Measuring the Success  of Waterfloods   G. Renouf Saskatchewan Research Council
Acknowledgments <ul><ul><li>Petroleum Technology Research Council </li></ul></ul><ul><ul><li>BP Exploration (Alaska) Inc. ...
Outline of Talk <ul><li>Motivation </li></ul><ul><li>Recap of previous studies </li></ul><ul><li>Findings </li></ul><ul><l...
Motivation <ul><li>Waterflooding common in heavy oil reservoirs </li></ul><ul><ul><li>139 in AB and 68 in SK represent 24%...
Previous Studies <ul><li>2004 Study “Heavy Oil Waterflooding Scoping Study” </li></ul><ul><ul><li>Statistics of 54 heavy o...
Multivariate vs Univariate Analysis <ul><li>SI=secondary production as % of OIP/#yrs wf </li></ul>
Multivariate Analysis <ul><li>General </li></ul><ul><ul><li>Reservoir and operating parameters are x’s (41 x’s) </li></ul>...
12.42 1992 808 14.5 969 1.073 14 30 5.9 826 0.31 0.74 0.12 0.57 9 1995 900 15.9 960 1.073 20 30 6.34 1166 1.46 1.99 0.27 1...
Scatter Plot
Loading Plot
Variable Importance Plot
Previous Studies <ul><li>Most important reservoir parameters for medium oils: permeability; heterogeneity; reservoir tempe...
Previous studies, continued <ul><li>Operating parameters also differed for heavy vs medium oil waterfloods  </li></ul><ul>...
Tasks to Improve Database <ul><li>Add more points (more waterfloods) </li></ul><ul><li>Add more variables (more reservoir ...
Add More Points, More Variables <ul><li>Original plan </li></ul><ul><ul><li>Incorporate Alaska waterfloods </li></ul></ul>...
Missed WF 250031 43 WATER FLOOD  UPPER MANNVILLE EE  ALDERSON  250028 43 UPPER MANNVILLE BB  ALDERSON  250027 43 WATER FLO...
Accuracy of Success  Measurements <ul><li>Two Success measurements proven themselves </li></ul><ul><ul><li>SI=Secondary Pr...
Primary Production Measurement SI Calc’n assumes constant  production rate Actual production  rate declines  non-linearly ...
Decline Fitting <ul><li>Fit pre-waterflood production data with 3 types of equations </li></ul><ul><ul><li>Exponential </l...
Decline Calculations: Original Plan SI SI-FU SI-Decline SI-FU Decline EXPONENTIAL HARMONIC  HYPERBOLIC
Exponential vs Hyperbolic  vs Harmonic 772,000 711,000 565,000 37%
Decline Equation
Decline Calculations SI SI-FU SI-Decline SI-FU Decline SI SI-FU SI-Exp SI-Har SI-Hyp SI-FU-Exp SI-FU-Har SI-FU-Hyp
Examples of SI 1.27 1.98 Viking-Kinsella X 0.45 0.68 Taber Glauc K 0.78 0.77 Sibbald 1.66 Mantario North 0.31 0.51 Cactus ...
Multivariate PLS Models 53 WFs 75 WFs Better than 2007 0.505 SI-Hyp, SI 50%, SI-FU-Har 10%, SI-FU-Exp 10% Medium 0.397 SI-...
Waterfloods Newly Added  to Database
Heavy vs Medium WFs
Important Parameters to  Heavy Oil WFs
Effect of Net Pay
Viscosity Related Parameters <ul><li>Viscosity and Viscosity/Permeability significant to success of heavy oil wfs and insi...
Injection Rate Parameters
VRRcum vs VRR Deviation from 1 <ul><li>Heavy WFs: 13% VRR > 1.10 </li></ul><ul><li>Medium: 32% VRR > 1.10 </li></ul><ul><l...
Type of Well
Relationship of Converted Wells  To Years of Waterflooding
Effect of Operating Company
Score Contribution Plot Provost Ll UU (Harvest) Injection Throughput Harvest HDI HDP HAL Spacing
Prediction of Success <ul><li>Concept: want to predict waterflooding behaviour for pools currently on primary production <...
