Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection

Tso, Chak-Hau Michael; Johnson, Timothy C.; Song, Xuehang; Chen, Xingyuan; Kuras, Oliver; Wilkinson, Paul; Uhlemann, Sebastian; Chambers, Jonathan; Binley, Andrew

doi:10.1016/j.jconhyd.2020.103679

Title: Integrated hydrogeophysical modelling and data assimilation for geoelectrical leak detection

Journal Article · Sun Jul 05 00:00:00 EDT 2020 · Journal of Contaminant Hydrology

DOI:https://doi.org/10.1016/j.jconhyd.2020.103679· OSTI ID:1650365

Tso, Chak-Hau Michael ^[1];

^[2]; Song, Xuehang ^[2]; Chen, Xingyuan ^[2]; Kuras, Oliver ^[3]; Wilkinson, Paul ^[3]; Uhlemann, Sebastian ^[4]; Chambers, Jonathan ^[3]; Binley, Andrew ^[1]

Lancaster Univ., Bailrigg (United Kingdom)
Battelle Pacific Northwest Labs., Richland, WA (United States)
British Geological Survey, Keyworth (United Kingdom)
British Geological Survey, Keyworth (United Kingdom); Battelle Pacific Northwest Labs., Richland, WA (United States)

Time-lapse electrical resistivity tomography (ERT) measurements provide indirect observations of hydrological processes in the Earth's shallow subsurface at high spatial and temporal resolution. ERT has been used in the past decades to detect leaks and monitor the evolution of associated contaminant plumes. Specifically, inverted resistivity images allow visualization of the dynamic changes in the structure of the plume. However, existing methods do not allow the direct estimation of leak parameters (e.g. leak rate, location, etc.) and their uncertainties. We propose an ensemble-based data assimilation framework that evaluates proposed hydrological models against observed time-lapse ERT measurements without directly inverting for the resistivities. Each proposed hydrological model is run through the parallel coupled hydro-geophysical simulation code PFLOTRAN-E4D to obtain simulated ERT measurements. The ensemble of model proposals is then updated using an iterative ensemble smoother. In this paper, we demonstrate the proposed framework on synthetic and field ERT data from controlled tracer injection experiments. Our results show that the approach allows joint identification of contaminant source location, initial release time, and solute loading from the cross-borehole time-lapse ERT data, alongside with an assessment of uncertainties in these estimates. We demonstrate a reduction in site-wide uncertainty by comparing the prior and posterior plume mass discharges at a selected image plane. This framework is particularly attractive to sites that have previously undergone extensive geological investigation (e.g., nuclear sites). It is well suited to complement ERT imaging and we discuss practical issues in its application to field problems.

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Research Organization:: Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE Office of Science (SC)

Grant/Contract Number:: AC05-76RL01830; AC02-05CH11231

OSTI ID:: 1650365

Report Number(s):: PNNL-SA-152552

Journal Information:: Journal of Contaminant Hydrology, Vol. 234; ISSN 0169-7722

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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