PNNL

Abstract

The regulatory oversight of a geologic carbon sequestration (GCS) project relies on iterative estimations, throughout the project lifetime, of the area where increased risks to underground sources of drinking water (USDWs) may occur due to the injection of CO2 into a subsurface reservoir. This area, referred to as Area of Review (AoR), is typically delineated based on the separate-phase CO2 plume and pressure predictions from physics-based reservoir simulators by assuming an open wellbore as a leakage pathway between the reservoir and the lowermost USDWs. The inherent uncertainty in input parameters used in reservoir modeling therefore affects the accuracy of determining the AoR for a project. Furthermore, the standard analytical approaches for calculating a critical pressure for delineating the risk area yield an infinite AoR for cases where the injection reservoir is overpressured relative to the USDWs. A methodology is presented here to better characterize the risk to USDWs while accounting for the uncertainty in reservoir modeling, with an application to a permitted GCS project, FutureGen 2.0, with an overpressured injection formation. The methodology relies on using the National Risk Assessment Partnership’s second-generation, open-source integrated assessment model (OpenIAM) to develop a probabilistic estimate of impact risk to USDW groundwater quality. CO2 and pressure predictions from the reservoir modeling conducted using the STOMP-CO2 simulator for the FutureGen 2.0 site are used in a system-level OpenIAM model with reservoir, wellbore, and aquifer components, allowing for: (1) assessing the extent of potential leakage into the USDW for the predicted reservoir pressure conditions; (2) evaluating the extent of potential impact based on a pre-determined “no-net-degradation” thresholds; and (3) accounting for uncertainty in reservoir permeabilities. The results demonstrate that this methodology can provide mapping of quantitative impact risk to USDWs for the delineation of a risk-based AoR and further informing project planning (e.g., design of a monitoring network). The estimation of impact, however, depends strongly on the selected “no-net-degradation” thresholds.