公开(公告)号：US11768982B1

公开(公告)日：2023-09-26

申请号：US18116877

申请日：2023-03-03

Applicant: Chengdu University of Technology

Inventor： Jun Li ,  Zhengwei Xu ,  Xuben Wang ,  Rui Wang ,  Shengxian Liang

IPC: G06F30/27 ,  G06F111/04

CPC classification number: G06F30/27 ,  G06F2111/04

Abstract: Disclosed are a hybrid density abrupt interface inversion method based on machine learning constraints. The inversion method includes constructing an initial basin interface and randomly generating a disturbed basin interface data set; obtaining a basin interface data set through Hadamard product operation on the initial basin interface and the disturbed basin interface data set; obtaining a high-resolution density interface model data set through filling the basin interface data set with advanced functions; performing forward calculation to obtain a simulated gravity data set; carrying out mathematical transformation on the simulated gravity data set and weighting to obtain a low-resolution migration density interface model data set; optimizing a migration model-based deep learning network and mapping to obtain a high-resolution constrained density interface prior model; and constructing a stable nonlinear loss function and performing regularization inversion to obtain a high-resolution density interface model.