Dnr

nB

npkhqwe 9.2

ln)12(

9.2ln12

)12(2

2

2

μ

π

Vertical wells in grid (with a distance D between them)

erDn 8.12)12( ≤+

31/10/2005 Course AT-327 102

Pressure distribution(for 3×3 horizontal wells in grid)

psyzpsxy psxz

31/10/2005 Course AT-327 103

Wells in Grid

Comparison of total inflow into N vertical and N horizontal wells:

0 5 10 15 200

100

200

300

400400

0

Q_v N( )

Q_h N( )

201 N

Input data: h = 4 m; re= 1000 m

Q(20 vertical wells) = Q(6 horizontal 200 m length wells)

31/10/2005 Course AT-327 104

Production Performance Optimization

Effect of the well interference on the total production:

Total production rate vs number of wells

0

2000

4000

6000

8000

10000

0 10 20 30 40 50 60

Number of wells

Tota

l pro

duct

ion

rate

, Sm

3/d

Without interference

With interference

Input data: h = 10 m;re= 5000 m

Q(15 wells without interference) = Q(26 wells with interference)

31/10/2005 Course AT-327 105

Transient Pressure Analysis

Horizontal well

31/10/2005 Course AT-327 106


Slanted well

31/10/2005 Course AT-327 107


Nine production horizontal wells in grid

31/10/2005 Course AT-327 108

Production rate

0.0

0.2

0.4

0.6

0.8

1.0

100 1000 10000 100000

Rate, bopd

Cum

ulat

ive

dist

ribut

ion

Sorokin Trend, Triassic sandstonesDepth - porosity trend

00.050.1

0.150.2

0.250.3

0.35

0 500 1000 1500 2000 2500 3000

Depth, m

Poro

sity

Porosity-permeability correlation Production rate forecast

Sorokin Trend, Triassic sandstonesDepth - permeability trend

01020304050607080

0 500 1000 1500 2000 2500 3000

Depth, m

Perm

eabi

lity,

mD

Porosity-permeability trend

1

10

100

0.05 0.1 0.15 0.2 0.25 0.3 0.35

Porosity

Perm

eabi

lity,

mD

Uncertainty in Forecasting a Well Productivity

31/10/2005 Course AT-327 109

Forecasting Production Rate of a Single Well…

Porosity %

Perm., md

Net pay, m

Oil visc., cp

Oil FVF

GOR, m3/m3 Skin Prod rate,

bopd

Min 11 1.2 30 2 1.1 20 -7 80

Mean 12 12 50 2.5 1.2 20 -6 2670

Max 13 25 70 3 1.3 20 -5 21000

Production Rate as a Fuzzy NumberAll input parameters are triangular FNs

0

0.2

0.4

0.6

0.8

1

10 100 1000 10000 100000

Production rate, bopd

Mem

bers

hip

grad

e

Prod Rate Cum. Distribution Curve(Triassic sandstones)

0.0

0.2

0.4

0.6

0.8

1.0

100 1000 10000 100000


Cum

. dis

tribu

tion

31/10/2005 Course AT-327 110

Production rate as a function of the (assumed) distributions of fluid and reservoir parameters

Well Productivity Forecast

100 1000 10000 100000

0.2

0.4

0.6

0.8

1.0

Po s

sibi

l ity

/ pr

obab

ilit y


0.0

31/10/2005 Course AT-327 111

Uncertainty inProduction Forecast

Pro

duct

ion

rate

, Kbo

pd

350

300

0 10Years

20 30 40

250

200

150

100

50

0 Cum

ulat

ive

prod

uctio

n, m

ill bb

l

0

500

1000

1500

2000

2500

3000

Low MediumScenarios

High

712 mill bbls

Uncertainty in cumulative production

31/10/2005 Course AT-327 112

Reservoir Simulation -Estimating Production Potential

Double-porosity medium

Capillary imbibition process

Ref: Panfilov et al., 2000

31/10/2005 Course AT-327 113

Reservoir Simulation -Estimating Production Potential

Updip versus downdip injectionSelecting drainage strategy

Gas

a) Downdip gas injection b) Updip gas injection

GasOil + gas

Position of gas-oildisplacing front atdifferent time steps

Unswept area

Unswept area

Oil + gas

31/10/2005 Course AT-327 114

Reservoir Simulation - Estimating Production Potential

Double-porosity mediumCapillary imbibition is not considered Capillary imbibition included