Success Prediction <ul><li>Model has declined in quality  </li></ul><ul><li>Adding Alberta Reds sub-population enlarged th...
Heavy Oils – Training Set Blue
Comparison of Prediction Method <ul><li>Prediction Set 7 WFs </li></ul><ul><li>Compare Prediction </li></ul><ul><ul><li>Bl...
Primary Pools <ul><li>Suffield Upper Mannville Y2Y (heavy) </li></ul><ul><li>Chauvin South Lloydminster J (medium) </li></...
Primary Pool Prediction
Primary Pool Prediction <ul><li>Chauvin S Lloydminster J </li></ul><ul><ul><li>Best prediction SI=0.68 </li></ul></ul><ul>...
Conclusions <ul><li>Collected data and measured success of 168 wfs </li></ul><ul><li>Completed 3 tasks to improve predicta...
Conclusions, cont’d <ul><li>Appears to be poorer predictor </li></ul><ul><li>Effect of certain parameters less clear cut <...
Conclusions, cont’d <ul><li>Heavy Oil WFs </li></ul><ul><li>Injection throughput rate </li></ul><ul><li>Converted injector...
Conclusions, cont’d <ul><li>Prediction is poor </li></ul><ul><li>I did it anyway: </li></ul><ul><ul><li>Chauvin S Lloydmin...
Recommendations for  Upcoming Research <ul><li>Fill in blank spots of database </li></ul><ul><li>Re-examine decline based ...
<ul><li>Thank you for your attention. </li></ul><ul><li>Any questions???? </li></ul>
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smart science solutions Measuring the Success

  1. 1. Measuring the Success of Waterfloods G. Renouf Saskatchewan Research Council
  2. 2. Acknowledgments <ul><ul><li>Petroleum Technology Research Council </li></ul></ul><ul><ul><li>BP Exploration (Alaska) Inc. </li></ul></ul><ul><ul><li>Canadian Natural Resources Ltd. </li></ul></ul><ul><ul><li>Canetic Resources Inc. </li></ul></ul><ul><ul><li>Husky Oil Energy Ltd. </li></ul></ul><ul><ul><li>Nexen Inc. </li></ul></ul><ul><ul><li>Shell International Exploration & Production BV </li></ul></ul><ul><ul><li>Total E&P Canada Ltd. </li></ul></ul>
  3. 3. Outline of Talk <ul><li>Motivation </li></ul><ul><li>Recap of previous studies </li></ul><ul><li>Findings </li></ul><ul><li>Conclusions and recommendations </li></ul>
  4. 4. Motivation <ul><li>Waterflooding common in heavy oil reservoirs </li></ul><ul><ul><li>139 in AB and 68 in SK represent 24% of heavy oil in place </li></ul></ul><ul><li>Additional recovery ranges from 0.4% to 47%. </li></ul><ul><li>We need to understand the reasons behind the extra-successful and failed waterfloods. </li></ul><ul><li>Extensive body of knowledge on waterflooding lighter oils … is it applicable to heavy oil waterflooding? </li></ul>
  5. 5. Previous Studies <ul><li>2004 Study “Heavy Oil Waterflooding Scoping Study” </li></ul><ul><ul><li>Statistics of 54 heavy oil waterfloods </li></ul></ul><ul><ul><li>Interviews with 25 engineering & field staff </li></ul></ul><ul><ul><li>8 abandoned waterfloods examined </li></ul></ul><ul><li>2006 Study “Measuring the Success of Western Canadian Waterfloods” </li></ul><ul><ul><li>Multivariate analysis </li></ul></ul><ul><ul><li>Compares heavy to medium oil waterfloods </li></ul></ul>
