1. 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 Berto
Master of Engineering
Chair of Advisory Committee:
Dr. Thomas. A. Blasingame
Department of Petroleum Engineering
Texas A&M University – College Station, Texas

2. 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

3. 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.

4. El Tordillo Field
El Tordillo Field is located in The San Jorge Basin, Patagonia (Argentina)
Area: Acres
El Tordillo Field is recognized as one of the major oil fields in Argentina.

5. El Tordillo Field – Reservoir Data
Total numbers of wells
Production oil wells
Injection water wells
Average final depth ,840 ft
Area ,000 acres
Cumulative oil (Aug. 1999) MMSTB
OOIP 1,800 MMSTB

6. 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.

7. 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.

8. El Tordillo Field – Waterflood Performance
Waterflood Oil Rate in ACN (Aug ’99) = 2200 STB/D
Area Central Norte project (ACN) has an excellent secondary response.

9. Area Central Norte (Region Map)

10. Project Area Cross-Sections
Stratigraphic Cross Section A-A’ for ACN Project Area

11. Area Central Norte (Region Map)

12. Project Area Cross-Sections
Stratigraphic Cross Section B-B’ for ACN Project Area

13. Top of Reservoir Contour Plot (ft) – ACN Study Region El Tordillo Field – Patagonia, Argentina

14. Reservoir Thickness Contour Plot (ft) – ACN Study Region El Tordillo Field – Patagonia, Argentina

15. Data Preparation
Production Data
Injection Data
Static Reservoir Data

16. 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

17. Data Preparation – Production Data
Re-allocated
Production Data
Well
Production
Data
Neighbor
Wells
Data
Fluid
Properties
Wellbore
Diagrams
Geological
Markers
Available information used to “re-allocate “ production on a per-well basis after each completion and each re-completion.

18. 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.

19. Data Preparation – “Re-allocation”
Production Performance Plot for Well –516
Comparison of Total Oil Rate and ACN Project Zones Oil Rate
ACN sands
Oil Production
Non -ACN sands
Oil Production
Oil Production Rates , STB/D
Date, year

20. Data Preparation
Production Data
Injection Data
Static Reservoir Data

21. 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.

22. Data Preparation
Production Data
Injection Data
Static Reservoir Data

23. 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.

24. Data Preparation – Static Reservoir Data
Static Reservoir Pressure Assigned by Date
El Tordillo Field, Argentina – ACN Region
Pressure (avg.) = * year
Datum : 7664 ft
high
avg.
low
Static Reservoir Pressure, psi
Date, year

25. Data Result Using Decline Type Curves
Production Wells
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, k
In-place fluid volumes
Original oil-in-place, N
Movable oil at current conditions, N p,mov
Reservoir drainage area, A

26. Example: Well S-677 (Oil) The well data used in these analyses are:
Reservoir Properties
Porosity: (fraction)
Irreducible Water Saturation : (fraction)
Net Pay Interval : ft
Initial Reservoir Pressure: 1,830 psia
Fluid Properties
Oil Formation Volume Factor: 1.2 RB/STB
Oil Viscosity: cp
Total Compressibility 25 E-6 psia-1

27. Production Rates , STB/D
Production Performance Plot for Well S-677 ACN Project - Blue, Junior, Brown Zones
Oil
Secondary
Water
Primary
Trend #1
Production Rates , STB/D
Completion (Oct. 76)
Workover (Jun. 82)
Workover (Aug. 93)
Date, year

28. 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.

29. Production Rates , STB/D
Production Performance Plot for Well S-677 ACN Project - Blue, Junior, Brown Zones
Oil
Secondary
Water
Primary
Trend #2
Production Rates , STB/D
Completion (Oct. 76)
Workover (Jun. 82)
Workover (Aug. 93)
Date, year

30. 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).

31. Production Rates , STB/D
Production Performance Plot for Well S-677 ACN Project - Blue, Junior, Brown Zones
Oil
Secondary
Water
Primary
Production Rates , STB/D
Completion (Oct. 76)
Workover (Jun. 82)
Workover (Aug. 93)
Secondary Trend
Date, year

32. 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.