Ref: Firoozabadi et al., 2001

31/10/2005 Course AT-327 115

Stochastic reservoir simulation

31/10/2005 Course AT-327 116

Reservoir geometry and a symmetry element of the well pattern system

Well placement and production performance evaluation

31/10/2005 Course AT-327 117

Well placement andproduction performance evaluation

Results of Stochastic Reservoir

Simulation

31/10/2005 Course AT-327 118

Selecting downhole completion and production equipment

Production Rate Forecast

Inflow Performance Relationship (IPR)

+

Vertical Lift Performance (VLP)

31/10/2005 Course AT-327 119

Selecting downhole completion and production equipment

Production Rate Forecast

250

200

150

100

50

0100 200

Liquid rate, Sm3/d

Pre

ssu

re, b

ar

300 400

31/10/2005 Course AT-327 120

Evaluating the Drilling Rate, Cost and Time

YearWells drilled

and completed per year

Drilling cost per year, mill. USD

1 5 42.5

2 7 57.4

3 7 51.6

4 7 54.1

5 7 53.7

6 7 53.2

7 7 52.9

8 6 45.3

9 3 22.7

Total wells

56

Total cost,mill USD

433.3

31/10/2005 Course AT-327 121

SCENARIO

Type a starting year of production 2007

YearNumber of

PW drilled per year

Number of IW drilled per

year

Number of other wells drilled per

year

Total number of wells drilled

per year

1 4 1 0 52 5 2 0 73 5 2 0 74 5 2 0 75 5 2 0 76 5 2 0 77 5 2 0 78 5 1 0 69 3 0 0 3

10 0 0 0 011 0 0 0 012 0 0 0 013 0 0 0 014 0 0 0 015 0 0 0 016 0 0 0 017 0 0 0 018 0 0 0 019 0 0 0 020 0 0 0 0

Total on well types

42 14 0 56

Number of wells coming on stream annually

Type only number of production, injection and other wells come on stream from drilling (columns C, D, E)!

Number of wells put in operation every year

Field-scale Production Forecast

31/10/2005 Course AT-327 122

FIELD REGION Scenario Base case

158.89mln m3 999.3 mln bbls130.29mln ton

79.32 mln m3 498.9 mln bbls65.04 mln ton

49.92 %

7.93 MM Sm3 49.89 MMbbls

10.00 %

1733 Sm3/d 10897bopd

42

14

0

56

WATER FLOODING

Peak production

Method of intensification

Length of HW

HORIZONTAL WELL

287 m

Field-1 Non-specified

Initial oil production rate per well

Oil recovery

Max annual production

STOOIP

Reserves

Type of EOR

Total producers

Total injectors

Other type of wells

Total wells

Non-adjusted production performance

020406080

100120140160180

0 5 10 15 20 25 30Duration, years

Oil

prod

uctio

n ra

te, K

bopd

0

100

200

300

400

500

600

Cum

pro

duct

ion,

MM

bbl

Oil prod rate, K bbls

Cum production, MM bbls

Adjusted production performance

0

20

40

60

80

100

120

140

160

0 5 10 15 20 25 30Duration, years

Oil

prod

uctio

n ra

te, K

bopd

0

100

200

300

400

500

600

Cum

pro

d, m

mbb

ls

Oil prod rate, K bblsCum production, MM bbls


31/10/2005 Course AT-327 123

Evaluation of the production rate @ Δp = 40 bar

0.0

0.2

0.4

0.6

0.8

1.0

2000 3000 4000 5000 6000 7000 8000


Cha

nce

fact

or

Evaluating production of a horizontal well (250 m)

