Discrete deep targets are a significant challenge for most surface-based geophysical techniques, even when considering high property contrasts. Generally, surface-based geophysical methods lose lateral and vertical resolution with depth as a result of poor measurement geometry and increased signal attenuation. The poor measurement geometry can be overcome through use of cross-borehole methods, but lateral localization is still needed for optimal borehole placement. As such, a relatively small, deep void located near the maximum depth of investigation is very unlikely to be detected. Yet, secondary features associated with these voids can be exploited for enhanced detection performance. When voids are located below the groundwater table a significant amount of dewatering and pumping is required to make them a functional passageway. This dewatering not only removes water from the void space but also the surrounding formation, resulting in a much larger, if more diffuse, secondary target: an induced groundwater table gradient. Many geophysical sensing methods are sensitive to subsurface moisture content. Here we implement a two-dimensional (2D) joint-petrophysical mixing-model, using inverted electrical resistivity tomography and inverted seismic refraction models to sense changes in the groundwater table gradient. Results are validated using depth to bedrock, groundwater-surface water information, ground-penetrating radar, and time-domain reflectometry methods. Our initial proof of concept is applied to a shallow area with a significant soil moisture gradient, through different surface soil types and bedrock. The 2D joint-petrophysical mixing-model results were used to generate an estimate of air, moisture, and matrix percent fractions in the investigation area, providing a clear delineation of the groundwater surface.

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