Incorporating Data Confidence and Scoring Sensitivity into Site Selection Ranking in Depleted Hydrocarbon Reservoirs

Abstract

Abstract Carbon capture and sequestration (CCS) is playing a role in mitigating carbon emissions, and that role is expected to grow dramatically with time. A key element to the widespread deployment of CCS is finding a suitable sequestration site for carbon storage. Site screening and ranking frameworks designed to provide insights into the suitability of storage sites are only as effective as the underlying data used. Therefore, in this work, data confidence is incorporated into a quantitative, criteria-driven methodology developed to assess the potential suitability of depleted oil and gas reservoirs for carbon storage. A sensitivity analysis was then performed on criterion weightings to explore the results’ variability. The criteria-driven workflow and data confidence analysis were applied to fields in the Gulf of Mexico and existing carbon storage projects in depleted hydrocarbon reservoirs. Including data confidence in the scoring of sites in the Gulf of Mexico decreased the technical field score by 4% to 15%, with the most significant changes stemming from heavily weighted criteria with low data confidence. As data confidence increases for a site, the site becomes more desirable even if the criteria scores do not change since more information about the site is known. Engineering solutions can be used to improve lower-scoring criteria.