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Sensitivity Analysis of Rock Physics Parameters for Modeling Time-Lapse Seismic(4D) response of Norne Field. Amit Suman and Tapan Mukerji 25 th SCRF Annual Meeting May 9 – 11, 2012. Joint Inversion Loop. Predicted flow and seismic response. Observed flow and seismic response. Model.
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Sensitivity Analysis of Rock Physics Parameters for Modeling Time-Lapse Seismic(4D) response of Norne Field Amit Suman and Tapan Mukerji 25th SCRF Annual Meeting May 9 – 11, 2012
Joint Inversion Loop Predicted flow and seismic response Observed flow and seismic response Model Reservoir SCRF
Motivation Production data at time t Dynamic modeling Δ Pressure Δ Saturation Optimize mismatch Velocity at time t Rock physics modeling Seismic data at time t Update parameters
Previous Work • Last year we investigated parameter sensitivity for modeling time-lapse seismic and flow data of Norne field • One of the investigated parameters was rock physics model • We didn’t investigate sensitivity of varying rock physics parameters on modeling 4D response SCRF
Questions? “Should we investigate sensitive rock physics parameters in modeling 4D response?” “What are the sensitive rock physics parameters in modeling 4D response?” SCRF
Norne Field Segment E F1H E3H In this study well log data of two wells are used SCRF
Data Available • Well logs (Sw, Sonic, Phi) • Horizons • Well data • - Oil , gas and water flow rate • - BHP (Bottom hole pressure) SCRF
Rock Physics Modeling Well Logs K and G (All Brine) Vp and Vs (Initial) K and Phi G and Phi Sonic Sw, Phi Gassmann’s Substitution Calculate Vp and Vs (All Brine) K and G (All Brine) Facies classification K and G (at Reservoir) Populate K ,G based on Phi K : Bulk Modulus G: Shear Modulus SCRF
Facies Classification Shale Brine Sand Vp / Vs Shaly Sand Oil Sand AI Vsh SCRF
Rock Physics Modeling Well Logs K and G (All Brine) Vp and Vs (Initial) K and Phi G and Phi Sonic Sw, Phi Gassmann’s Substitution Calculate Vp and Vs (All Brine) K and G (All Brine) Facies classification K and G (at Reservoir) Populate K ,G based on Phi K : Bulk Modulus G: Shear Modulus SCRF
Sensitivity Parameters in fluid substitution • Clay content • Salinity • Gas-oil ratio (GOR) • Pore pressure • The sensitivity of varying above parameters to variations in Response Response: Sum of seismic P-wave velocity after fluid substitution SCRF
Experimental Design SCRF
Results of fluid substitution Sensitivity to clay content Sensitivity to salinity 40 16000 20 0 15500 15000 Response Sensitivity to pore pressure Sensitivity to GOR 225 30 200 27 25 175 Clay content and GOR are the first and second most sensitive parameters in fluid substitution
Rock Physics Modeling Well Logs K and G (All Brine) Vp and Vs (Initial) K and Phi G and Phi Sonic Sw, Phi Gassmann’s Substitution Calculate Vp and Vs (All Brine) K and G (All Brine) Facies classification K and G (at Reservoir) Populate K ,G based on Phi K : Bulk Modulus G: Shear Modulus SCRF
Rock physics model Varying clay content and GOR (9 cases) SCRF
Constant cement model Cement fraction Coordination number Clay content
Fluid mixing • Seismic velocities depend on fluid saturation as well as saturation scale • Reservoirs with gas are very likely to show patchy behavior Sengupta ,2000 SCRF
Effective pressure model Two effective pressure models are selected for sensitivity study SCRF
Sensitivity Parameters in modeling 4D response • Clay content • Gas-oil ratio (GOR) • Coordination number • Cement fraction • Effective pressure model • Fluid mixing (Uniform or Patchy) • The sensitivity of varying above parameters to variations in Response Response: L1 Norm of change in seismic P-wave impedance after 4 years
Experimental Design Total number of cases: 324
Compare Methodology Dynamic modeling (1997-2001) Δ Pressure Δ Saturation P-wave impedance in 1997 and 2001 Rock physics modeling Difference in impedance SCRF
Results P-wave impedance change in 4 years (m/s.kg/m3) Clay content = 0 % Clay content = 20 % SCRF
Results Sensitivity to clay content Sensitivity to coordination number 9 7 5 40 20 0 Sensitivity to GOR Sensitivity to cement Response 3 5 1 225 200 175 Sensitivity to effective pressure model Sensitivity to fluid mixing Uniform Patchy Model 1 Model 2
Conclusions and Future Work • Clay content is the most sensitive parameter in fluid substitution • Salinity and pore pressure have a lesser impact than clay content • Coordination number is the most sensitive parameter in modeling 4D response of Norne field • The result of this study will be used in joint inversion of time-lapse and production data of Norne field SCRF
Acknowledgement • Statoil for data • Norwegian University of Science and Technology (NTNU) SCRF
Conclusions and Future Work • Clay content is the most sensitive parameter in fluid substitution • Salinity and pore pressure have a lesser impact than clay content • Coordination number is the most sensitive parameter in modeling the time lapse seismic signature of Norne field • The result of this study will be used in joint inversion of time-lapse seismic and production data of Norne field SCRF