Geochemical characterization using geophysical data and Markov Chain Monte Carlo methods: A case study at the South Oyster bacterial transport site in Virginia

The study demonstrates the use of ground-penetrating radar (GPR) tomographic data for estimating sediment geochemical parameters using data collected at the Department of Energy South Oyster bacterial transport site in Virginia. By exploiting the site-specific mutual dependence of GPR attenuation and extractable Fe(II) and Fe(III) concentrations on lithofacies, we develop a statistical model in which lithofacies and Fe(II) and Fe(III) concentrations at each pixel between the boreholes are considered as random variables. The unknown variables are estimated by conditioning to the colocated GPR data and the lithofacies measurements along boreholes using a Markov Chain Monte Carlo method. Cross-validation results show that the geophysical data, constrained by lithofacies, have the potential for providing high-resolution, multidimensional information on extractable Fe(II) and Fe(III) concentrations at the South Oyster site.