Research advisor: Dr. Thomas W. Engler
Committee members: Drs. Mike Kelly and Reid Grigg
Presented by
Akapak “Nick” Srichumsin
Graduate Student
New Mexico Tech
1
2
Introduction
Reservoir characterization
Model construction
History matching
Prediction
Conclusions
2
3 3
4
This research is one part of the project entitled “Mini-Waterflood: A New Cost
Effective Approach to Extend the Economic Life of Small, Mature Oil
Reservoirs”.
The project focuses on assisting small producers with technical knowledge to
enhance oil recovery for a mature oil field.
4
Reservoir
Characterization
Reservoir Simulation Core Analysis
Evaluation of
Mini-Waterflood
Potential
5
The targeted reservoirs are small, mature, shallow, low pressure, low
temperature, and has unfavorable mobility.
Typically ignored, this type of reservoir generally still contains significant
amount of oil-in-place.
5
Round Tank
Fields with high oil production have experienced waterflood.
6
The main objective of this thesis is to evaluate the waterflood potential of the
Round Tank (Queen) reservoir and determine the best strategy for the field by
using reservoir simulation.
6
7 7
New Mexico
Texas
Miles
0 100
Carlsbad
Hobbs
Roswell
Lea
County
Eddy
County
Chaves County
Goat Seep reef
Caprock
Queen
Double L
Vest Ranch
S Lucky Lake
Sulimar
Round Tank
High Lonesome
miles
0 12
Delaware Basin
New Mexico
Texas
Miles
0 100
Carlsbad
Hobbs
Roswell
Lea
County
Eddy
County
Chaves County
Goat Seep reef
Caprock
Queen
Double L
Vest Ranch
S Lucky Lake
Sulimar
Round Tank
High Lonesome
miles
0 12
Delaware Basin
Thin reservoir (~16’ thick).
Stratigraphic trap
~1,500’ from the surface
The Round Tank Queen sand
8 8
Gp = 4.2 Bscf
Pi = 600psi
P ~ 50psi
RF ~ 92%
Np = 26 MBO
OOIP = 2.85 MMBO
RF ~ 1%
9 9
Gas properties
Dry gas w/ high N2
(61% N2 and 28% CH4)
Oil properties
Dead oil (very low GOR)
35°API w/ 13.67cp
10 10
To locate injectors along the downdip edge of the oil column in the water leg,
and producers along the updip edge of the oil column.
11 11
Data Acquisition
Data Interpretation
Model Construction
Model Validation
Prediction
Reservoir Characterization
Reservoir Simulation
12 12
13
A common problem in small, mature fields is the limited and poor quality data,
typically consisting of only old logs and production history.
Evaluation of the field relies on existing data or data which are easy to acquire.
Old logs (circa 1960s), 14 modern logs and one-core are the main sources for
this reservoir study.
13
14
Available wireline logs for acquiring porosity
Modern logs (late 2000s) – a combination of density and neutron logs.
Old logs (1960s to 1970s)
• Neutron
• Sonic
• Density
The main problems applying old logs are (1) the poor quality and reliability and
(2) the required conversion.
14
In general, only one type is available at each well location.
15 15
Density/neutron crossplot
Anhydrite layer
Anhydrite layer
Maximum porosity interval
16
A common problem for the old neutron log is the units; generally, CPS or API
unit was used.
Typically, these units can be converted to porosity unit (either % or fraction) with
the use of calibration chart provided by a logging company.
16
Calibration chart (courtesy Schlumberger)
If the proper calibration chart is not accessible, a linear relationship of tool
response and porosity can be created from two known, porosity control points.
Different in
operating companies,
scale ranges,
borehole conditions,
and calibration
17
All the neutron logs with various scale-ranges were normalized into 0-1 scale-
range with a linear relationship.