  6. 6. Multivariate vs Univariate Analysis <ul><li>SI=secondary production as % of OIP/#yrs wf </li></ul>
  7. 7. Multivariate Analysis <ul><li>General </li></ul><ul><ul><li>Reservoir and operating parameters are x’s (41 x’s) </li></ul></ul><ul><ul><li>Success measurements are y’s (8 y’s) </li></ul></ul><ul><ul><li>Each waterflood is an observation point (168 points) </li></ul></ul><ul><li>Details </li></ul><ul><ul><li>Can include qualitative x’s or y’s </li></ul></ul><ul><ul><li>Types: PCA, PLS, PCR </li></ul></ul><ul><ul><li>We used PLS </li></ul></ul>
  8. 8. 12.42 1992 808 14.5 969 1.073 14 30 5.9 826 0.31 0.74 0.12 0.57 9 1995 900 15.9 960 1.073 20 30 6.34 1166 1.46 1.99 0.27 1.70 8 1997 860 14.5 969 1.08 15 31 5.72 186 0.79 1.12 0.11 1.13 4.83 2000 860 16.0 959 1.054 33.1 31 5.5 190 0.00 0.00 0.08 0.00 16.58 1988 863 17.0 953 1.063 23 28.5 7.47 777 0.70 1.26 0.14 1.02 9 1996 863 17.0 953 1.063 23 32 5.75 502 0.00 0.00 0.26 0.00 16.33 1988 818 14.1 972 1.039 25 30 4 1344 0.21 0.08 0.20 0.17 45.92 1959 823 12.6 982 1.078 31 24.1 11.46 3076 0.17 0.19 0.12 0.30 16.58 1988 851 15.3 964 1.039 35 30 4.83 2736 0.57 0.48 0.14 0.50 16.5 1988 851 15.3 964 1.039 35 30 9.16 259 0.63 0.34 0.22 0.44 16.58 1988 814 12.7 981 1.039 31 29.6 6.8 793 0.19 0.04 0.10 0.14 34.83 1969 823 13.2 978 1.05 25 26.6 3.72 719 0.27 0.13 0.13 0.33 22.67 1981 532 16.0 959 1.02 21 30 4.1 421 0.29 0.23 0.11 0.21 16.67 1988 787 14.7 968 1.111 32 28 4.75 1409 0.92 0.24 0.11 0.85 16.58 1988 737 14.4 970 1.029 20 28 4.5 1125 0.36 0.42 0.06 0.32 14.58 1970 541 13.5 976 1.017 15 34 3.9 987 0.43 0.41 0.67 0.28 7.58 1997 625 18.1 946 1.036 25 30 5.95 227 0.31 0.23 0.08 0.32 14.58 1990 625 18.1 946 1.031 25 30 4.5 227 0.35 0.93 0.09 0.61 16.17 1988 625 18.1 946 1.031 25 30 5.46 420 0.88 0.58 0.07 0.57 19.08 1985 625 18.1 946 1.031 25 30 9.58 518 0.62 0.67 0.08 0.68 20.33 1984 712 17.9 947 1.033 23 35 2.75 971 0.16 0.10 0.23 0.11 11.5 1968 518 15.6 962 1.031 21 30 6.2 1263 0.03 0.28 0.38 0.28 20.67 1971 472 15.4 963 1.033 16 35.7 4.33 874 0.16 0.15 1.28 0.15 2.67 1992 475 14.8 967 1.023 20 30 4.9 2229 0.32 0.32 0.32 0.43 13.08 1971 493 14.4 970 1.016 20 32.37 3.99 1749 0.12 0.20 0.74 0.16 30.58 1972 563 15.3 964 1.02 18 35 4.15 923 0.05 0.28 0.27 0.17 38.42 1966 566 15.3 964 1.02 18 35 4.52 2220 0.06 0.44 0.27 0.20 10.92 1970 491 15.1 965 1.018 15.3 36 2.82 1604.5 0.09 0.24 0.34 0.26 14.25 1969 535 14.7 968 1.017 13 35 5.18 1522 0.07 0.07 0.29 0.06
  9. 9. Scatter Plot
  10. 10. Loading Plot
  11. 11. Variable Importance Plot
  12. 12. Previous Studies <ul><li>Most important reservoir parameters for medium oils: permeability; heterogeneity; reservoir temperature; porosity </li></ul><ul><li>Most important reservoir parameters for heavy oils: viscosity/permeability; formation volume factor; production depth </li></ul><ul><li>Comparison between the importance of injection throughput rate and years to fill-up shows pressure maintenance might not be only benefit. </li></ul>
