Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
10121022 | Journal of Applied Geophysics | 2018 | 23 Pages |
Abstract
One of the key issues in three-dimensional (3D) potential field data inversion is computational efficiency. We have developed an efficient 3D potential field data inversion method using fast proximal objective function (FPOF) optimization algorithm. A distinguishing feature of the proposed inversion method is to calculate each unknown element in the model space independently at each iteration. In addition, based on subsequent data misfits in the iterative process, we design a computationally efficient method to choose an appropriate regularization parameter. We take gravity data inversion as an example and apply the proposed inversion method to synthetic data contaminated with noise. The results demonstrate that the proposed method provides almost identical results as the conventional conjugate gradient (CG) method, however, with a significant reduction in the execution time. Lastly, an application on real field data acquired in the Western China is carried out, yielding a 3D density model which is in good agreement with the available geological knowledge.
Keywords
Related Topics
Physical Sciences and Engineering
Earth and Planetary Sciences
Geophysics
Authors
Guomin Peng, Zhan Liu, Kaijun Xu, Yongliang Bai, Runlin Du,