17
(from Modern logs)
Min. Ф interval
Max. Ф interval
Control point 2
Ф = 23.4%
Control point 1
Ф = 1%
18
Two linear relationships were made:
(1) Linear porosity vs. linear tool response
(2) Log porosity vs. linear tool response
18
(1)
(2)
Adjacent
wells
19
Advantages
The normalizing process helps to mitigate the effects of the different conditions
among wells such as hole size, mud type, and logging company.
The proposed application, therefore, improves unreliable and poor quality data
to useful and reliable data.
19
20
Wyllie’s and Raymer-Hunt transforms
(courtesy Schlumberger)
ФHi t & Mod t > 29%
Porosity-transform correlations
Wyllie’s transform
- Clean and consolidated formation
Raymer-Hunt transform
- Unconsolidated/friable formations
21 21
Adjacent well
Adjacent wells
Raymer-Hunt
Raymer-Hunt
Raymer-Hunt transform is not applicable within the Round Tank Queen formation.
22 22
Comparison between Raymer-Hunt transform with Gulf of Mexico data obtained from moderately consolidated to unconsolidated sands (Bassiouni 1994)
Unconsolidated sands from Gulf of Mexico do not comply with the Raymer-Hunt
transform; the actual porosities from core experiment tend to be lower than
calculated.
23
In general, abnormally high interval transit time is due to the effect of reservoir
gas and uncompacted formation.
Core samples collected from Round Tank Queen Unit No.6-Y indicate friable
characteristic of the formation.
23
Main factor causing abnormally high t
24
(max)
(max)
known
R
cU
Overestimated porosities due to the effect of friable sand need to be corrected.
The work was done by modifying Raymer-Hunt transform with the correction
factor, an Uncompaction Correction (Uc).
Uc is the ratio of apparent sonic porosity to known porosity.
24
log
log
t
ttC
ma
R
c
RR
U
'
C = 0.6 for gas zone,
C = 0.67 for oil and water zones
tma = 56 μsec/ft for sandstone formation
Raymer-Hunt transform
Modified Raymer-Hunt transform
Adjacent new wells
Raymer-Hunt Trans.
25 25
Comparison between modified Raymer-Hunt
transforms with Gulf of Mexico data obtained from
moderately consolidated to unconsolidated sands
The proposed procedure gives
satisfactory results in both value
and curve trend.
26
Water saturation of the field was observed through well logs with the use of
Archie’s equation.
Where a = tortuosity factor
m = cementation exponent
n = saturation exponent
26
n
T
w
wR
FRS
/1
m
aF
27
Resistivity/porosity crossplot or Pickett plot is applied for this study to examine m
and n exponents.
27
28 28
c OWC (~2210’)
Transition zone
FWL (???)
Hydrocarbon zone w/ Siw =41.7% (from core Siw =43%)
29
Capillary pressure curve was
constructed based on published
correlation and log-derived water
saturation.
The power function proposed by
Brooks and Corey (1964) is
applied to create Pc curve.
29
/1'
w
dc
S
pp
iworw
iwww
SS
SSS
1
'
ow
cpheight
433.0
where λ = pore-size distribution index. Pd = entry pressure
S’w = normalized water saturation
Pc curve can be converted to
height curve by
30
Layers of the Round Tank Queen Sand need to be identified to acquire accurate
definition of the geologic flow units within the sand.
A stratigraphic layering approach was chosen to identify the number of layers and
layer thicknesses.
30
31
Evidence of abnormally high responses from sonic logs indicates that a friable zone exists with the Queen sand.
The observation of friable zone was made by focusing on two dimensions – areal and vertical.
Areal Vertical
Highest
over-response
32
A core sample from Round Tank Queen Unit No.6-Y also supports that Layer3
is the most friable interval.
32
33
Mineralogy of the Round Tank Queen sand has been studied through
examination of core samples and interpretation of wireline logs.
33
Thin section study from core samples (Wilson 2010)
The main mineral is quartz, mixed with potassium feldspar, anhydrite, micas,
and illite.
