inversemodeling

inversemodeling - Optimization in reservoir modeling,...

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Unformatted text preview: Optimization in reservoir modeling, engineering and management ERE 284 Department of Energy Resources Engineering Stanford University, Stanford, California, USA Overview Field Development Optimization Overview • The history matching problem • Reservoir model updating problem • Real­time optimization problem • Closed­loop reservoir management Techniques/Topics covered • Deterministic, gradient­based history matching • • • • • • • • Pilot­point method Adjoint method • Stochastic history matching with geological constraints Gradual deformation Probability perturbation • • Including 4D seismic data Scale issues and upscaling Principal component analysis (PCA) Kernel PCA Neural networks Pattern recognition techniques for dimension reduction • Ensemble Kalman filters Reservoir modeling constrained to flow and pressure data model : model parameters m, spatially distributed data : multiple diverse data sets d1, d2, of production history and other reservoir data True earth Earth’s response function Model error Measurement error Gathered data (d1, d2,…) Model mismatch Earth model m Forward model g Inverse model Simulated data (ds1, ds2,…) =g(m) Non­unique solution Example of inversion of pressure and flow data Permeability Distribution mD 80 Producer Injector 0 80 Solution by gradient­based method, no constraints Color Scale 1 (Case 1) 80 80 (A) Case 1 Initial Model 80 (B) Case 2 (C) Case 3 80 0 80 0 80 4 simulations 0 36 simulations 80 0 20 simulations 80 Color Scale 2 (Cases 2&3) 80 Inversion Result 80 80 80 0 80 0 80 0 80 0 80 Data match Case 1 (A) : Matching Result Case 2 (B) : Matching Result Case 3 (C) : Matching Result Solution by stochastic method with geological constraints Training Image 250 80 Initial Model 80 Inversion Result (A) Case 4 13 simulations 0 250 0 80 0 80 250 80 80 (B) Case 5 76 simulations 0 250 0 80 0 80 Data match Case 4 (A) : Matching Result Case 5 (B) : Matching Result Solution by stochastic method with geological constraints 250 80 80 (C) Case 6 180 simulations 0 250 0 80 0 80 250 80 80 (D) Case 7 233 simulations 0 250 0 80 0 80 Data match Case 6 (C) : Matching Result Case 7 (D) : Matching Result ...
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This note was uploaded on 01/24/2011 for the course ERE 284 taught by Professor . during the Spring '10 term at Stanford.

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inversemodeling - Optimization in reservoir modeling,...

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