Automatic Interpretation of Potential Field Data Based on Euler Deconvolution with Linear Background

Author:

Liu Qiang1,Shu Qing1,Gao Wei1,Luo Yao1,Li Zelin2,Yang Junjun1ORCID,Xu Wenqiang3

Affiliation:

1. China Aero Geophysical Survey and Remote Sensing Center for Natural Resources, Beijing 100083, China

2. Key Laboratory for Resource Exploration Research of Hebei Province, School of Earth Science and Engineering, Hebei University of Engineering, Handan 056038, China

3. School of Geophysics and Information Technology, China University of Geosciences (Beijing), Beijing 100083, China

Abstract

Euler deconvolution is a popular technique used for analyzing potential field data because it requires little prior information. However, the reliability of Euler solutions can be impacted by interference from adjacent field sources, or background fields. In this manuscript, we present an effective Euler deconvolution algorithm that accounts for linear background fields. Our algorithm, called improved finite-difference Euler deconvolution, builds upon the finite-difference method and is less susceptible to interference from nearby sources. We use this algorithm to achieve a joint estimation of the coefficients of the source coordinates, the structure index, and the linear background trend. Compared to Euler deconvolution methods based on differential similarity transformations, which also account for linear background fields, our method is easier to understand and implement programmatically and is faster. We tested our method using both 2D and 3D synthetic data, and the results indicate that our algorithm has better computational accuracy than the finite-difference algorithm and is comparable to the Euler deconvolution algorithm based on differential similarity transformations. In addition, our method was shown to be effective when tested on real data.

Funder

National Natural Science Foundation of China

Natural Science Foundation of Hebei Province

Geological Survey Project of China

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

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