Simulation of Carbon Dioxide Storage Applying Accurate Petrophysics, Fluid-Flowand Seismics Models

Abstract

Capture and storage of Carbon dioxide in aquifers and reservoirs is one of the solutions to mitigate the greenhouse effect. Geophysical methods can be used to monitor the location and migration of the gas in the underground. To perform this task properly, a suitable geological model is important, which simulates the geometry and petro-elastical properties of the different formations. In this work we integrate numerical simulators of CO2-brine flow and seismic wave propagation to model and monitor CO2 storage in saline aquifers. We also build a petrophysical model of a shaly sandstone based on porosity and clay content and considering the variation of properties with pore pressure and fluid saturation.
The pressure map before the injection of CO2 is assumed to be hydrostatic for which a reference porosity map is defined. The permeability is assumed to be anisotropic and is obtained from first principles as a function of porosity and grain sizes. The density is the usual arithmetic average of the sandy and
shaly components. The numerical simulator of the CO2-brine flow is based on the Black-Oil formulation for two phase flow in porous media, which uses the Pressure-Volume-Temperature (PVT) behavior as a simplified thermodynamic model. The propagation of waves in porous media is described using a
viscoelastic model that takes into account the dispersion and attenuation effects due to the presence of heterogeneities in the fluid and solid phase properties. We introduce the P-wave attenuation following White’s model of porous layers alternately saturated with brine and CO2. S-wave attenuation is considered with a mechanism related to the P-wave one. Numerical examples of CO2 injection and time-lapse seismics in the Utsira formation at the Sleipner field are analyzed. The Utsira formation is represented using the new petrophysical model that allows a realistic inclusion of shale seals and fractures. The results of the simulations show the capability of the proposed methodology to monitor the migration and dispersal of the CO2 plume and to make long term predictions.