Bayesian Inversion of Lithology and Liquid Phase Parameters From Seismic Velocity and Electrical Conductivity in the Crust and Uppermost Mantle

Abstract

To deeply understand various geodynamic processes, including volcanic activities and earthquakes, it is essential to extract detailed information about Earth materials, such as lithology and geofluid, from geophysical, petrological, and geochemical observations of Earth's interior. We developed a Bayesian probabilistic framework that can estimate the lithology and geofluid type (aqueous fluid or melt), geofluid amount (porosity), and parameters related to the fluid geometry (aspect ratio and critical fluid fraction related to connectivity) from P‐wave and S‐wave seismic velocities and electrical conductivity data obtained from geophysical tomography. By conducting synthetic inversion tests, we showed that methods based on a joint probability distribution, which simultaneously determines all parameters, sometimes fail to narrow the number of possible answers from 78 lithologies (e.g., basalt, granite, and eclogite) × two geofluid type (melt or aqueous fluid) candidate sets. This failure is derived directly from the difficult nature of inversion problems with relatively large data uncertainties. The proposed method uses a marginalization technique that first estimates lithology and geofluid type and then quantifies geofluid parameter values, which can narrow the probable lithology, geofluid type, and geofluid parameter sets in many cases. In addition, the computational cost of the proposed marginalization method is comparative to a former joint‐estimation method, which is theoretically identical to a previous heuristic method based on the least squares method. Therefore, the marginalization method is useful for geophysical data analyses that involve large amounts of observational data with relatively large uncertainties.

Adjoint-based marker-in-cell data assimilation for constraining thermal and flow processes from Lagrangian particle records

“…For problems in geodynamics, the unknown parameters are the thermal, chemical, and flow structures of the Earth's deep interior over billions of years, none of which can be observed in real time. Geophysical observations such as seismic, electromagnetic, and gravity are useful for estimating unknown parameters of the presentday crust and mantle (e.g., Iwamori et al, 2021;Kuwatani et al, 2023), but not over geologic time. Therefore, it is difficult to apply sequential data assimilation to geodynamic phenomena, except for a short time scale such as post-seismic crustal deformation (Fukuda & Johnson, 2021).…”

Design of Three-Dimensional Electrical Impedance Tomography System for Rock Samples

“…Through these electrical properties, we can understand the differences in resistivity and polarization between mineralized bodies and surrounding rocks, which serve as essential criteria for selecting appropriate geophysical exploration methods. Furthermore, the electrical parameters of rocks and ores provide an objective basis for forward calculations and inversion interpretations, as well as a physical foundation for result explanations [2]. In addition to laboratory-based investigations, the study of rocks and ores often necessitates field-based research.…”