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The controlled source audio-frequency magnetotelluric method (CSAMT) stands out for its economic efficiency and widespread application in geophysical monitoring. However, the separate inversion of time-lapse monitoring data encounters challenges in comparing and identifying abnormal changes due to variations in data fitting. Furthermore, the utilization of a method akin to Cagniard apparent resistivity for inversion necessitates the simultaneous observation of at least two components of the electromagnetic field, making it unsuitable for extensive three-dimensional observations. This paper proposes a 3D time-lapse electric field inversion algorithm for CSAMT, addressing the complexities in geophysical monitoring. The algorithm introduces two regularization factors and defines an objective function with both temporal and spatial constraints. Synthetic testing reveals the stability of the 3D time-lapse electric field inversion algorithm, demonstrating its effectiveness in delineating underground variations. This solution resolves the challenges posed by the independent inversion of time-lapse monitoring data. [ABSTRACT FROM AUTHOR]

ZTEM refers to the Z-axis tipper electromagnetic method. The ZTEM method is an airborne magnetotelluric sounding method based on the difference in rocks' resistivity using the native electromagnetic field. The method is effective in exploring large-scale structures when the ground is fluctuant. The paper introduces the inversion algorithm of 2D ZTEM named the conjugate gradient method. This method, which avoids solving the Jacobi matrix, is very effective but not effective enough when the model is divided into a big grid. This study can perform further computation using parallel computation and then receive the processed data. We compare the results of the serial algorithm with the result of the parallel algorithm, which proves that the parallel algorithm is correct. When the number of processes is between three and six, the speedup ratio is between 1.74 and 3.19. It improves the effectiveness of the parallel algorithm of 2D ZTEM. [ABSTRACT FROM AUTHOR]

The gradient-based optimization methods are preferable for the large-scale three-dimensional (3D) magnetotelluric (MT) inverse problem. Compared with the popular nonlinear conjugate gradient (NLCG) method, however, the limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) method is less adopted. This paper aims to implement a L-BFGS-based inversion algorithm for the 3D MT problem. And we develop our code on top of the ModEM package, which is highly extensible and popular among the MT community. To accelerate the convergence speed, the preconditioning technique by the affine linear transformation of the original model parameters is used. Two modifications of the conventional L-BFGS algorithm are also made to get a comparable convergence rate with the NLCG method. The impacts of the preconditioner parameters, the regularization parameters, the starting model, etc., on the inversion are evaluated by synthetic examples for both L-BFGS and NLCG methods. And the real MT Kayabe dataset is also inverted by the inversion algorithms. The synthetic tests show that through our L-BFGS inversion algorithm the similar resistivity models can be obtained with that from the NLCG method. For the real data inversion, the L-BFGS method performs more efficiently and reasonable results could be obtained by less iterations of the inversion process than the NLCG method. Thus, we suggest the common usage of the L-BFGS method for the 3D MT inverse problem. [ABSTRACT FROM AUTHOR]

Four kinds of array of induced polarization (IP) methods (surface, borehole-surface, surface-borehole, and borehole-borehole) are widely used in resource exploration. However, due to the presence of large amounts of the sources, it will take much time to complete the inversion. In the paper, a new parallel algorithm is described which uses message passing interface (MPI) and graphics processing unit (GPU) to accelerate 3D inversion of these four methods. The forward finite differential equation is solved by ILU0 preconditioner and the conjugate gradient (CG) solver. The inverse problem is solved by nonlinear conjugate gradients (NLCG) iteration which is used to calculate one forward and two “pseudo-forward” modelings and update the direction, space, and model in turn. Because each source is independent in forward and “pseudo-forward” modelings, multiprocess modes are opened by calling MPI library. The iterative matrix solver within CULA is called in each process. Some tables and synthetic data examples illustrate that this parallel inversion algorithm is effective. Furthermore, we demonstrate that the joint inversion of surface and borehole data produces resistivity and chargeability results are superior to those obtained from inversions of individual surface data. [ABSTRACT FROM AUTHOR]

We developed a three-dimensional (3D) conjugate gradient inversion algorithm for inverting magnetotelluric impedance tensor measurements. In order to show the importance of including diagonal components of magnetotelluric impedance tensor in 3D inversion, synthetic data were inverted using the 3D conjugate gradient inversion, and the inversion results were compared and analyzed. The results from the 3D inversion of synthetic data indicate that both the off-diagonal and the diagonal components are required in inversions to obtain better inversion results when there are no enough data sites to recover the target resistivity structure. These examples show that lots of information about 3D structure is also contained in the diagonal components; as a result, diagonal components should be included in 3D inversions. The inversion algorithm was also used to invert the impedance tensor data acquired in the Kayabe area in Japan. Inversions with the synthetic and real data demonstrated the validity and practicability of the inversion algorithm. [ABSTRACT FROM AUTHOR]