公开(公告)号：US20240192646A1

公开(公告)日：2024-06-13

申请号：US18555098

申请日：2022-02-03

Applicant: ExxonMobil Technology and Engineering Company

Inventor： Sriram DORAISWAMY ,  Jai MANIK ,  Fahim FOROUZANFAR ,  Kyle GUICE ,  Xiaohui WU

IPC: G05B13/02

CPC classification number: G05B13/0265

Abstract: Methods for analyzing subsurface process data in order to perform one or more subsurface operations in a subsurface are provided. Generating subsurface models is typically a long and laborious process in which subsurface process data is analyzed in order to generate the subsurface models. In contrast, work in generating the subsurface models may be front-loaded by first using a physics simulator in order to generate a training set of subsurface forward models, and then performing machine learning using the training set to generate one or more proxy models, such as a forward proxy model and an inverse proxy model. The machine learning may be constrained using physics-based rules to better converge on the proxy models. In this way, the already-trained inverse proxy model may input the subsurface process data in order to generate potential inverse models, which may then be used to perform subsurface operations in the subsurface.