Long Zhao

Beijing University of Posts and Telecommunications

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H. Cai

China University of Geosciences

Bin Li

The University of Tokyo

Chenglin Zhao

Beijing University of Posts and Telecommunications

Xiangyun Hu

China University of Geosciences

Xiaoning He

Qingdao Agricultural University

Yanqing Su

Harbin Institute of Technology

Xinwang Liu

Huazhong University of Science and Technology

Lina Zhao

Southeast University

Jingjie Guo

Harbin Institute of Technology

Zengguo Tian

Zhengzhou University

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Harbin Institute of Technology

Heilongjiang Institute of Technology

China University of Geosciences

Beijing University of Posts and Telecommunications

Northwestern Polytechnical University

Beijing Information Science & Technology University

Zhengzhou University

Harbin University

The University of Tokyo

Tianjin University

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Parallelized 3D Inversion for CSEM Data with Unstructured Tetrahedral Elements in Data Space

83rd EAGE Annual Conference & Exhibition (2022)

Long Zhao H. Cai Xiangyun Hu Xiaoning He Zengguo Tian

Summary We developed a parallelized 3D inversion algorithm for large-scale controlled controlled-source electromagnetic (CSEM) data in data space. We solve the forward modelling process with the finite element (FEM) method based on the unstructured tetrahedral elements, which can efficiently deal with complex geometry CSEM problems. For the inversion process, we transformed the conventional model space inversion to data space to decrease the RAM memory requirement. A synthetic CSEM land model with three anomalous bodies is applied to demonstrate the effectiveness and stableness of the developed CSEM inversion scheme. By comparing the inversion results of the conventional model space inversion method and the data space inversion method, we validated the newly proposed method is more sensitive to the low conductor. Further, the new inversion scheme requires much less memory compared to the model space inversion method, which validates the applicability of the developed inversion scheme in data space to the large-scale field CSEM data with complex geometry.

Tetrahedron

10.3997/2214-4609.202210340

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Hydrogen solubility in molten TiAl alloys

International Journal of Hydrogen Energy (2010)

Yanqing Su Xinwang Liu Liangshun Luo Long Zhao Jingjie Guo

10.1016/j.ijhydene.2010.05.054

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Citations (23)

Rain Attenuation Prediction Models of 60GHz Based on Neural Network and Least Squares-Support Vector Machine

Lecture notes in electrical engineering (2013)