Quantifying incremental value in mature fields using unconventional high resolution modelling workflows, supported by field analogues from Myanmar

M. Bentley

doi:10.3997/2214-4609.201977087

Quantifying incremental value in mature fields using unconventional high resolution modelling workflows, supported by field analogues from Myanmar

M. Bentley^*

^*Corresponding author for this work

Research output: Contribution to conference › Paper › peer-review

Abstract

Decision-making in mature fields requires us to adjust our workflows. Modelling for understanding ('truth models') is advocated as an alternative to full-field history matching exercises and aligns neatly with the current interest in Machine Learning. Examples from modelling analogues will be shown and application to Central Myanmar, a region with many mature fields with remaining locked-in value, will be discussed.

Original language	English
DOIs	https://doi.org/10.3997/2214-4609.201977087
Publication status	Published - 2019
Event	2nd EAGE-VPI Conference on Reservoir Geoscience 2019 - Hanoi, Viet Nam Duration: 2 Dec 2019 → 3 Dec 2019

Conference

Conference	2nd EAGE-VPI Conference on Reservoir Geoscience 2019
Abbreviated title	RESGEO 2019
Country/Territory	Viet Nam
City	Hanoi
Period	2/12/19 → 3/12/19

ASJC Scopus subject areas

Geochemistry and Petrology
Geology

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10.3997/2214-4609.201977087

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title = "Quantifying incremental value in mature fields using unconventional high resolution modelling workflows, supported by field analogues from Myanmar",

abstract = "Decision-making in mature fields requires us to adjust our workflows. Modelling for understanding ('truth models') is advocated as an alternative to full-field history matching exercises and aligns neatly with the current interest in Machine Learning. Examples from modelling analogues will be shown and application to Central Myanmar, a region with many mature fields with remaining locked-in value, will be discussed.",

author = "M. Bentley",

note = "Publisher Copyright: {\textcopyright} EAGE 2019.; 2nd EAGE-VPI Conference on Reservoir Geoscience 2019, RESGEO 2019 ; Conference date: 02-12-2019 Through 03-12-2019",

year = "2019",

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AB - Decision-making in mature fields requires us to adjust our workflows. Modelling for understanding ('truth models') is advocated as an alternative to full-field history matching exercises and aligns neatly with the current interest in Machine Learning. Examples from modelling analogues will be shown and application to Central Myanmar, a region with many mature fields with remaining locked-in value, will be discussed.

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U2 - 10.3997/2214-4609.201977087

DO - 10.3997/2214-4609.201977087

M3 - Paper

AN - SCOPUS:85093871430

T2 - 2nd EAGE-VPI Conference on Reservoir Geoscience 2019

Y2 - 2 December 2019 through 3 December 2019

ER -

Quantifying incremental value in mature fields using unconventional high resolution modelling workflows, supported by field analogues from Myanmar

Abstract

Conference

ASJC Scopus subject areas

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