65% chance, that production rate will be not less than 3300 bopd

Results of stochastic modeling

P90 2450 4.22P50 3785 6.53P10 5743 9.90

Most likely 2928 5.05Mean 3839 6.62

Level Well rate, bopd PI, bopd/psi


31/10/2005 Course AT-327 124

Water Cut – 90%

Contribution of each reservoir into overall production

0

20

40

60

80

100

120

2016 2019 2022 2025 2028 2031 2034 2037

Years

Oil

prod

rate

, Kbo

pd

UJ-E

UJ-W

Number of acting wells

0

10

20

30

40

50

60

70

2016 2020 2024 2028 2032 2036

Year

Num

ber o

f wel

ls

IW

IW


31/10/2005 Course AT-327 125

Water Cut – 90%

Contribution of each reservoir into overall production

0

20

40

60

80

100

120

2016 2019 2022 2025 2028 2031 2034 2037

Years

Oil

prod

rate

, Kbo

pd

UJ-E

UJ-W

Production forecast

0

20

40

60

80

100

120

2010 2015 2020 2025 2030 2035 2040

Years

Oil

prod

rate

, Kbo

pd

0

20

40

60

80

100

Gas

pro

d ra

te, M

Msc

f/d

WaterOilGas


31/10/2005 Course AT-327 126

Reservoir1

Reservoir2 Total Comments

STOOIP, MM STB 1193 892

220

22.7

202.6

66.6

12.0

501767

4.0

17.8

3314*

4.05

90

294

2M

14

Area, кm2 200

2085

220

22.8

475.3

100

7.7

501767

4.0

41.7

N/A

9.51

90

291

2M

Oil recovery, % 22.9

Reserves, MM STB 272.7

Initial well production rate, bopd 4442* HW 250 m

21

Number of the drilling platformsrequired 2M M (S)– mobile

(stationary) unit

Duration of production, years 15

Production plateau, Kbopd 100

Max rate of production (per year), % 13.3

Number of wells: ProdInjTotal

50*17*67*

* Recompleted from the lower reservoir

Area per PW, кm2 4.0

STOOIP/PW, MM STB 23.9

Reserves /PW, MM STB 5.45

Max watercut, % 90

Min bottomwhole pressure, bar 291


31/10/2005 Course AT-327 127

Risk Analysis and Decision Making

Sensitivity Analysis

Main objective –identification ofparameters, whichuncertainty has thehighest impact on theproject value

Tornado diagram illustrate the influenceof the parameters uncertainty on theproject value

-20 0 20 40 60 80 100Parameter

Base case40 MM USD

A

BC

DEF

31/10/2005 Course AT-327 128

How to Estimate an Undiscovered Potential?

31/10/2005 Course AT-327 129

Fractal analysis of resources/reserves

Estimating an Undiscovered Potential…

Discovery year

Siz

e, M

Mbb

l

31/10/2005 Course AT-327 130

Rank1

110

10

100

100

1000

1000

10000

100000

10000

Size

, MM

bbl



discovered till 2002

31/10/2005 Course AT-327 131


α−⋅= RARN )(

West Siberia

1

10

100

1000

10000

100000

1 10 100 1000 10000

RANK

MM

bbl

PRESENTTILL 1985TILL 1975TILL 1965

Timan Pechora

1

10

100

1000

10000

100000

1 10 100 1000 10000

RANK

MM

bbl

PRESENTTILL 1985TILL 1975

Volga Ural

1

10

100

1000

10000

100000

1 10 100 1000 10000

RANK

MM

bbl

PRESENTTILL 1985TILL 1965TILL 1955


Ultimate mode

31/10/2005 Course AT-327 132

α−⋅= RARN )(

Final distribution – limit of a sequence described by one ofthe population models

10000

Res

erve

s, M

mbb

l 1000

100

10

110000

Res

erve

s, M

mbb

l

Rank

10000

1000

1000

100

100

10

101

1

Ultimatemode

Pi,3

Pi,1

Pi,1

Pi,3

( )jn,jn,jin,j,jn /Npprpp −⋅+=+ 11



31/10/2005 Course AT-327 133

Final distribution: aRAN ~ln~lnln ⋅−=

∑=

⋅+=n

ii aR

nxaxJ

1

)(ln1),(min δδδδ

[ ]niNaRxaRXNaRxaRX

iii

iii

,1,lnlnlnlnlnln

∈≤⋅−−⋅−≥⋅++⋅−

δδδδ ),(~ xXX δ=

or

Linear Possibility Regression Model:

where

α−⋅= RARN )(

Estimating an Undiscovered Potential…Fractal analysis of resources/reserves

31/10/2005 Course AT-327 134

α−⋅= RARN )(

11 10

Rank

100 1000 10000

10

100

1000

10000

Fiel

d re

serv

es, 1

0 b

bl6

1 2 3 4

1 - 19652 - 19753 - 19854 - 1995

Ultimate mode


31/10/2005 Course AT-327 135

Yet-to-find (YTF) reserves of the Pechora Sea

Conclusion: YTF potential of the undiscovered fields with reserves greater than 100 mill bbls amounts to approx. 2200bbls of oil

