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Evaluation of Reservoir Performance Using Decline Type Curves Improve Reservoir Description - Area Central Norte (ACN)
Region, El Tordillo Field Argentina
Final Project for
Carlos Alejandro BertoMaster of Engineering
Chair of Advisory Committee:
Dr. Thomas. A. Blasingame
Department of Petroleum Engineering
Texas A&M University – College Station, Texas
Outline
• El Tordillo Field Description.
• Area Central Norte Waterflood Project Description.
• Data Acquisition and Preparation.
• Production and Injection Data Analysis.
• Integration of Results.
• Conclusions and Recommendations
Objectives
• To present a description of El Tordillo Field and the Area Central Norte waterflood project.
• To show the preparation of the production and injection data.
• To analyze and interpret the reallocated production data.
• To demonstrate the various analyses.
• To integrate the results (as maps and crossplots).
• To make recommendations for future waterflood projects in El Tordillo Field.
El Tordillo Field
El Tordillo Field is located in The San Jorge Basin, Patagonia (Argentina)
C O M O D O R O R I V A D A V I A
A R G E N T I N A
7 1 ° 7 0 ° 6 9 ° 6 8 ° 6 7 ° 6 6 °
7 1 ° 6 9 °7 0 ° 6 8 ° 6 7 ° 6 6 °
ATLA
NTIC
OCE
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D E S E A D O M A S S I F
S O M O C U R A M A S S I F4 4 °
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M I L E SCH
ILE
N O R T H -W E S T E R N
A R E A
N O R T H C E N T R A L
A R E A
C E N T R A L B A S I N
W E S T E R N A R E A
S O U T H F L A N K
S O U T H -W E S T E R N
A R E A
ANDE
AN
BELT
O F F S H O R E
C O M O D O R O R I V A D A V I A Area: 29000 Acres
El Tordillo Field is recognized as one of the major oil fields in Argentina.
El Tordillo Field – Reservoir Data
• Total numbers of wells 850• Production oil wells 420• Injection water wells 69• Average final depth 9,840 ft• Area 29,000 acres• Cumulative oil (Aug. 1999) 189 MMSTB• OOIP 1,800 MMSTB
Reservoir Description
• El Tordillo Field reservoir consists of a complex of fluvial-dominated sandstone sequences comprised of multiple layers with distinctive shale zones.
• Sandstones bodies are concentrated in groups, locally called “complejos”.
• Normal faults are the most common and most important structures in the reservoir.
• Trébol, Comodoro Rivadavia, Mina El Carmen are principal producing formations in the stratigraphic column in the reservoir.
El Tordillo Field – Waterflood Performance
There are several producing regions within El Tordillo Field with:
• Excellent continuity of oil-bearing sands,
• Sequence development, and
• A high cumulative oil recovery.
These three characteristics are sufficient to define El Tordillo Field as “feasible” for waterflooding.
• Area Central Norte project (ACN) has an excellent secondary response.
EL TORDILLOPRODUCCION POR SECUNDARIA
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MESES
CA
UD
AL
[m
3/d
]
T.SUR TN ACN LPE BLOQUE D ACNE LPS ACNSOM TSPROF.
Waterflood Oil Rate in ACN (Aug ’99) = 2200 STB/D
El Tordillo Field – Waterflood Performance
Area Central Norte (Region Map)
Area Central Norte
• Stratigraphic Cross Section A-A’ for ACN Project Area
MINA EL CARMEN FORMATION
S-667 S-678 S-537 S-691 S-694 S-637 S-624 S-572 S-634 S-632 S-631 S-682 S-782
EL TREBOL FORMATION
PATAGONIA FORMATION
SARMIENTO-RIO CHICO FORMATION
COMODORO RIVADAVIA FORMATION
SALAMANCA FORMATION
8141 ft
Ew
0 ft
1000 ft
2000 ft
3000 ft
4000 ft
5000 ft
6000 ft
7000 ft
8000 ft
10000 ft
9000 ft
0 ft 1300 ft 2600 ft 3900 ft 5200ft 6500 ft 7800 ft 9100 ft 10500 ft
8443 ft8095 ft
8787 ft
7993 ft
8532 ft
8207 ft
8580 ft
8450 ft8532 ft 8472 ft 8561 ft 8521 ft
Dry Horizon (No production)
Gas, Oil, and Water production
Injection horizon
Gas production
Oil and Water production
Oil production
Converted water injection well
Project Area Cross-Sections
Area Central Norte (Region Map)
Area Central Norte
Project Area Cross-Sections
• Stratigraphic Cross Section B-B’ for ACN Project Area
MINA EL CARMEN FORMATION
S-554
EL TREBOL FORMATION
PATAGONIA FORMATION
SARMIENTO-RIO CHICO FORMATION
