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4D ERT-based calibration and prediction of biostimulant-induced changes in fluid conductivity

T.C. Johnson (timothy.johnson@inl.gov)
Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-2107, United States

R.J. Versteeg (roelof.versteeg@inl.gov)
Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-2107, United States

F.D. Day-Lewis (daylewis@usgs.gov)
U.S. Geological Survey Branch of Geophysics, 11 Sherman Place, Unit 5015 University of Connecticut, Storrs Mansfield, CT 06269, United States

W.R. Major (william.major@navy.mil)
Naval Facilities Engineering Service Center, 00000, Port Hueneme, CA 00000, United States

K.E. Wright (Karen.Wright@inl.gov)
Idaho National Laboratory, P.O. Box 1625, Idaho Falls, ID 83415-2107, United States

Abstract

In-situ bioremediation is an emerging and cost-effective method of removing organic contaminants from groundwater. The performance of bioremedial systems depends on the adequate delivery and distribution of biostimulants to contaminated zones. Monitoring the distribution of biostimulants using monitoring wells is expensive, time consuming, and provides inadequate information between sampling wells. We discuss a Hydrogeophysical Performance Monitoring System (HPMS) deployed to monitor bioremediation efforts at a TCE-contaminated Superfund site in Brandywine MD. The HPMS enables autonomous electrical geophysical data acquisition, processing, quality-assurance/quality-control, and inversion. Our objective is to demonstrate the feasibility and cost effectiveness of the HPMS to provide near real-time information on the spatiotemporal behavior of injected biostimulants. As a first step, we use time-lapse electrical resistivity tomography (ERT) to estimate changes in bulk conductivity caused by the injectate. We demonstrate how ERT-based bulk conductivity estimates can be calibrated with a small number of fluid conductivity measurements to produce ERT-based estimates of fluid conductivity. The calibration procedure addresses the spatially variable resolution of the ERT tomograms. To test the validity of these estimates, we used the ERT results to predict the fluid conductivity at tens of points prior to field sampling of fluid conductivity at the same points. The comparison of ERT-predicted vs. observed fluid conductivity displays a high degree of correlation (correlation coefficient over 0.8), and demonstrates the ability of the HPMS to estimate the four-dimensional (4D) distribution of fluid conductivity caused by the biostimulant injection.


Final copy as submitted to American Geophysical Union for publication as: Johnson, T.C., Versteeg, R.J., Day-Lewis, F.D., Major, W.R., and Wright, K.E., 2008, 4D ERT-based calibration and prediction of biostimulant-induced changes in fluid conductivity [abs.]: EOS Transactions, American Geophysical Union, v. 89, no. 53, Fall Meeting Supplement, abstract H42D-07.

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