Final Project for Carlos Alejandro Berto Master of Engineering Chair of Advisory Committee :

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: 29000 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 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

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 faultsare the most common and most important structures in the reservoir. • Trébol, Comodoro Rivadavia, Mina El Carmenare 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 Area Central Norte (Region Map)

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

11. Area Central Norte 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 RegionEl Tordillo Field – Patagonia, Argentina

14. Reservoir Thickness Contour Plot (ft) – ACN Study RegionEl 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.) = 84426 - 41.8 * 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: 0.15 (fraction) Irreducible Water Saturation : 0.25 (fraction) Net Pay Interval : 131 ft Initial Reservoir Pressure: 1,830 psia Fluid Properties Oil Formation Volume Factor: 1.2 RB/STB Oil Viscosity: 1.0 cp Total Compressibility 25 E-6 psia-1

27. Production Performance Plot for Well S-677ACN Project - Blue, Junior, Brown Zones Oil Secondary Water Primary Trend #1 Production Rates , STB/D Completion (Oct. 76) Workover (Aug. 93) Workover (Jun. 82) 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 Performance Plot for Well S-677ACN Project - Blue, Junior, Brown Zones Oil Secondary Water Primary Trend #2 Production Rates , STB/D Completion (Oct. 76) Workover (Aug. 93) Workover (Jun. 82) 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 Performance Plot for Well S-677ACN Project - Blue, Junior, Brown Zones Oil Secondary Water Primary Production Rates , STB/D Completion (Oct. 76) Workover (Aug. 93) Workover (Jun. 82) 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) 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 = 0.452 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. qovs. 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. qovs. Np (Semi-Empirical-Approach) (S-677) “This plotting approach is used when bottomhole pressure data are not available”.

36. Primary Performance Np,mov: 328.9 MSTB Recovery factor: 6.0 % Secondary Performance Np,mov: 201.7 MSTB Recovery factor: 3.68 % Secondary/Primary Recovery Ratio = 0.613 EUR Analysis: Results – Well S-677 (Oil)

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: 0.15 (fraction) Irreducible Water Saturation : 0.25 (fraction) Net Pay Interval : 166 ft Initial Reservoir Pressure: 1,000 psia Fluid Properties Oil Formation Volume Factor: 1.01 RB/STB Oil Viscosity: 1.0 cp Total Compressibility 40 E-6 psia-1

39. Injection Performance Plot for Well S-638ACN Project - Blue, Junior, Brown Zones Pwf qwi Flowing Bottomhole Pressure , psia Water Injection Rates , STB/D Workover (Oct. 95) Workover (Oct. 98) Workover (Apr. 97) Conversion (Oct. 93) 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 = 439.6 acres • Flow Properties Permeability, kw = 1.848 md Skin factor, s = -6.498

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: • EURPrimaryvs. OOIP • EURSecondary vs. OOIP • EURSecondaryvs. 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 , EURSecondaryvs. Oil Rates.