SELECTING 3D RESERVOIR MODEL REALIZATIONS USING WELL TEST

1. SELECTING 3D RESERVOIR MODEL REALIZATIONS USING WELL TEST H. Hamdi (Heriot Watt University) Ph. Ruelland (Total E&P U.K.) P. Bergey (Total E&P U.K.) EAGE – Dubai – November 28th 2012

2. MATCHING WELL TEST ON 3D RESERVOIR MODELS • Critical source of multi-scale information. Two simulation methods: Finite difference models Analytical models LogΔP & Log ΔP’ Log(t) • Large model flexibility • Cumbersome & costly simulation • Non routine Assisted History Match • Facies and 3D structure • Slow convergence Focus Few simplistic solutions Fast to run and easy to match EAGE – Dubai – November 28th 2012

3. FIELD CHARACTERISTICS • Context: • Fluvial environment, anastomosing channels. • NTG 40 – 70%, Porosity 12-20%, Net sand permeability 10-500 mD range. • Light oil / gas condensate • Previous delineation showed strong permeability drop away from wellbore • Marginal economics in large part due to large scale connectivity and compartmentalization, poorly apprehended with previous generation object models. • Extended Well test: • 3+ months duration • Multiple sets of perforations • PLT acquisition during draw-down. Comparatively unambiguous interpretation. Reasonably stabilized production split during well test duration. EAGE – Dubai – November 28th 2012

4. EXTENDED Well test ANSWER References interpretations performed with 1 to 4 layers (linear composite with faults) Perfect data match for all cases. EAGE – Dubai – November 28th 2012

5. 3D MODEL MATCH OBTAINED RUN-OF-THE MILL WORKFLOW Good match of most important feature from an appraisal perspective Transitions never well matched TRIAL & ERROR ON OBJECT BASED + SGS MODEL SUBSTANTIAL DEVIATIONS FROM A PRIORI EAGE – Dubai – November 28th 2012

6. Training image Parana River, Argentina mouth delta (unit 1 & 2) Magdalena River, Colombia (unit 3) 2000 m 10 x 10 x 1 m cells EAGE – Dubai – November 28th 2012

7. MULTI-POINT STATISTICS BASED RESERVOIR MODELS Representative layers • Sector cell count: • 290 x 320 x 46 • Average cell size: • 11 x 11 x 2 m • SNESIM algorithm • Facies hierarchy • Auxiliary mud fraction variable • Chugunova & al, MPS constrained by continuous Auxiliary data. MathematicalGeosciences + Sequential Gaussian Simulation of porosity & Porosity / Permeability transforms per facies EAGE – Dubai – November 28th 2012

8. WELL TEST ANSWER – SENSITIVITY TO FACIES Valid model Shape of key transitions present in dataset Bracketing of large scale permeability Underestimation of medium scale permeability Underestimation of small scale permeability Local match action required EAGE – Dubai – November 28th 2012

9. WELL TEST ANSWER – SENSITIVITY TO PETROPHYSICS Limited sensitivity to spatial variations of porosity EAGE – Dubai – November 28th 2012

10. Effective volume cropping Hybridization Box cropping Potential for of use of FMM not done in this study (Jiang Xie & al 2012, SPE) EAGE – Dubai – November 28th 2012

11. FINAL MATCH : PRESSURE FIT & MODEL x 1.8 near wellbore permeability increase Hybrid looks right EAGE – Dubai – November 28th 2012

12. CONCLUSION • An example: • Stronger geology a priori (MPS)  better (deterministic) match of complex signature. • Around 5 weeks work time by trained personnel. • Further potential step: probabilistic & systematic approach. Most exciting leads: • Factoring systematically test rate uncertainties in pressure history match • Determination of 3D investigated volume by Fast Marching Method (for hybridisation or localization) • Approximated emitter pressure simulation by Fast Marching Method (?) • Fast & high dimension automated match: • Ensemble method approach • Facies parameterisation by distance to • Fault parameterisation • Multi-scale parameterization approaches (whatever the match approach) EAGE – Dubai – November 28th 2012

13. THANK YOU-QUESTIONS EAGE – Dubai – November 28th 2012