34 34
Mineralogy analysis through wireline logs
Density/neutron crossplot Lithodensity MID plot
1510
1515
1520
1525
1530
1535
1540
1545
1550
1555
00.10.20.3
True Porosity, frac.
Dep
th, f
t
The Queen
Interval
Example from Eskimo State No.2
Mineralogy analysis was made by using density/neutron crossplot and lithodensity
MID plot.
35 35
Mineral identification chart (courtesy Schlumberger)
The result supports the core analysis about clay types.
Thorium/potassium ratios (Th/K) are quite consistent among layers (~1.7 Th/K).
36 36
Because the formation is characterized into 2 zones, friable and consolidated,
two porosity/permeability correlations are applied.
Round Tank Queen core experiment (taken from samples located in the friable zone)
Adjacent field core experiment
(the Sulimar Queen and South Lucky Lake fields)
37 37
38 38
To achieve the main objective of the study, the following approaches are
selected for constructing the simulation model:
Actual, full-field model with three-dimension aspect.
Isotropic permeability with a single porosity system.
Black-oil fluid description (Eclipse E100 is used for the study).
Fully-implicit equation solver.
39
No sensitivity analysis of gridblock number has been made on this study.
A rule of thumb mentioned in Ertekin (2001) is applied;
3 - 5 gridblocks between production wells.
39
The shortest distance
between wells (L)
L
Gridblock size (WxL) = L/5 x L/5
40
To accurately construct the model, coverage of friable zone need to be considered.
40
Areal Vertical
Porosity map of Layer3 before corrections of friable effect
Friable Consolidated
Friable
Consolidated
Friable Consolidated
41 41
3D-Blackoil
simulation model
Geologic
Description
- Structure
- Porosity
- Permeability
Fluid PVT
Properties
- Dead oil
- Dry gas
- Water
Petrophysics
- Pc curve
- Kr curves
42 42
10% Porosity cut-off for reservoir boundary
43 43
44
Reservoir pressure, well production and bottomhole flowing pressure are the
three parameters for history matching.
Assumption: All the wells, especially oil wells, were operated with low bottom
hole pressure.
Production rates were used in the model to constrain operating conditions when
running the simulation.
44
Model Validation
Well production
Reservoir pressure
Bottomhole flowing pressure
45
The decline curve analysis from Fetkovich (1996) type curve indicates that
most gas wells had produced with constantly low bottom hole pressure.
45
Mehurin#3, b=0.5
JW-State#2, b=0.5
46 46
Before history matching
After history matching (manual history-matching approach was applied)
JW-State#2
JW-State#2
47 47
48 48
60% Reduction
60% Reduction
75% Reduction
The large reduction indicates that permeability in the Round Tank Queen field is
significantly lower than the other Queen sands.
30% increased for kro
49 49
50 50
The proposed flooding pattern is to locate injectors along the downdip edge of the
oil column in the water leg, and producers along the updip edge of the oil column.
The pattern design, well locations and spacing, strongly depends on the existing
new wells in the field to reduce the cost of infill drilling.
The pattern consists of 6 producers and 6 injectors.
51 51
The prediction was performed by running the simulation for 20 years.
Injection and production rates were controlled by bottomhole flowing pressures.
All production wells produce with the minimum bottomhole flowing pressure.
The maximum bottomhole pressure for injection wells is limited at fracture
pressure.
~3.5 BWPD/well
~1.33 BOPD/well
- Prediction results -
Field injection and production rates
Injection rate
Production rate
The prediction results show extremely poor water injection and oil production.
52 52
The observation of oil saturation and
reservoir pressure through time
indicates the poor waterflooding
performance - slow flood front
movement and unable to fill-up
reservoir pressure.
53 53
Reservoir properties and water
injection rates of the Round Tank
Queen field were compared with
the successful waterflooding field,
the Sulimar Queen.
Water injection rates were
calculated from radial-flow,
steady-state equation with
various differential pressures
(dP).
