A metric for evaluating conformance robustness during geologic CO2 sequestration operations

Abstract

A metric for quantifying the robustness of a designation of conformance of a geologic CO 2 sequestration (GCS) project during its operational phase is developed and demonstrated. Conformance in this context is a measure of the degree to which the sequestration system is understood and can be accurately modeled along with the degree to which the storage system is performing as designed. The robustness of conformance quantifies the degree to which parameter values can deviate from their current nominal estimates and still produce model forecasts that meet the performance criteria for the GCS operation. We develop and demonstrate the approach on a simplified scenario to illustrate the concept using a single uncertain parameter (homogeneous reservoir permeability) and a single performance criterion (critical pressure at a monitoring well in the reservoir; i.e., one that may displace brine from the reservoir to an overlying drinking water aquifer for example). Increased confidence in conformance assessment as more monitoring data are obtained is incorporated through the standard error of the coefficient (reservoir permeability in the case presented here), which we designate as the concordance metric. As more monitoring data become available during the course of the GCS operation, the standard error of the coefficient decreases (in general), thereby leading to increased conformance robustness as a larger deviation from nominal is required to fail to meet performance criteria. Increasing conformance robustness over time builds confidence that a GCS project will continue to meet performance criteria during the life-span of the project, thereby supporting designations of conformance. A lack of conformance robustness provides a critical warning that the performance criteria of the GCS operation are not robust against probabilistic and non-probabilistic uncertainty in model conceptualization and/or model parameters.

Improved geophysical monitoring of carbon sequestration through parameter linkage to reservoir modeling

“…Despite fairly significant deviations from the actual model, the 5-year ORM produced a gross-scale match of the actual gas saturation that turned out sufficient for the bound construction and ensuing delineation of anticipated target zones. A follow-up study similar to Harp et al (2019) would investigate at what point larger deviations, caused by larger ORM parameter errors, would render the BSEM imaging outcome too distorted. Harp et al (2019) developed a metric for quantifying the degree to which ORM parameters can deviate from their actuals without violating preset reservoir performance criteria.…”

“…A follow-up study similar to Harp et al (2019) would investigate at what point larger deviations, caused by larger ORM parameter errors, would render the BSEM imaging outcome too distorted. Harp et al (2019) developed a metric for quantifying the degree to which ORM parameters can deviate from their actuals without violating preset reservoir performance criteria. We envision a similar kind of robustness measure for assessing when an ORM may become too erroneous for properly constraining geophysical reservoir imaging.…”

Geomechanical effects of co2 storage in geological structures: two case studies

“…Some of the major potential hazards related to the underground storage of CO2 include the leakage of CO2 from the storage unit, induced seismic activity, significant ground deformation and well damage. Various cases have since been reported in which earthquakes were caused by the production and injection of gas or water in the underground storage sites [1][2][3][4]. There have been some attempts to describe the procedure leading to the seismicity in hydrocarbon production fields [5][6].…”

CO2 plume evolution in a depleted natural gas reservoir: Modeling of conformance uncertainty reduction over time

“…In terms of regulators and stakeholders, a conforming GCS project is a successful GCS project. Nevertheless, as with all subsurface technologies, there is uncertainty involved in the assessment of conformance, and this uncertainty must be understood in order to understand the robustness of conformance assessment (e.g., Harp et al, 2019).…”