Reduced order reservoir simulation with neural-network based hybrid model

Pavel Temirchev, Anna Gubanova, Ruslan Kostoev, Anton Gryzlov, Dmitry Voloskov, Dmitry Koroteev, Maxim Simonov, Alexey Akhmetov, Andrey Margarit, Alexander Ershov

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

This paper considers the development of a computationally fast model for simulation of multiphase flow in porous media for a heterogeneous reservoir with the unlimited number of wells characterized by a different type of completion. This fast solution has been obtained by means of replacing the differential equation governing the flow in porous media by approximate governing equations which are parametrized by convolutional neural networks. The matching of the dynamic properties of the original and reduced models is ensured by conservation of spatial invariance property of the equations. The suggested approach is characterized by the minimal number of limitations and shortcomings related to geological-hydrodynamical structure and size of the original model. Also, there is no necessity of additional model training for reservoirs not included in a training dataset. Suggested approach has been evaluated on the synthetic benchmark test model SPE10, where a significant decrease in computational time has been demonstrated comparing to a traditional commercial reservoir simulator. Based on the results of all demonstrated test case scenarios, it could be noted that hybrid hydrodynamic modeling leads to a significant reduction in computational cost (by a factor of few hundreds), maintaining at the same time required accuracy of calculations.

Original languageEnglish
Title of host publicationSociety of Petroleum Engineers - SPE Russian Petroleum Technology Conference 2019, RPTC 2019
PublisherSociety of Petroleum Engineers
ISBN (Electronic)9781613996928
DOIs
Publication statusPublished - 2019
EventSPE Russian Petroleum Technology Conference 2019, RPTC 2019 - Moscow, Russian Federation
Duration: 22 Oct 201924 Oct 2019

Publication series

NameSociety of Petroleum Engineers - SPE Russian Petroleum Technology Conference 2019, RPTC 2019

Conference

ConferenceSPE Russian Petroleum Technology Conference 2019, RPTC 2019
Country/TerritoryRussian Federation
CityMoscow
Period22/10/1924/10/19

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