- Patent Title: Methods and systems for machine-learning based simulation of flow
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Application No.: US13805649Application Date: 2011-05-19
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Publication No.: US10198535B2Publication Date: 2019-02-05
- Inventor: Adam Usadi , Dachang Li , Rossen Parashkevov , Sergey A. Terekhov , Xiaohui Wu , Yahan Yang
- Applicant: Adam Usadi , Dachang Li , Rossen Parashkevov , Sergey A. Terekhov , Xiaohui Wu , Yahan Yang
- Applicant Address: US TX Spring
- Assignee: ExxonMobil Upstream Research Company
- Current Assignee: ExxonMobil Upstream Research Company
- Current Assignee Address: US TX Spring
- Agency: ExxonMobil Upstream Research Company—Law Department
- International Application: PCT/US2011/037177 WO 20110519
- International Announcement: WO2012/015517 WO 20120202
- Main IPC: G06F17/50
- IPC: G06F17/50 ; G06N3/04

Abstract:
There is provided a method for modeling a hydrocarbon reservoir that includes generating a reservoir model comprising a plurality of sub regions. At least one of the sub regions is simulated using a training simulation to obtain a set of training parameters comprising state variables and boundary conditions of the at least one sub region. A machine learning algorithm is used to approximate, based on the set of training parameters, an inverse operator of a matrix equation that provides a solution to fluid flow through a porous media. The hydrocarbon reservoir can be simulated using the inverse operator approximated for the at least one sub region. The method also includes generating a data representation of a physical hydrocarbon reservoir can be generated in a non-transitory, computer-readable, medium based, at least in part, on the results of the simulation.
Public/Granted literature
- US20130096900A1 Methods and Systems For Machine - Learning Based Simulation of Flow Public/Granted day:2013-04-18
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