Model verification: synthetic single pattern simulations using seismic reflection data

During Phase 1 of the Weyburn Project (2000-2004), 4D reflection seismic data were used to map CO2 migration within the Midale reservoir, while an extensive fluid sampling program documented the geochemical evolution triggered by CO2-brine-oilmineral interactions. The aim of this task (3b.11) is to exploit these existing seismic and geochemical data sets, augmented by CO2/H2O injection and HC/H2O production data toward optimizing the reservoir model and thereby improving site characterization and dependent predictions of long-term CO2 storage in the Weyburn-Midale reservoir. Our current project activities have concentrated on completing and testing a stochastic inversion method that will identify reservoir models that optimize agreement between the observed and predicted seismic response. This report describes the results of a validation test that uses synthetic seismic data to identify optimal porosity/permeability distributions within the reservoir. The report partially fulfills deliverable D3: “Model verification: synthetic single pattern simulations” in the project’s statement of work. A future deliverable will describe verification activities related to the geochemical inversion algorithm. This work has been performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under Contract DE-AC52-07NA27344. Introduction When completed, our completed stochastic inversion tool will explicitly integrate reactive transport modeling, facies-based geostatistical methods, and a novel stochastic inversion technique to optimize agreement between observed and predicted storage performance. Such optimization will be accomplished through stepwise refinement of: 1) the reservoir model—principally its permeability magnitude and heterogeneity—and 2) geochemical parameters—primarily key mineral volume fractions and kinetic data. We anticipate that these refinements will facilitate significantly improved history matching and forward modeling of CO2 storage. Our tool uses the Markov Chain Monte Carlo (MCMC) methodology. Deliverable D1, previously submitted as a report titled “Development of a Stochastic Inversion Tool To Optimize Agreement Between The Observed And Predicted Seismic Response To CO2 Injection/Migration in the Weyburn-Midale Project” (Ramirez et al., 2009), described the stochastic inversion approach that will identify reservoir models that optimize agreement between the observed and predicted seismic response. The software that implements this approach has been completed and requires that its performance be verified. This document contains deliverable D3, a report that summarizes verification activities that evaluate the performance of the software and its ability to recover reservoir model permeabilities that optimize agreement between measured and predicted seismic reflection data. A future deliverable will describe verification activities that ensure recovery of geochemical parameters (mineral volume fraction, kinetic parameters) that optimize agreement between measured and predicted aqueous chemistry data.