SrrB
PPhkkq
weww
Rwfrw
w
)/ln(
)(00708.0
Many factors contribute to the low injection rate of the Round Tank Queen field
such as low permeability, low krw and low differential pressure.
54 54
Indication of the poor transmissibility of the formation.
~3.5 BWPD/well
~1.33 BOPD/well
- Prediction results -
Field injection and production rates
Injection rate
Production rate
55 55
Low production and injection rates would also be influenced by high oil viscosity.
56 56
An influence of the depleted reservoir pressure to waterflooding performance was
also investigated.
The observation of pressure fill-up trend was made by running the simulation
without opening any producers.
Shut-in all producers
Small pressure increase in oil and water zones; approximately 150 psi of pressure
is increased for 20 years of water injection.
57 57
The investigation was further made by multiplying permeability of the model with a
factor of 10 and reduce μo to 7 cp to reduce the effect of poor transmissibility.
10xPermeability and 7 cp oil viscosity
Even at higher injection rate and
better formation transmissibility,
pressure fill-up is still unfavorable.
Significant amount of oil moves up
into the gas cap due to water
displacement.
The proposed flooding pattern
seems not to be effective.
Water inj.
Oil prod. Water prod.
58 58
59
Successful characterization of the Round Tank Queen reservoir with limited and
poor quality data was made with the assistance of modern logs and core
analysis.
Normalization of old neutron logs and calibration of old sonic logs were two
techniques applied to acquire valuable information.
The study of mineralogy indicates that quartz is the main mineral of the
formation with other minor minerals present a combination of potassium
feldspar, anhydrite, micas and illite.
A newly discovered friable sand bed was identified and has implications on
reservoir performance.
The results from history matching show satisfactory outcomes; a minor
adjustment was made for the porosity distribution, and reservoir boundary was
identified.
59
60
The large permeability reduction from history matching indicates that
permeability of the Round Tank Queen formation is significantly lower than the
other Queen sands.
The prediction results of the proposed flooding pattern show poor performance:
low oil production and water injection rates, slow flood front movement and
unable to fill-up reservoir pressure.
Many factors contribute to the poor performance including low permeability,
high oil viscosity, depleted gas-cap and low differential pressure between
bottomhole and reservoir.
60
61 61
Research Partnership to Secure Energy for America (RPSEA)
Dr. Thomas W. Engler
Drs. Mike Kelly and Reid Grigg
Drs. Her-Yuan Chen and Robert E. Bretz
Armstrong Energy and Bruce Stubbs
Garrett A. Wilson, Albert Ofori, and Oluwafemi Oduye
Karen M. Balch
62 62
Q&A
63 63
Backup
64 64
Round Tank
Queen
Sulimar
Queen
krw' 0.06 0.3
uw 1.56 1.64
kro' 0.39 0.55
uo 13.67 7.6
M' 1.35 2.53
wkro
okrwM
'
''
65
Model discretization is the process of dividing space and time of the simulation
model into discrete segments.
Space discretization gives information about grid-number needed for horizontal
and vertical directions whereas time discretization provides the timesteps used
in the model.
65
66
Space Discretization
Vertical discretization (layering)
As stated previously, the Round Tank Queen sand can be divided into three
layers based on gamma ray logs.
66
Time Discretization (Timesteps)
Timesteps are placed on any major well history occurred such as 1st production,
shut-in, and workover.
Timesteps from all the wells are placed on yearly intervals, and all the wells share
the same timestep (Jan 1 of every year) for simulator computation.
67
No sensitivity analysis of gridblock number has been made on this study.
A rule of thumb mentioned in Ertekin (2001) is applied;
For primary recovery, 3 - 5 gridblocks between production wells.
For waterflooding recovery, 5 - 10 gridblocks between adjacent wells.
67
The shortest distance
between wells (L)
L
Gridblock size (WxL) = L/5 x L/5
> 10 Gridblocks
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