Reducing uncertainty associated with CO2 injection and brine production in heterogeneous formations. (June 2015)

• Record Type: Journal Article
• Authors: Dempsey, David; O'Malley, Daniel; Pawar, Rajesh
• Is Part Of: International journal of greenhouse gas control. Volume 37(2015:Jun.)
• Page Start: 24
• Page End: 37
• Publication Date: 2015-06
• Subjects: CO2 geologic storage -- Permeability -- Heterogeneity -- Bayesian -- Interference test; Greenhouse gases -- Environmental aspects -- Periodicals; Air -- Purification -- Technological innovations -- Periodicals; Gaz à effet de serre -- Périodiques; Gaz à effet de serre -- Réduction -- Périodiques; Air -- Purification -- Technological innovations; Greenhouse gases -- Environmental aspects; Periodicals; 363.73874605
• DOI: 10.1016/j.ijggc.2015.03.004
• Languages: English
• ISSNs: 1750-5836

Abstract

Highlights: Unknown permeability heterogeneity increases the risk of a CO2 storage operation. We use point measurements and Bayesian reasoning to constrain heterogeneity. Risk quantified by 30-year prediction envelopes from multiple model realizations. Interference tests provide weights for realizations; improves predictions. Abstract: Spatial heterogeneity and variability across many orders of magnitude are two properties of formation permeability that are challenging to effectively capture in subsurface flow models. With regard to geological CO2 storage, heterogeneity affects storage capacity, plume migration, pressure build-up around injection wells and, if utilized, the possibility of early breakthrough at brine extraction wells. Faced with under-characterized heterogeneity and an information-poor environment, the challenge is to make as much use as possible of the available data in reducing uncertainty associated with model prediction of a CO2 injection operation. The two types of data used here to inform models are point permeability measurements from each well and interference tests between wells; these are both obtained from a synthetic permeability distribution approximating a hypothetical CO2 storage formation. These data are used to reduce uncertainty in predictions of CO2 injection, brine and CO2 production rates, and CO2 breakthrough times obtained from simulations of five-spot CO2 injection/brine production performed on >600 conditional permeability realizations. First, assuming the underlying permeability field exhibits long-range correlation and a log-normal permeability distribution, a Bayesian analysis was undertaken using the point permeability measurements to reduce the likely magnitude of permeability heterogeneity. Comparison of realizations drawn from the prior and posterior indicate that the data were sufficient to exclude extreme scenarios with very rapid or very slow CO2 transport and breakthrough at brine production wells. Thirty-year prediction envelopes for net CO2 retention, brine and CO2 production were reduced by 40, 45 and 72%, respectively. In the second stage, simulated interference tests for each of the posterior realizations were compared against interference tests simulated for the synthetic "true" permeability field. Weighting functions derived from these comparisons are used to further refine predictions, providing additional reductions of uncertainty by 38 and 69% for brine and CO2 production rates, respectively. Predictions of CO2 breakthrough are especially sensitive to analysis of interference tests, with a good estimate of the correct time obtained in three out of four cases.