Stochastic seismic inversion to reduce the bias in simulated porosity field for CO2 injection in the Saint-Flavien reservoir, Québec, Canada

The estimation of the volume of pores available for fluids is of prime importance when evaluating the potential of a site for the geological storage of CO2. Acoustic impedance (AI) cube, inverted from seismic amplitude, are used to guide the geostatistical simulations of porosity. The use of an AI cube inverted by a deterministic approach generates a bias in the simulated porosity of the Saint-Flavien reservoir, Québec, Canada. The poor vertical resolution of the seismic data generates a low-pass filtered distribution of AI, where extreme values evaluated at well logs cannot be recovered. Stochastic seismic inversion (SSI) allows better recovering the whole bandwidth of AI distribution by optimally combining AI information from the observed seismic amplitude and AI well logs. AI cubes obtained by SSI better reproduce the distribution of porosity observed on well logs. This methodology is of prime importance in the Saint-Flavien context, as the average porosity is extremely low, and only a fraction of the reservoir exhibits higher porosity where CO2 injection would be possible. Zones of low AI and high porosity, recognized on well cuttings as having high clay content in the Saint-Flavien region, are only identified when using high-frequency AI cubes obtained by SSI.