Exploring for Offshore Freshened Groundwater: Integrated Geophysical Field Studies

Offshore freshened groundwater (OFG) may become increasingly of interest, particularly in densely populated coastal regions and on islands. The only physical parameter that changes with seafloor pore water salinity is the subsurface electrical resistivity. Therefore, marine electromagnetic measurements are the only techniques that can be used to explore OFGs. However, due to the diffusive nature of the electromagnetic fields, there is always a whole set of electrical resistivity models that may fit the measured data. Conventional deterministic inversion methods derive a single best-fit model and do not capture the associated uncertainties in the resistivity model. This in turn may lead to misinterpretations about the probability of OFG occurrence, volume estimates, and potential connection to land aquifers. This study employs a trans-dimensional Markov- Chain Monte-Carlo (MCMC) inversion workflow on time-domain controlled source electromagnetic (CSEM) data from Canterbury Bight to estimate uncertainties in electrical resistivity models. By integrating probability density distributions of resistivity with interpreted seismic sections, we derive pore-water salinity probability distributions, enabling us to estimate salinity uncertainties. Our results reveal an OFG body in the center of the study area within silt and fine-sand sediments, suggesting a connection to onshore groundwater. This study demonstrates the effectiveness of using Bayesian inversion on CSEM data to estimate pore-water salinity values and their associated uncertainties.

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Published
2024-09-23
DOI
https://doi.org/10.1109/oceans55160.2024.10754589
Primary Topic
Hydrocarbon exploration and reservoir analysis
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article
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article

Exploring for Offshore Freshened Groundwater: Integrated Geophysical Field Studies

Aaron Micallef, Christian Berndt, Jan Dettmer, Bradley A. Weymer et al.
Hydrocarbon exploration and reservoir analysis
article

Exploring for Offshore Freshened Groundwater: Integrated Geophysical Field Studies

Aaron Micallef, Christian Berndt, Jan Dettmer, Bradley A. Weymer, Romina Gehrmann, Amir Haroon, Joshu J. Mountjoy, Zahra Faghih, Katrin Schwalenberg, Marion Jegen
article en

Abstract

Offshore freshened groundwater (OFG) may become increasingly of interest, particularly in densely populated coastal regions and on islands. The only physical parameter that changes with seafloor pore water salinity is the subsurface electrical resistivity. Therefore, marine electromagnetic measurements are the only techniques that can be used to explore OFGs. However, due to the diffusive nature of the electromagnetic fields, there is always a whole set of electrical resistivity models that may fit the measured data. Conventional deterministic inversion methods derive a single best-fit model and do not capture the associated uncertainties in the resistivity model. This in turn may lead to misinterpretations about the probability of OFG occurrence, volume estimates, and potential connection to land aquifers. This study employs a trans-dimensional Markov- Chain Monte-Carlo (MCMC) inversion workflow on time-domain controlled source electromagnetic (CSEM) data from Canterbury Bight to estimate uncertainties in electrical resistivity models. By integrating probability density distributions of resistivity with interpreted seismic sections, we derive pore-water salinity probability distributions, enabling us to estimate salinity uncertainties. Our results reveal an OFG body in the center of the study area within silt and fine-sand sediments, suggesting a connection to onshore groundwater. This study demonstrates the effectiveness of using Bayesian inversion on CSEM data to estimate pore-water salinity values and their associated uncertainties.

University of Hawaiʻi at Mānoa (US), Dalhousie University (CA), Federal Institute for Geosciences and Natural Resources (DE), Monterey Bay Aquarium Research Institute (US), University of Calgary (CA), Shanghai Jiao Tong University (CN), GEOMAR Helmholtz Centre for Ocean Research Kiel (DE), National Institute of Water and Atmospheric Research (NZ)
Openalex Percentile: Top 77%
Hydrocarbon exploration and reservoir analysis
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