Applications of neural networks in multiwell field development

A. Centilmen; T. Ertekin; A. S. Grader

doi:10.2523/56433-ms

Applications of neural networks in multiwell field development

A. Centilmen, T. Ertekin, A. S. Grader

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

97 Scopus citations

Abstract

A neuro-simulation technique that forms a bridge between an accurate reservoir simulator and a fully-trained predictive artificial neural network (ANN) is presented. Results are given that demonstrate the effectiveness of neuro-simulation to reduce computational effort and to maintain accurate predictive capabilities. Guidelines for using this technique to optimize the placement of the wells are also introduced.

Original language	English (US)
Pages	33-43
Number of pages	11
DOIs	https://doi.org/10.2523/56433-ms
State	Published - Jan 1 1999
Event	1999 SPE Annual Technical Conference and Exhibition: 'Production Operations and Engineering - General' - Houston, TX, USA Duration: Oct 3 1999 → Oct 6 1999

Other

Other	1999 SPE Annual Technical Conference and Exhibition: 'Production Operations and Engineering - General'
City	Houston, TX, USA
Period	10/3/99 → 10/6/99

All Science Journal Classification (ASJC) codes

Fuel Technology
Energy Engineering and Power Technology

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10.2523/56433-ms

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title = "Applications of neural networks in multiwell field development",

abstract = "A neuro-simulation technique that forms a bridge between an accurate reservoir simulator and a fully-trained predictive artificial neural network (ANN) is presented. Results are given that demonstrate the effectiveness of neuro-simulation to reduce computational effort and to maintain accurate predictive capabilities. Guidelines for using this technique to optimize the placement of the wells are also introduced.",

author = "A. Centilmen and T. Ertekin and Grader, {A. S.}",

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AU - Centilmen, A.

AU - Ertekin, T.

AU - Grader, A. S.

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N2 - A neuro-simulation technique that forms a bridge between an accurate reservoir simulator and a fully-trained predictive artificial neural network (ANN) is presented. Results are given that demonstrate the effectiveness of neuro-simulation to reduce computational effort and to maintain accurate predictive capabilities. Guidelines for using this technique to optimize the placement of the wells are also introduced.

AB - A neuro-simulation technique that forms a bridge between an accurate reservoir simulator and a fully-trained predictive artificial neural network (ANN) is presented. Results are given that demonstrate the effectiveness of neuro-simulation to reduce computational effort and to maintain accurate predictive capabilities. Guidelines for using this technique to optimize the placement of the wells are also introduced.

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T2 - 1999 SPE Annual Technical Conference and Exhibition: 'Production Operations and Engineering - General'

Y2 - 3 October 1999 through 6 October 1999

ER -

Applications of neural networks in multiwell field development

Abstract

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