  13. 13. Previous studies, continued <ul><li>Operating parameters also differed for heavy vs medium oil waterfloods </li></ul><ul><li>Horizontal & directional production and injection wells very important for heavy oil waterflooding; reducing conversion of producers to injectors </li></ul><ul><li>Well spacing important to success of both types </li></ul><ul><li>Screening criteria not very discriminating </li></ul><ul><li>Categorization reasonably successful </li></ul>
  14. 14. Tasks to Improve Database <ul><li>Add more points (more waterfloods) </li></ul><ul><li>Add more variables (more reservoir and operating parameters) </li></ul><ul><li>Make sure each y-variable (each success measure) is as accurate as possible </li></ul>
  15. 15. Add More Points, More Variables <ul><li>Original plan </li></ul><ul><ul><li>Incorporate Alaska waterfloods </li></ul></ul><ul><ul><li>Looked at 11 Alaskan fields </li></ul></ul><ul><ul><li>8 of 11 used gas and WAG injection with waterflooding </li></ul></ul><ul><li>Actual 2007 tasks </li></ul><ul><ul><li>Grew database from 83 to 168 waterfloods </li></ul></ul><ul><ul><li>New category from Alberta EUB data </li></ul></ul><ul><li>8 new parameters including: pumping, flowing wells, operating company </li></ul>
  16. 16. Missed WF 250031 43 WATER FLOOD UPPER MANNVILLE EE ALDERSON 250028 43 UPPER MANNVILLE BB ALDERSON 250027 43 WATER FLOOD UPPER MANNVILLE AA ALDERSON 250026 43 WATER FLOOD UPPER MANNVILLE Z ALDERSON 250025 43 WATER FLOOD AREA ALDERSON 250025 43 PRIMARY AREA ALDERSON 250025 43 TOTAL UPPER MANNVILLE Y ALDERSON 250021 43 UPPER MANNVILLE U ALDERSON 250020 43 UPPER MANNVILLE T ALDERSON 250019 43 WATER FLOOD UPPER MANNVILLE S ALDERSON Pool Field Pool Field Field and Pool Codes Field and Pool
  17. 17. Accuracy of Success Measurements <ul><li>Two Success measurements proven themselves </li></ul><ul><ul><li>SI=Secondary Production/OIP/Yrs WF*100% </li></ul></ul><ul><ul><li>SI-FU=SI calc’d year after fill-up </li></ul></ul><ul><li>SI Calculation: After WF start, oil is produced as both primary and secondary, want to fractionate the total </li></ul><ul><ul><li>Primary </li></ul></ul><ul><ul><li>Secondary </li></ul></ul><ul><li>SIR estimates Coleville </li></ul><ul><ul><li>4.6% primary </li></ul></ul><ul><ul><li>19.5% enhanced </li></ul></ul><ul><li>At WF start, 2.5% OOIP produced, leaving 2.1% primary </li></ul>Primary = 2.1 2.1+19.5 Secondary = 19.5 2.1+19.5
  18. 18. Primary Production Measurement SI Calc’n assumes constant production rate Actual production rate declines non-linearly WF Start
  19. 19. Decline Fitting <ul><li>Fit pre-waterflood production data with 3 types of equations </li></ul><ul><ul><li>Exponential </li></ul></ul><ul><ul><li>Harmonic </li></ul></ul><ul><ul><li>Hyperbolic </li></ul></ul><ul><li>Production data were individual wells or groupings of similarly-behaved wells </li></ul><ul><li>38% of waterfloods could not be decline-fitted </li></ul><ul><li>Hyperbolic generally best (68% of production data) </li></ul>
  20. 20. Decline Calculations: Original Plan SI SI-FU SI-Decline SI-FU Decline EXPONENTIAL HARMONIC HYPERBOLIC