COMODORO RIVADAVIA FORMATION
SALAMANCA FORMATION
9000 ft9073 ft 8991 ft
8476 ft8498 ft 8630 ft
8334 ft
8056 ft
S-720S-719 S-693 S-637 S-638 S-516 S-642
N S
0 ft
1000 ft
2000 ft
3000 ft
4000 ft
5000 ft
6000 ft
7000 ft
8000 ft
10000 ft
9000 ft
0 ft 650 ft 1300 ft 1950 ft 2600 ft 3250 ft 3900 ft 4550 ft 5200 ft 5600 ft
Dry Horizon (No production)
Gas, Oil, and Water production
Injection horizon
Gas production
Oil and Water production
Oil production
Converted water injection well
Top of Reservoir Contour Plot (ft) – ACN Study RegionEl Tordillo Field – Patagonia, Argentina
Reservoir Thickness Contour Plot (ft) – ACN Study RegionEl Tordillo Field – Patagonia, Argentina
Data Preparation
Production Data
Injection Data
Static Reservoir Data
Data Preparation – Production Data
The fact that the production data are commingled may significantly affect our ability to analyze and interpret the production for each well:
It is impossible to provide an analysis for each individual layer.
The production data is “re-allocated” in Area Central Norte (ACN) zones: Comodoro Rivadavia and Mina El Carmen formations
Data Preparation – Production Data
Re-allocated Production Data
Well Production
Data
FluidProperties Geological
Markers
NeighborWellsData
WellboreDiagrams
Available information used to “re-allocate “ production on a per-well basis after each completion and each re-completion.
Data Preparation - Steps
• Identify errors or anomalies in the production and injection data.
• Locate and annotate changes in the completion practices.
• Reinitialize the production data in time.
• Reallocate the total production for each reservoir interval.
1.E+00
1.E+01
1.E+02
1.E+03
1962 1966 1970 1974 1978 1982 1986 1990 1994 1998
Data Preparation – “Re-allocation”O
il P
rod
uct
ion
Rat
es ,
ST
B/D
Date, year
ACN sandsOil Production Non -ACN sands
Oil Production
Production Performance Plot for Well –516Comparison of Total Oil Rate and ACN Project Zones Oil Rate
Data Preparation
Production Data
Injection Data
Static Reservoir Data
Data Preparation – Injection Data
Although the injection wells are injecting in a “multi-stage” fashion (i.e., injection over several layers simultaneously), the total injection per well is used in the analysis because the oil production could not be identified sand by sand.
Data Preparation
Production Data
Injection Data
Static Reservoir Data
Data Preparation – Static Reservoir Data
To estimate the static reservoir pressure as a func-tion of date, we used the fluid level measured in swab tests (performed on individual sands (or groups of sands)) during the productive life of each well.
Although the pressure data show a poor correlation with date, we believe that the data are reasonable, and as such, we have used the average trend for our analysis.
0
500
1000
1500
2000
2500
3000
1960 1965 1970 1975 1980 1985 1990 1995 2000
Data Preparation – Static Reservoir Data
Pressure (avg.) = 84426 - 41.8 * yearDatum : 7664 ft
Sta
tic
Res
ervo
ir P
ress
ure,
psi
Date, year
Static Reservoir Pressure Assigned by DateEl Tordillo Field, Argentina – ACN Region
high
avg.
low
Data Result Using Decline Type Curves
Production WellsThe material balance type curve analyses yield two types of results: “flow” and “volumetric” parameters.
• Reservoir properties Skin factor for near well damage or stimulation, s Effective permeability, k
• In-place fluid volumes Original oil-in-place, N Movable oil at current conditions, N p,mov
Reservoir drainage area, A
Example: Well S-677 (Oil)
The well data used in these analyses are:
Reservoir PropertiesPorosity: 0.15 (fraction)
Irreducible Water Saturation : 0.25 (fraction)
Net Pay Interval : 131 ft
Initial Reservoir Pressure: 1,830 psia
Fluid PropertiesOil Formation Volume Factor: 1.2 RB/STB
Oil Viscosity: 1.0 cp
Total Compressibility 25 E-6 psia-1
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1975 1979 1983 1987 1991 1995 1999
Production Performance Plot for Well S-677ACN Project - Blue, Junior, Brown Zones
Prod
ucti
on R
ates
, S
TB
/D
Date, yearW
orko
ver
(A
ug. 9
3)
PrimarySecondary
Oil
Water
Com
plet
ion
(Oct
. 76)
Wor
kove
r (
Jun.
