公开(公告)号：US11555936B2

公开(公告)日：2023-01-17

申请号：US16738025

申请日：2020-01-09

Applicant: CGG SERVICES SAS

Inventor： Song Hou ,  Stefano Angio ,  Henning Hoeber

IPC: G06N3/04 ,  G01V1/28 ,  G01V1/30 ,  G06N3/08

Abstract: Property values inside an explored underground subsurface are determined using hybrid analytic and machine learning. A training dataset representing survey data acquired over the explored underground structure is used to obtain labels via an analytic inversion. A deep neural network model generated using the training dataset and the labels is used to predict property values corresponding to the survey data using the DNN model.