Model selection for CO2 sequestration using surface deformation and injection data

Incorporating time-lapse observations from sources such as remote sensing and seismic is important for monitoring the migration of CO2 plumes in carbon capture and storage projects. Significant computational costs make it impractical to run coupled flow-geomechanical simulations for all plausible geologic scenarios in a prior ensemble. This study presents a model selection framework that integrates a fast approximator as a proxy to evaluate flow and geomechanical responses of geologic models. The proxy utilizes a particle tracking algorithm to mimic flow paths of injected CO2 within the geologic models. Pressure changes and rock deformation resulting from CO2 injection are estimated using a finite-element algorithm. The reliability of the proposed proxy is tested by comparing simulation and proxy results with regards to the shapes and extents of CO2 plumes, reservoir pressure, and vertical displacement at the top layer of a given reservoir. Models showing similar proxy responses are grouped into clusters by invoking multi-dimensional scaling followed by k-means clustering. A representative model of each cluster is selected, and its dynamic responses are evaluated by running flow-geomechanical simulations. The posterior ensemble consists of the models in the cluster whose representative conforms to given observation data. The proposed model selection approach is applied to history matching of a realistic channelized reservoir and a fractured reservoir inspired from In Salah, Algeria. The two case studies demonstrate that the incorporation of surface deformation data within model selection contributes to reduction in geologic uncertainty by improving the matching quality of well responses.