  21. 21. Exponential vs Hyperbolic vs Harmonic 772,000 711,000 565,000 37%
  22. 22. Decline Equation
  23. 23. Decline Calculations SI SI-FU SI-Decline SI-FU Decline SI SI-FU SI-Exp SI-Har SI-Hyp SI-FU-Exp SI-FU-Har SI-FU-Hyp
  24. 24. Examples of SI 1.27 1.98 Viking-Kinsella X 0.45 0.68 Taber Glauc K 0.78 0.77 Sibbald 1.66 Mantario North 0.31 0.51 Cactus Lake unit 2 0.71 0.85 Senlac 0.15 0.06 Aberfeldy SI-Hyp SI Waterflood
  25. 25. Multivariate PLS Models 53 WFs 75 WFs Better than 2007 0.505 SI-Hyp, SI 50%, SI-FU-Har 10%, SI-FU-Exp 10% Medium 0.397 SI-Hyp, SI 50%, SI-FU-Har 10%, SI-FU-Exp 10% Heavy - Used 0.435 SI-Hyp, SI-Exp, SI-FU Hyp 10%, SI-FU Exp 10% Heavy - Best 0.507 SI-Exp, SI 50%, SI-Hyp 10%, SI-Har 10% All 0.532 SI, WOR 5% Medium - 2006 0.704 SI, WOR 5% Heavy - 2006 0.545 SI, WOR 80% All WFs - 2006 Q 2 Cum Y Variables Dataset
  26. 26. Waterfloods Newly Added to Database
  27. 27. Heavy vs Medium WFs
  28. 28. Important Parameters to Heavy Oil WFs
  29. 29. Effect of Net Pay
  30. 30. Viscosity Related Parameters <ul><li>Viscosity and Viscosity/Permeability significant to success of heavy oil wfs and insignificant to medium oil wfs </li></ul><ul><li>Viscosity data for only 30 of 168 waterfloods </li></ul><ul><li>Dataset restricted to these 30 waterfloods </li></ul><ul><ul><li>Inconsistent results: about same level of importance heavy oil wfs, more important to medium oil wfs </li></ul></ul><ul><li>Tested Viscosity predictor for Alaska reservoirs </li></ul><ul><li>Poor prediction of viscosity </li></ul><ul><li>Formula was important to medium oil wf success </li></ul>
  31. 31. Injection Rate Parameters
  32. 32. VRRcum vs VRR Deviation from 1 <ul><li>Heavy WFs: 13% VRR > 1.10 </li></ul><ul><li>Medium: 32% VRR > 1.10 </li></ul><ul><li>Heavy: 4% VRR > 1.25 </li></ul><ul><li>Medium: 15% VRR > 1.25 </li></ul>
  33. 33. Type of Well
  34. 34. Relationship of Converted Wells To Years of Waterflooding
  35. 35. Effect of Operating Company
  36. 36. Score Contribution Plot Provost Ll UU (Harvest) Injection Throughput Harvest HDI HDP HAL Spacing
  37. 37. Prediction of Success <ul><li>Concept: want to predict waterflooding behaviour for pools currently on primary production </li></ul><ul><ul><li>Predict success level </li></ul></ul><ul><ul><li>Identify waterflood most similar to the primary pool </li></ul></ul>
  38. 38. Success Prediction <ul><li>Model has declined in quality </li></ul><ul><li>Adding Alberta Reds sub-population enlarged the scatter plot rather than increased the density </li></ul><ul><li>Plan to capitalize on sub-populations: make prediction from sub-population rather than whole group </li></ul>
  39. 39. Heavy Oils – Training Set Blue
  40. 40. Comparison of Prediction Method <ul><li>Prediction Set 7 WFs </li></ul><ul><li>Compare Prediction </li></ul><ul><ul><li>Blue Training Set vs </li></ul></ul><ul><ul><li>Heavy WFs Training Set </li></ul></ul><ul><li>Blue Training Set: </li></ul><ul><li>39-7-18=14 wfs </li></ul>Slope much < 1 Y Intercept > 0 R 2 poor