82)
Trend #1
Well S-677 (Oil) – Match Trend #1
We note a good match of all the production data, for both the transient and boundary-dominated flow periods in trend #1.
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1975 1979 1983 1987 1991 1995 1999
Production Performance Plot for Well S-677ACN Project - Blue, Junior, Brown Zones
Prod
ucti
on R
ates
, S
TB
/D
Date, yearW
orko
ver
(A
ug. 9
3)
PrimarySecondary
Oil
Water
Com
plet
ion
(Oct
. 76)
Wor
kove
r (
Jun.
82)
Trend #2
Well S-677 (Oil) – Match Trend #2
We note an excellent match of all the production data, for both the transient and boundary-dominated flow periods (Trend #2).
1.E+00
1.E+01
1.E+02
1.E+03
1.E+04
1975 1979 1983 1987 1991 1995 1999
Production Performance Plot for Well S-677ACN Project - Blue, Junior, Brown Zones
Prod
ucti
on R
ates
, S
TB
/D
Date, yearW
orko
ver
(A
ug. 9
3)
PrimarySecondary
Oil
Water
Com
plet
ion
(Oct
. 76)
Wor
kove
r (
Jun.
82)
Secondary Trend
Well S-677 (Oil) – Match Secondary Trend
We note a good match of all the production data in the boundary-domi-nated flow periods during the secondary production trend.
Results: Well S-677 (Oil)
The production rate (and pressure) functions were plotted versus “material balance time” (Np/q) on the Fetkovich-McCray type curve. The following average results are obtained:
• Volumetric PropertiesOriginal Oil in Place, N = 5,485 MSTBDrainage Area, A = 92.8 acres
• Flow PropertiesPermeability, k = 0.452 md
Skin factor, s = -5.57
Estimated Ultimate Recovery Analysis
qo vs. Np (Semi-Empirical-Approach) (S-677) (This plotting approach is used when bottomhole pressure data
are not available).
Primary Performance
Extrapolating the trends prior to
waterflood response to qo=0,
the primary movable oil is
obtained.
Estimated Ultimate Recovery Analysis
qo vs. Np (Semi-Empirical-Approach) (S-677) “This plotting approach is used when bottomhole pressure data
are not available”.
Secondary Performance
Extrapolating the trends in the
waterflood period to qo=0, the secondary
movable oil is obtained.
EUR Analysis: Results – Well S-677 (Oil)
Primary PerformanceNp,mov: 328.9 MSTBRecovery factor: 6.0 %
Secondary Performance Np,mov: 201.7 MSTBRecovery factor: 3.68 %
Secondary/Primary Recovery Ratio = 0.613
Data Result Using Decline Type Curves
Injection WellsAs for oil cases performed previously, the material balance type curve analyses yield two types of results: “flow” and “volumetric” parameters.
• Reservoir properties• Skin factor for near well damage or stimulation, s• Effective permeability, kw
• In-place fluid volumes• Total system volume available for injection, W• Injectable water, Winj
• Injection area, A
Example : Well S-638 (Water Injection)
The well data used in the analysis are:
Reservoir PropertiesPorosity: 0.15 (fraction)
Irreducible Water Saturation : 0.25 (fraction)
Net Pay Interval : 166 ft
Initial Reservoir Pressure: 1,000 psia
Fluid PropertiesOil Formation Volume Factor: 1.01 RB/STB
Oil Viscosity: 1.0 cp
Total Compressibility 40 E-6 psia-1
1.E+01
1.E+02
1.E+03
1.E+04
1.E+05
1.E+06
9401 9501 9601 9701 9801 9901
0
500
1,000
1,500
2,000
2,500
3,000
3,500
4,000
4,500
5,000
5,500
6,000
Injection Performance Plot for Well S-638ACN Project - Blue, Junior, Brown Zones
Wat
er I
njec
tion
Rat
es ,
ST
B/D
Date, year
Wor
kove
r (
Oct
. 98)
Pwf
qwi
Con
vers
ion
(Oct
. 93)
Wor
kove
r (
Oct
. 95)
Wor
kove
r (
Apr
. 97)
Flo
win
g B
otto
mho
le P
ress
ure
, psi
a
Well S-638 (Inj.) – Match Injection Trend
• We note a good match of the injection data—for both the transient and transition flow periods.
