Reservoir Lithology Classification by the Hidden Markov Model

Runhai Feng, Stefan Luthi, Dries Gisolf

Research output: Chapter in Book/Conference proceedings/Edited volumeConference contributionScientific

1 Citation (Scopus)

Abstract

Hidden Markov Model has been applied to predict the reservoir lithologies by using seismic inversion results as inputs. This method can take the conditional probability between different states or lithologies into account which is the vertical correlation in geology. In order to consider the misfit between the inversion results and the true well-logging data, the model needs to be trained. The application on a field example is quite successful in which most of lithologies have been predicted correctly even for some thin layers. However, this method is only 1D which means that the lateral continuity has not been considered yet.
Original languageEnglish
Title of host publication4th EAGE Exploration Workshop 2017
Subtitle of host publication2-4 May 2017, Muscat, Oman
Number of pages5
DOIs
Publication statusPublished - 2017
Event4th EAGE Exploration Workshop 2017 - Muscat, Oman
Duration: 2 May 20174 May 2017
Conference number: 4
https://events.eage.org/en/2017/fourth-eage-exploration-workshop

Workshop

Workshop4th EAGE Exploration Workshop 2017
CountryOman
CityMuscat
Period2/05/174/05/17
Internet address

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