  41. 41. Primary Pools <ul><li>Suffield Upper Mannville Y2Y (heavy) </li></ul><ul><li>Chauvin South Lloydminster J (medium) </li></ul><ul><li>Barriers: </li></ul><ul><ul><li>Lack of viscosity data </li></ul></ul><ul><ul><li>No cores </li></ul></ul><ul><ul><li>Aquifer support for Suffield Y2Y </li></ul></ul>
  42. 42. Primary Pool Prediction
  43. 43. Primary Pool Prediction <ul><li>Chauvin S Lloydminster J </li></ul><ul><ul><li>Best prediction SI=0.68 </li></ul></ul><ul><ul><li>Analogue WF Provost Sparky D & Edgerton Lloydminster C&J </li></ul></ul><ul><li>Suffield Upper Mannville Y2Y </li></ul><ul><ul><li>Best prediction SI=1.06 </li></ul></ul><ul><ul><li>Analogue WF Suffield Upper Mannville U </li></ul></ul>
  44. 44. Conclusions <ul><li>Collected data and measured success of 168 wfs </li></ul><ul><li>Completed 3 tasks to improve predictability of last year’s database </li></ul><ul><ul><li>83 wfs to 168 wfs </li></ul></ul><ul><ul><li>Added new parameters </li></ul></ul><ul><ul><li>Refined success measurements using decline calc’ns </li></ul></ul><ul><li>Last year’s database was unusually cohesive </li></ul>
  45. 45. Conclusions, cont’d <ul><li>Appears to be poorer predictor </li></ul><ul><li>Effect of certain parameters less clear cut </li></ul><ul><li>Would be missing large chunk of how certain wfs behave </li></ul><ul><li>Approaching truer sense of how heavy oil wfs differ from medium wfs </li></ul><ul><li>More confidence in effect of certain parameters when they show impact no matter what database is </li></ul>
  46. 46. Conclusions, cont’d <ul><li>Heavy Oil WFs </li></ul><ul><li>Injection throughput rate </li></ul><ul><li>Converted injectors </li></ul><ul><li>Pumping wells </li></ul><ul><li>Horizontal and directional producers and injectors </li></ul><ul><li>Was fill-up achieved? </li></ul><ul><li>Net pay </li></ul><ul><li>Ratio Viscosity/perm’y </li></ul><ul><li>Porosity </li></ul><ul><li>Medium Oil WFs </li></ul><ul><li>Injection throughput rate </li></ul><ul><li>Permeability </li></ul><ul><li>Heterogeneity </li></ul>
  47. 47. Conclusions, cont’d <ul><li>Prediction is poor </li></ul><ul><li>I did it anyway: </li></ul><ul><ul><li>Chauvin S Lloydminster J </li></ul></ul><ul><ul><ul><li>SI = 0.7 </li></ul></ul></ul><ul><ul><ul><li>Analogue WF = Provost Sp D or Edgerton Ll C&J </li></ul></ul></ul><ul><ul><li>Suffield Upper Mannville Y2Y </li></ul></ul><ul><ul><ul><li>SI = 1.1 </li></ul></ul></ul><ul><ul><ul><li>Analogue = Suffield Upper Mannville U </li></ul></ul></ul>
  48. 48. Recommendations for Upcoming Research <ul><li>Fill in blank spots of database </li></ul><ul><li>Re-examine decline based measurements </li></ul><ul><li>New parameters to add: injectivity data; pressure data; geological data </li></ul><ul><li>Collect field samples - quality injection water; presence natural surfactants; CO 2 injection; salinity of injection water </li></ul><ul><li>Revise prediction procedure so PCA is performed first, then PLS </li></ul>
  49. 49. <ul><li>Thank you for your attention. </li></ul><ul><li>Any questions???? </li></ul>
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