3D magnetotelluric inversion with arbitrary data orientation angles

• Published in: Computers & geosciences Vol. 188; p. 105596
• Main Authors: Liu, Zhongyin, Kelbert, Anna, Chen, Xiaobin
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.06.2024
• Subjects: 3D inversion; algorithms; computer software; Data functional; data quality; instrumentation; Jacobian matrix; magnetism; Magnetotellurics; surveys; Tensor rotation; Magnetotellurics; Data functional; Jacobian matrix; Tensor rotation; 3D inversion
• DOI: 10.1016/j.cageo.2024.105596
• ISSN: 0098-3004

The survey setup of 3D magnetotelluric inversion is typically chosen to best reflect the underlying geological structure. Typically, the individual observation azimuths are distinct from this preferred survey layout orientation; in fact, measured electric and magnetic fields are aligned with local geomagnetic North. When that happens, either data preprocessing (rotation) is required before the inversion may be performed, or the orientation of the modeling grid is aligned with the data orientations. None of these approaches is optimal, possibly resulting in a reduction of data quality, the loss of statistical accuracy of the error estimates, or in unnecessary grid cells, resulting in increased computation times. In situations when the data quality may be improved by allowing distinct individual site orientations, such as when cultural noise or faulty instrumentation cause a degradation of one of the modes, data loss due to rotation is especially detrimental. In this paper, we present a modified 3D magnetotelluric inversion algorithm, based on the ModEM software, that allows for direct interpretation of observations with arbitrary data orientation angles (ModEM ADORA). In ModEM ADORA, the modeling responses are rotated to the observation orientation angles after each forward calculation and before the data misfit is evaluated. This allows for direct interpretation of observation data with distinct orientations at each site and (as needed for some historical data) at each frequency. The derivative of the penalty functional is computed by pre-multiplying the derivatives of the data functionals (or the complete Jacobian matrix) by the relevant sparse block-diagonal rotation operators. We describe the principle and implementation of ModEM ADORA, and provide a collection of synthetic and real data tests for validation and an analysis of effectiveness of the ADORA option of ModEM. We show that by decoupling modeling grid and sensor orientations, ModEM ADORA supports both computational efficiency and ease of use, as well as allows for the maximum quality and quantity of inverted data. •Modeling and observation coordinate systems can now be set arbitrarily for 3D magnetotelluric inversion.•More high-quality data can be incorporated into inversion by choosing optimal data orientation.•Solve for fewer inversion model parameters by rotating the modeling coordinate system to site distribution.•Free for academic use.