公开(公告)号：US20240210586A1

公开(公告)日：2024-06-27

申请号：US18557715

申请日：2022-03-24

Applicant: ExxonMobil Technology and Engineering Company

Inventor： Ruichao YE

IPC: G01V1/30 ,  G01V1/34

CPC classification number: G01V1/301 ,  G01V1/345 ,  G01V2210/66

Abstract: A method and a system for a multi-task neural network for salt model building is disclosed. Imaging salt in the subsurface may be challenging because salt may be associated with strong diffraction and poor focused image, thereby making it difficult to interpret sediments underneath salt body or near salt flanks. To better image salt in the subsurface, the method and system trains, in combination, multiple aspects related to the subsurface, one of which is the target salt feature, in order to generate a salt feature model. The multiple aspects may include the target salt feature, such as the predicted salt mask, and at least one other salt feature, and one or more subsurface features, such as reconstruction of the input image and P-wave velocity. Thus, the salt model may better image salt, thereby making the seismic migration image more focused and easier to identify geological structures.