Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data
This report summarizes the results of three-dimensional (3-D) resistivity inversion simulations that were performed to account for local 3-D distortion of the electric field in the presence of 3-D regional structure, without any a priori information on the actual 3-D distribution of the known subsurface geology. The methodology used a 3-D geologic model to create a 3-D resistivity forward (“known”) model that depicted the subsurface resistivity structure expected for the input geologic configuration. The calculated magnetotelluric response of the modeled resistivity structure was assumed to represent observed magnetotelluric data and was subsequently used as input into a 3-D resistivity inverse model that used an iterative 3-D algorithm to estimate 3-D distortions without any a priori geologic information. A publicly available inversion code, WSINV3DMT, was used for all of the simulated inversions, initially using the default parameters, and subsequently using adjusted inversion parameters. A semiautomatic approach of accounting for the static shift using various selections of the highest frequencies and initial models was also tested. The resulting 3-D resistivity inversion simulation was compared to the “known” model and the results evaluated. The inversion approach that produced the lowest misfit to the various local 3-D distortions was an inversion that employed an initial model volume resistivity that was nearest to the maximum resistivities in the near-surface layer.
Citation Information
Publication Year | 2017 |
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Title | Semiautomatic approaches to account for 3-D distortion of the electric field from local, near-surface structures in 3-D resistivity inversions of 3-D regional magnetotelluric data |
DOI | 10.3133/ofr20171007 |
Authors | Brian D. Rodriguez |
Publication Type | Report |
Publication Subtype | USGS Numbered Series |
Series Title | Open-File Report |
Series Number | 2017-1007 |
Index ID | ofr20171007 |
Record Source | USGS Publications Warehouse |
USGS Organization | Crustal Geophysics and Geochemistry Science Center |