This is a Preprint and has not been peer reviewed. The published version of this Preprint is available: https://doi.org/10.1016/bs.agph.2021.06.001. This is version 1 of this Preprint.
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Abstract
Quantitative characterization of subsurface properties is critical for many environmental applications and serves as the basis to simulate and better understand dynamic subsurface processes. Geophysical imaging methods allow to image subsurface property distributions and monitor their spatio-temporal changes in a minimally invasive manner. While it is widely agreed upon that models integrating multiple independent data sources are more reliable, the number of approaches to do so is increasing rapidly and often overwhelming for researchers and, particularly, novices to the field.
With this work, we aim to contribute to the development multimethod imaging through (1) an overview of, and didactic introduction to, existing inversion approaches for the integration of multiple geophysical data sets with other measurement types (e.g., hydrological observations), petrophysical models, and process simulations, (2) a state-of-the-art review on the use and potentials of these approaches in various environmental applications, and (3) a discussion on new frontiers and remaining challenges in the field.
We hope that this chapter provides an entry point to recent developments in multimethod geophysical imaging, clarifies similarities, differences, and development potentials of existing approaches, and ultimately helps practitioners to choose the optimum one to integrate their data sets.
DOI
https://doi.org/10.31223/X5HP67
Subjects
Earth Sciences, Geophysics and Seismology, Physical Sciences and Mathematics
Keywords
Environmental geophysics, Geophysical tomography, Multimethod imaging, Coupled inversion
Dates
Published: 2021-08-30 06:21
Last Updated: 2021-08-30 13:21
License
CC BY Attribution 4.0 International
Additional Metadata
Conflict of interest statement:
None.
Data Availability (Reason not available):
Review article with no original data
There are no comments or no comments have been made public for this article.