Density abrupt interface inversion method and system based on machine learning constraints
US11768982B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Mar 3, 2023 |
| Grant date | Sep 26, 2023 |
| Priority date | — |
| Expiry date | Mar 3, 2043 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06F2111/04
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
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.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.