33. Results: Well S-677 (Oil) Volumetric Properties Flow Properties
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 Properties
Original Oil in Place, N = 5,485 MSTB
Drainage Area, A = 92.8 acres
Flow Properties
Permeability, k = md
Skin factor, s = -5.57

34. Estimated Ultimate Recovery Analysis
Primary Performance
Extrapolating the trends prior to waterflood response to qo=0, the primary movable oil is obtained.
qo vs. Np (Semi-Empirical-Approach) (S-677)
(This plotting approach is used when bottomhole pressure data are not available).

35. Estimated Ultimate Recovery Analysis
Secondary Performance
Extrapolating the trends in the waterflood period to qo=0, the secondary movable oil is obtained.
qo vs. Np (Semi-Empirical-Approach) (S-677)
“This plotting approach is used when bottomhole pressure data are not available”.

36. EUR Analysis: Results – Well S-677 (Oil)
Primary Performance
Np,mov: MSTB
Recovery factor: 6.0 %
Secondary Performance
Np,mov: MSTB
Recovery factor: %
Secondary/Primary Recovery Ratio = 0.613

37. Data Result Using Decline Type Curves
Injection Wells
As 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

38. Example : Well S-638 (Water Injection)
The well data used in the analysis are:
Reservoir Properties
Porosity: (fraction)
Irreducible Water Saturation : (fraction)
Net Pay Interval : ft
Initial Reservoir Pressure: 1,000 psia
Fluid Properties
Oil Formation Volume Factor: RB/STB
Oil Viscosity: cp
Total Compressibility 40 E-6 psia-1

39. Injection Performance Plot for Well S-638 ACN Project - Blue, Junior, Brown Zones
Pwf
qwi
Water Injection Rates , STB/D
Flowing Bottomhole Pressure , psia
Conversion (Oct. 93)
Workover (Oct. 95)
Workover (Apr. 97)
Workover (Oct. 98)
Date, year

40. Well S-638 (Inj.) – Match Injection Trend
We note a good match of the injection data—for both the transient and transition flow periods.

41. 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 Properties
Total system volume
available for injection, W = 42,040 MSTBW
Injection Area, A = acres
Flow Properties
Permeability, kw = md
Skin factor, s =

42. Estimated Injectable Water Analysis – S-638
Injection Performance
By plotting the injectivity index, (qwi/Dp), versus cumulative water injection, we can estimate the injectable water volume when (qwi/Dp)=0.
(qwi/Dp) vs. Wi
We note a reasonably linear trend with sig-nificant data scatter. The extrapolation of this trend yields Winj = 11.1 x 106 STBW

43. 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.

44. Flow Capacity (kh) Contour Map
OOIP
EUR(p)

45. Original-Oil-in-Place (OOIP) Contour Map
EUR(p) kh

46. Primary EUR - Contour Map
OOIP kh

47. Secondary EUR - Contour Map

48. Total Recovery Factor - Contour Map

49. Secondary/Primary Ratio - Contour Map

50. 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. OOIP
EURSecondary 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.

51. Crossplot: Primary EUR versus OOIP

52. Crossplot: Secondary EUR versus OOIP

53. Crossplot: Secondary EUR versus Primary EUR

54. Crossplot: kh versus Initial Oil Rate (qoi)

55. Crossplot: OOIP versus Initial Oil Rate (qoi)

56. Crossplot: EURprimary versus Initial Oil Rate (qoi)

57. Crossplot: EURsecondary versus Initial Oil Rate (qoi)

58. Integration of Results – Time Dependency

59. Integration of Results – Time Dependency

60. Integration of Results – Time Dependency

61. 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.

62. 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).

63. 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.

64. 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.

65. Recommendations
In 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.

66. Dedication
This work is dedicated to my lovely wife, Diana and to my two beautiful children, Lucia y Manuel.

67. Acknowledgments
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.

68. 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 Berto
Master of Engineering
Chair of Advisory Committee:
Dr. Thomas. A. Blasingame
Department of Petroleum Engineering
Texas A&M University – College Station, Texas