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Three-Dimensional Resistivity and Induced Polarization Data Inversion with Image Focusing

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Abstract

A maximum smoothness stabilizing functional constraint is normally used to stabilize the three-dimensional (3D) direct current (DC) resistivity and induce polarization (IP) data inversions process. These kinds of algorithms can converge stably, but the obtained solution is a smooth image, which in many practical situations does not describe the examined object properly. In this paper, we present a regularized inversion with image focusing of 3D DC resistivity and IP data. In the inversion approach, the minimum support functional constraint is incorporated into the objective functional, then the damped Gauss-Newton method is used to find the optimization of the objective function, and the preconditioned conjugate gradient algorithm is used to calculate the model updates. The model tests show that the proposed inversion approach owns good reliability and stability. The comparisons show that the program helps to generate more focused and resolved images of blocky geoelectrical structures and with better convergence than the traditional smoothing inversion approach.

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Acknowledgments

This work was supported by the National Natural Science Foundation of China (No. 41204055, 41304054, 41304055, 41104074) and the Natural Science Foundation of Jiangxi province (20161BAB211027).

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Ye, Y., Zhang, Z., Li, Z., Zhao, Y. (2017). Three-Dimensional Resistivity and Induced Polarization Data Inversion with Image Focusing. In: Di, Q., Xue, G., Xia, J. (eds) Technology and Application of Environmental and Engineering Geophysics. Springer Geophysics. Springer, Singapore. https://doi.org/10.1007/978-981-10-3244-8_13

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