- journal_title：Geophysics
- Contributor：Christopher Power ; Jason I. Gerhard ; Panagiotis Tsourlos ; Antonios Giannopoulos
- Publisher：Society of Exploration Geophysicists
- Date：2013-07-01
- Format：text/html
- Language：en
- Identifier：10.1190/geo2012-0395.1
- journal_abbrev：Geophysics
- issn：0016-8033
- volume：78
- issue：4
- firstpage：EN1
- section：Engineering and Environmental Geophysics
Electrical resistivity tomography (ERT) has, for a considerable length of time, been considered promising for subsurface characterization activities at sites contaminated with dense, nonaqueous phase liquids (DNAPLs). The relatively few field studies available exhibit mixed results, and the technique has not yet become a common tool for mapping such contaminants or tracking mass reduction during their remediation. To help address this, a novel, coupled DNAPL-ERT numerical model was developed that can provide a platform for the systematic evaluation of ERT under a wide range of realistic, field-scale subsurface environments. The coupled model integrated a 3D multiphase flow model, which generates realistic DNAPL scenarios, with a 3D ERT forward model to calculate the corresponding resistivity response. Central to the coupling, and a key contribution, was a new linkage between the main hydrogeologic parameters (including hydraulic permeability, porosity, clay content, groundwater salinity and temperature, and air, water, and DNAPL contents evolving with time) and the resulting bulk electrical resistivity by integration of a variety of published relationships. Sensitivity studies conducted for a single node compared well to published correlations and for a field-scale domain demonstrated that the model is robust and sensitive to heterogeneity in DNAPL distribution and soil structure. A field-scale simulation of a DNAPL release and its subsequent remediation, monitored by ERT surface surveys, demonstrated that ERT is promising for mapping DNAPL mass reduction. The developed model provides a cost-effective avenue to test optimum ERT data acquisition, inversion, and interpretative tools, which should assist in deploying ERT strategically at contaminated sites.