Open Access3-D Regularized focusing migration method for gravity data
Author(s) -
Yidan Ding,
Guoqing Ma,
Qingfa Meng
Publication year - 2021
Publication title -
iop conference series. earth and environmental science
Language(s) - English
Resource type - Journals
eISSN - 1755-1307
pISSN - 1755-1315
DOI - 10.1088/1755-1315/660/1/012096
Subject(s) - regularization (linguistics) , gaussian , divergence (linguistics) , computer science , seismic migration , geology , gravity model of trade , algorithm , mathematics , mathematical optimization , geophysics , artificial intelligence , physics , linguistics , philosophy , quantum mechanics , international trade , business
Potential field migration of gravity data is a kind of method using the migration concept to efficiently obtain the density distributions subsurface. To get migration imaging results with the high resolution, we propose the regularized focusing migration method that adopts the regularization theory to realize focusing migration imaging and the conjugate migration direction method to solve the optimal solution of model parameters, which effectively improves the divergence of the conventional migration imaging. Synthetic model tests demonstrate that the proposed advanced method improves the imaging resolution significantly while guaranteeing the computational efficiency, and can bring about the relatively convergent results in a random Gaussian noise environment. This method is applied to the interpretation of the gravity anomaly from Huayangchuan, Shaanxi Province, which predicts the spatial distribution of uranium deposits.