Results: Well S-638 (Injection Well)
The injection rate (and pressure) functions were plotted versus “material balance time” on the Fetkovich/McCray type curve .The following results were obtained:
• Volumetric PropertiesTotal system volume available for injection, W = 42,040 MSTBWInjection Area, A = 439.6 acres
• Flow PropertiesPermeability, kw = 1.848 md
Skin factor, s = -6.498
Estimated Injectable Water Analysis – S-638
We note a reasonably linear trend with sig-nificant data scatter. The extrapolation of this trend yields Winj = 11.1 x 106 STBW
Injection Performance
By plotting the injectivity index, (qwi/p), versus
cumulative water injection, we can
estimate the injectable water volume when
(qwi/p)=0.
(qwi/p) vs. Wi
Integration of Results - Maps
The following maps are presented as a mechan-ism to integrate the results from our individual well analyses:
•Flow Capacity, kh
•Original Oil-in-Place,OOIP
•Primary and Secondary EUR
•Total Recovery Factor
•Secondary/Primary Recovery Ratio.
Flow Capacity (kh) Contour Map
OOIP
EUR(p)
Original-Oil-in-Place (OOIP) Contour Map
kh
EUR(p)
Primary EUR - Contour Map
OOIP
kh
Secondary EUR - Contour Map
Total Recovery Factor - Contour Map
Secondary/Primary Ratio - Contour Map
Integration of Results - Crossplots
•Crosplots are presented to estimate average values for the primary and secondary recovery factors and secondary/ primary recovery ratio:
EURPrimary vs. OOIP
EURSecondary vs. OOIPEURSecondary vs. EURPrimary
•Log-log correlation plots were prepared as an attempt to obtain meaningful relations between the computed flow capacity and the oil recovery versus initial oil rate in order to estimate the performance of infill wells in the ACN Region:
kh, OOIP, EURPrimary , EURSecondary vs. Oil Rates.
Comparison of Estimated Ultimate Recovery (Primary)Versus Oil-in-Place (OOIP ) Computed from Decline Type Curve Analysis
El Tordillo Field, Argentina(ACN Region- Zones : Blue, Junior, and Brown)
1.E+04
1.E+05
1.E+06
1.E+07
1.E+05 1.E+06 1.E+07 1.E+08
Computed Oil-in-Place, STB
Es
tim
ate
d U
ltim
ate
Re
co
ve
ry
(Pri
ma
ry),
ST
B
EUR PRIMARY = 0.1 OOIP
Crossplot: Primary EUR versus OOIP
Crossplot: Secondary EUR versus OOIP Comparison of Estimated Ultimate Recovery (Secondary)
Versus Oil-in-Place (OOIP ) Computed from Decline Type Curve AnalysisEl Tordillo Field, Argentina
(ACN Region- Zones : Blue, Junior, and Brown)
1.E+03
1.E+04
1.E+05
1.E+06
1.E+05 1.E+06 1.E+07 1.E+08
Computed Oil-in-Place, STB
Es
tim
ate
d U
ltim
ate
Re
co
ve
ry
(Se
co
nd
ary
), S
TB
EUR SECONDARY = 0.047 OOIP
Crossplot: Secondary EUR versus Primary EUR Comparison of Secondary Estimated Ultimate Recovery
Versus Primary Estimated Ultimate RecoveryEl Tordillo Field, Argentina
(ACN Region- Zones : Blue, Junior, and Brown)
1.E+04
1.E+05
1.E+06
1.E+07
1.E+04 1.E+05 1.E+06 1.E+07
Estimated Ultimate Recovery (Primary), STB
Es
tim
ate
d U
ltim
ate
Re
co
ve
ry (
Se
co
nd
ary
), S
TB
EUR Secondary = 0.47 EUR Primary
Crossplot: kh versus Initial Oil Rate (qoi) Comparison of Flow Capacity (kh )
Versus Initial Oil RateEl Tordillo Field, Argentina
(ACN Region- Zones : Blue, Junior, and Brown)
1.E+00
1.E+01
1.E+02
1.E+03
1.E+01 1.E+02 1.E+03 1.E+04
Initial Oil Rate, STB/D
Co
mp
ute
d F
low
Ca
pa
cit
y (kh
), m
d-f
t
kh (avg) = 4.7624 q oi 0.4944
Low
Avg
High
Crossplot: OOIP versus Initial Oil Rate (qoi) Comparison of Oil-in-Place (OOIP ) Computed from DeclineType Curve Analysis
Versus Initial Oil RateEl Tordillo Field, Argentina
(ACN Region- Zones : Blue, Junior, and Brown)
1.E+05
1.E+06
1.E+07
1.E+08
1.E+01 1.E+02 1.E+03 1.E+04
Initial Oil Rate, STB/D
Co
mp
ute
d O
il-i
n-P
lac
e,
ST
B
OOIP (avg) = 119017 q oi 0.6681
Low
Avg
High
Crossplot: EURprimary versus Initial Oil Rate (qoi) Comparison of Estimated Ultimate Recovery (Primary)
Versus Initial Oil RateEl Tordillo Field, Argentina
