Application of a serial denoising autoencoder for geological plausibility of a channelized reservoir in history matching

S. Kim, B. Min, J. Choe

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

1 Scopus citations

Abstract

Denoising autoencoder (DAE) is utilized to preserve and improve geological reality and plausibility in a channelized reservoir model during history matching by ensemble smoother with multiple data assimilation (ES-MDA). As one of history matching methods, ES-MDA calibrates reservoir properties such as rock facies corresponding to production history. While ES-MDA modifies reservoir parameters, it recognizes them only as figures not honoring to geological features. Thus, conservation of geological characteristics during calibration of reservoir parameters is challenging in ES-MDA. DAE is trained to restore lost connectivity and pattern of an original geological concept and it is applied to posterior reservoir models after an assimilation by ES-MDA. ES-MDA combined with DAE shows not only geologically enhanced channel models but also well-matched production prediction.

Original languageEnglish
Title of host publication4th EAGE Conference on Petroleum Geostatistics
PublisherEuropean Association of Geoscientists and Engineers, EAGE
ISBN (Electronic)9789462822962
DOIs
StatePublished - 2019
Event4th EAGE Conference on Petroleum Geostatistics - Florence, Italy
Duration: 2 Sep 20196 Sep 2019

Publication series

Name4th EAGE Conference on Petroleum Geostatistics

Conference

Conference4th EAGE Conference on Petroleum Geostatistics
Country/TerritoryItaly
CityFlorence
Period2/09/196/09/19

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