Abstract

Mathematical simulation plays a vital role in the analysis of electromagnetic vibration spectrum field response. This article realizes a three-dimensional adaptive vector finite meta-acting algorithm of controlled source electromagnetic vibration spectrum (CSEM) field to address 3D meshing for the simulation of terrain fluctuations and complex electrical anomalies. The adaptive methods utilized in this article is employed for one-time field and secondary field separation in order to calculate electromagnetic vibration spectrum field response. This response can effectively solve the source singularity in finite meta-simulation and improves the numerical accuracy of electromagnetic vibration spectrum field near the field source. The two approaches analysed in this article are CSEM one-dimensional positive algorithm and finite meta-method. The adaptive mesh refinement algorithm based on post-test error estimation is used in this paper to guide the mesh refinement to reduce man-made errors caused by designing a grid. The validity of the proposed algorithm is verified through numerical simulation of one-dimensional and three-dimensional models. The outcomes obtained reveals that the finite solution of one-dimensional model coincides well with the analytical solution. The relative error of electromagnetic vibration spectrum field amplitude is about 1 %, and the overall phase difference of less than 1 degree is observed. It is analysed that the three-dimensional model finite solution also fits well with the finite volume solution and the controlled source electromagnetic vibration spectrum response with three-dimensional tilt plate abnormality is simulated. This experimental analysis shows the ability and effectiveness of the algorithm to simulate the electromagnetic vibration spectrum field of complex geoelectrical structure.

Highlights

  • In the exploration of ground electromagnetic vibration spectrum method, controllable source audio geomagneance method (CSAMT) plays an important role in the survey and exploration of petroleum, geothermal, metal mineral, hydration, environment and so on

  • An adaptive vector finite element algorithm is used to realize the CSEM3D forward simulation and the primary/secondary field separation algorithms are utilized for the calculation of the electromagnetic vibration spectrum field response

  • For the vertical electromagnetic vibration spectrum field component, when the transmission distance is small, the relative amplitude error is less than 1 %, and the phase difference is 1° when the transmission distance is greater than 5 km, the relative error of the amplitude is relatively large, and the maximum phase difference of the components is 1.4°

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Summary

Introduction

In the exploration of ground electromagnetic vibration spectrum method, controllable source audio geomagneance method (CSAMT) plays an important role in the survey and exploration of petroleum, geothermal, metal mineral, hydration, environment and so on. Great progress has been made in the study of the three-dimensional forwarding method of controllable source electromagnetic vibration spectrum field, and many equations based on integral equations have been proposed. Most of these algorithms are implemented on the structural grid, but the structural grid cannot accurately simulate complex geological structures such as terrain fluctuations and tilt interfaces, and the non-structural mesh finite meta-method is more suitable for simulating these complex geo-electronic models, and the completely non-structural mesh can realistically simulate complex geological structures such as terrain ups and downs and tilt interfaces, especially non-structural [4, 5]. The 3D meshing for the simulation of terrain fluctuations and complex electrical anomalies is addressed in this article by proposing a three-dimensional adaptive vector finite meta-acting algorithm of controlled source electromagnetic vibration spectrum (CSEM) field.

Governing equation
Finite element analysis
Adaptive mesh refinement algorithm based on posterior error estimation
One-dimensional oil and gas model
Three-dimensional oil and gas model
Three-dimensional tilt anomaly model
Findings
Conclusions
Full Text
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