(ACN Region- Zones : Blue, Junior, and Brown)
1.E+04
1.E+05
1.E+06
1.E+07
1.E+01 1.E+02 1.E+03 1.E+04
Initial Oil Rate, STB/D
Es
tim
ate
d U
ltim
ate
Re
co
ve
ry
(Pri
ma
ry),
ST
B
EUR (primary)(avg) = 25010 q oi
0.5243
High
Avg
Low
Crossplot: EURsecondary versus Initial Oil Rate (qoi) Comparison of Estimated Ultimate Recovery (Secondary)
Versus Initial Oil RateEl Tordillo Field, Argentina
(ACN Region- Zones : Blue, Junior, and Brown)
1.E+03
1.E+04
1.E+05
1.E+06
1.E+01 1.E+02 1.E+03 1.E+04
Initial Oil Rate, STB/D
Es
tim
ate
d U
ltim
ate
Re
co
ve
ry
(Se
co
nd
ary
), S
TB
EUR (Secondary)(avg)
= 14299 q oi 0.4538
Low
Avg
High
Integration of Results – Time Dependency
Integration of Results – Time Dependency
Integration of Results – Time Dependency
Integration of Results – Time Dependency
•We note that the previous comparisons do not show any specific trends. The lack of any specific time dependency of the results clearly confirms that the reservoir is highly heterogeneous and probably of a low, to very low permeability.
Conclusions
The following conclusions are noted:
• The guidelines to set the production and injection realloca-tion are well established an all of the necessary information/ data was identified and sorted.
• The decline type curve and volumetric analyses yielded acceptable estimates of original oil-in-place, as well as primary and secondary movable oil.
• The calculation of movable oil volume using the q versus Np plot yields acceptable results (unless pwf varies significantly).
Conclusions (Cont.)
• Integrating the results of this study, we identified areas with favorable conditions for additional oil reserves. We believe that a detailed analysis (on a well-by-well basis) of these zones will support the drilling of new infill wells in the ACN Region.
• We observed relatively constant trends of OOIP and primary EUR versus completion date, which confirms that the reser-voir is highly heterogeneous, is of low permeability, and infill wells should improve overall recovery.
• Crossplots of results developed in this study can be used as predictive tools for estimating the recovery of infill wells of the ACN Region.
Conclusions (Cont.)
• The secondary/primary recovery ratio for the ACN Region (0.47) is a useful parameter for predicting secondary EUR in the preliminary evaluation of other projects with similar characteristics as El Tordillo Field.
RecommendationsIn order to enhance the recovery in the ACN Region, a detailed surveillance program is proposed:
• Monitoring of production by sands or by groups of sands.
• Periodic measurements of static reservoir pressure.
• Pressure and rate monitoring of water injection.
• Periodic step rate tests to optimize injection pressures and rates.
• Injection profile logging (for routing of injections fluids).
• Periodically perform specific production tests.
• Periodically check fluid levels to ensure pump-off in producing wells.
This work is dedicated to my lovely wife, Diana and to my two beautiful children, Lucia y Manuel.
Dedication
I would like to thank Tecpetrol S.A for providing me the opportunity and the financial support to pursue my Master of Engineering degree at Texas A&M University.
I would also like to thank the following individuals for their contributions to this work:
Dr. T.A. Blasingame , for serving as Committee Chairman, and for his advise, support, and encouragement during this investigation.
Dr. A. Datta-Gupta, Dr. R. Thompsen and Dr. J. Watkins for serving as Committee Members.
Acknowledgments
Evaluation of Reservoir Performance Using Decline Type Curves Improve Reservoir Description - Area Central Norte (ACN)
Region, El Tordillo Field Argentina
Final Project for
Carlos Alejandro BertoMaster of Engineering
Chair of Advisory Committee:
Dr. Thomas. A. Blasingame
Department of Petroleum Engineering
Texas A&M University – College Station, Texas