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- W2022258458 abstract "Electrical Resistivity Tomography (ERT), which has seen increasingly wide use for environmental monitoring, uses the measurement of electrical potentials induced by a low-frequency electric current source. An alternative technique, magnetometric resistivity (MMR), measures the magnetic fields created by the same type of low-frequency electric current source used for ERT. Combining these two methods and thus the two types of data, provides an opportunity for producing improved subsurface images in a wider range of environments. This paper discusses the use of a fully three-dimensional inverse routine that combines magnetic and electric field measurements. The algorithm is based on a 3-D finite difference forward algorithm. The magnetic fields are modeled by applying the reciprocity theorem to model the electric fields induced by a coil of unit moment at a frequency of one radian per second. Using this method, allows for an adjoint formulation for calculating sensitivities of both magnetic and electric fields with respect to changes in the conductivities of individual cells within the finite-difference mesh. In initial model studies, combined MMR∕ERT surveys were better able to resolve 3-D structures than ERT alone. The paper also considers design issues and choices of arrays for MMR surveys over a simple 3-D model. In this case, an integral-equation modeling algorithm is used to calculate the expected magnetic fields over a simple 3-D model. Several horizontal and buried vertical electric sources with surface magnetic receivers are employed. This work suggests that in-well horizontal arrays produce the strongest anomalous signals, while vertical dipoles provide the best sensitivity to target location." @default.
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- W2022258458 date "2003-12-01" @default.
- W2022258458 modified "2023-10-14" @default.
- W2022258458 title "Combined Electrical and Magnetic Resistivity Tomography: Synthetic Model Study and Inverse Modeling" @default.
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- W2022258458 doi "https://doi.org/10.4133/jeeg8.4.251" @default.
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