TOWARD MINIMALLY INVASIVE PERFORMANCE MONITORING: APPLICATIONS OF TIME-LAPSE GEOPHYSICAL IMAGING TO AQUIFER STORAGE AND RECOVERY AND ENGINEERED REMEDIATION

Geophysical monitoring has potential to enable more robust and cost-effective aquifer management and remediation. Time-lapse geophysical approaches, such as electrical-resistivity tomography, can provide site operation managers with near real-time information about the spatial distribution of injected fluids, remedial amendments, and water quality. We provide an overview of two field experiments involving application of time-lapse geophysical methods to monitor (1) aquifer storage and recovery (ASR); and (2) biostimulation with emulsified vegetable oil. Case studies from an ASR pilot-scale experiment in Charleston, South Carolina, and a biostimulation experiment in Fridley, Minnesota demonstrate that geophysical methods provide valuable insight into mass transport at the site-scale; however, our experience also indicates that site managers and decision makers prefer summary performance indicators to more complex geophysical results, the interpretation of which commonly requires an understanding of image resolution and measurement sensitivity. Translating geophysical results into relevant performance indicators remains an important challenge for realizing the full potential of near-surface geophysics for performance monitoring. Toward this end, we investigate alternative approaches to conventional inversion of geophysical data: (1) moment-based inversion (MBI); and (2) object-based inversion (OBI). For time-lapse imaging of transport processes, MBI yields estimates of plume moments (e.g., total mass, center of mass, spread, etc.), providing direct insight into advection, dispersion, and mass transfer. OBI parameterization is guided by geologic and hydrologic insight into the target, e.g., a layered block model describing the shape of an amendment plume injected into stratified media. The MBI and OBI inversion methods reduce inversion artifacts, simplify interpretive complexity, and translate geophysical data into actionable information by estimating parameters of direct interest to engineers and hydrologists.