Value of information methodology for assessing the ability of electrical resistivity to detect CO2/brine leakage into a shallow aquifer

Subsurface sequestration of CO2 has uncertainties and potential consequences. Decision analysis and the value of information (VOI) can aid in (1) linking subsurface uncertainty to economic outcomes and (2) determining when additional information may be useful before making further decisions. This study uses an uncertainty quantification (UQ) evaluation of CO2 and accompanying brine leakage into a shallow aquifer via an abandoned wellbore from a deep reservoir to demonstrate both of these functions. First, we equate the range of TDS (total dissolved solids) plume results into a range of possible economic outcomes from a decision for an agricultural application of the resource, where the groundwater is used to irrigate corn crops, and therefore high saline concentrations result in economic losses. We use the concept of perfect information and these risk quantification results to identify that any information source will be only relevant when considering plumes which exceed 2000 ppm concentration. Next, we provide a physics-based methodology to calculate the reliability of electrical resistance data to detect PH/brine plumes. We simulate the electrical resistivity response for all of the leak simulations from the UQ study. This gives us the information reliability which, along with the economic outcomes, is used to calculate the value of imperfect information (VOLII). The calculated reliabilities demonstrate that electrical resistivity generally can determine the existence of a plume but it cannot perfectly determine if the plumes' concentration is >= 2000 ppm. We present VOIII measures for three different electrical resistivity field acquisitions that vary in their distance to the leaking wellbore. Published by Elsevier Ltd.