1

01

1

10

10

Rank

100

100

10

2000

100

4000

1000

6000

10000

8000

Fiel

d re

serv

es, 1

0 b

bl6

Res

erve

s, 1

0 b

bl6

1 - 2 -

offshore present ultimate mode

1

2

1

23

1 - 2 -3 -

cum. present creaming curveYTF offshore


31/10/2005 Course AT-327 136

Reserves per structure Our estimate US Geological

Survey(USGS)

>100 mill bbls>70 mill bbls

46005800

4600

>100 mill bbls150037008200

>70 mill bbls1900495010400

Min: 2000Mean: 4000

Max: 8000

D

F

F


YTF reserves of the Pechora Sea

31/10/2005 Course AT-327 137

World Oil YTF Reserves


31/10/2005 Course AT-327 138

1 - 19602 - 19653 - 19704 - 19755 - 19806 - 19857 - 19908 - 1995

Rank

Fiel

d re

serv

es, M

mbb

l

1000000

100000

10000

10000

1000

1000

100

100

10

101

1

1 9 - 2000

23

4

56

789

Ultimate mode


ApplicationApplication ofof IntervalInterval//FuzzyFuzzy AnalysisAnalysis TechniqueTechnique to E&P to E&P taskstasks

Ref.: SPE 63199

31/10/2005 Course AT-327 139

0.1 1 10 100 1000 10000 100000

200

400

600

800

1000

1200

1400

Une

xplo

red

rese

rves

, 10

bbl

9

Field size, 10 bbl6

0

YTF min

YTF maxYTF mostlikely

Othersources

Assumption:Fields with reserves exceeding 20 bill bblshave been discovered

NB:Reserves of liquid HC of theNorth America are not includedin this estimate



Ref.: SPE 63199

31/10/2005 Course AT-327 140

Starting from 1980 annualproduction of liquid HC leaves behind incrementalgrowth of discoveredreserves

Question: when oil and condensate reserves will be depleted and their productionwill cease?



Динамика добычи и прироста запасов жидких углеводородов

0,10

1,00

10,00

100,00

1 000,00

1900 1920 1940 1960 1980 2000 2020

Год

Млрд.

баррелей/год

Годовая добычаПрирост запасов в год

Production and incremental growth of discovered reserves

Annual productionIncremental growth of disc. reserves

Year

Bill

bbl

s/ye

ar

Ref.: Leif Magne Meling, 1999

31/10/2005 Course AT-327 141

Peak production can be achieved between 2004 –2024



Оценка мировых темпов добычи нефти

0

10

20

30

40

50

60

70

80

90

100

1900

1908

1916

1924

1932

1940

1948

1956

1964

1972

1980

1988

1996

2004

2012

2020

2028

2036

2044

2052

2060

2068

2076

2084

2092

2100

Год

Млн

. баррелей/сут

Макс. запасы, 2800 млрд. баррелейСредние запасы, 2400 млрд. баррелейМин. запасы, 2160 млрд. баррелей

World production rate estimate

Max reserves = 2800 bill bblsMean reserves= 2400 bill bblsMin reserves = 2160 bill bbls

Year

Mill

bop

d


31/10/2005 Course AT-327 142

Mean oil recovery on all fileds in the world amountsto approx. 34.8%.As of 2000




Зависимость нефтеотдачи от извл. запасов м-я

34,79

0

10

20

30

40

50

60

70

80

90

100

1 10 100 1000 10000 100000 1000000

Запасы, млн. баррелей

Неф

теотдача,

%

МесторождениеСредневзвешенный показатель

Oil recovery versus field reserves

Reserves in mill bbls

Oil

reco

very

, %

FieldMean value

31/10/2005 Course AT-327 143

Distribution of liquid HC among countriesand regions


31/10/2005 Course AT-327 144

EOR/IOR can increase oil recovery up to 50 – 60%, whichis equivalent to the discovery of 810 – 1350 bill bblsadditional reserves of oil

This is higher than both undiscovered potential and produced oil volume. This can secure required rate of oilproduction for many decades.

Our evaluation: oil reserves will be depleted and itsproduction will cease by the middle of XXII century



31/10/2005 Course AT-327 145

Thank you!

Engineering - NTNU

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