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Parameter optimization of gravity density inversion based on correlation searching and the golden section algorithm |
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| Authors: | Lu-Ping Sun Zhan Liu Hao Shou Yu-Hua Zhang |
| Institution: | 1. School of Geophysics and Information Technology, China University of Geosciences, Beijing, 100083, China 2. Key Laboratory of Geo-detection, Ministry of Education, Beijing, 100083, China 3. School of Geosciences, China University of Petroleum, Qingdao, 266555, China 4. Research Institute of Petroleum Exploration and Development, CNPC, Beijing, 100083, China 5. Research Institute, CNOOC, Beijing, 100027, China |
| Abstract: | For density inversion of gravity anomaly data, once the inversion method is determined, the main factors affecting the inversion result are the inversion parameters and subdivision scheme. A set of reasonable inversion parameters and subdivision scheme can, not only improve the inversion process efficiency, but also ensure inversion result accuracy. The gravity inversion method based on correlation searching and the golden section algorithm is an effective potential field inversion method. It can be used to invert 2D and 3D physical properties with potential data observed on flat or rough surfaces. In this paper, we introduce in detail the density inversion principles based on correlation searching and the golden section algorithm. Considering that the gold section algorithm is not globally optimized, we present a heuristic method to ensure the inversion result is globally optimized. With a series of model tests, we systematically compare and analyze the inversion result efficiency and accuracy with different parameters. Based on the model test results, we conclude the selection principles for each inversion parameter with which the inversion accuracy can be obviously improved. |
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