Conditioning reservoir models to dynamic data - a forward modeling perspective

Sanjay Srinivasan; Jef Caers

doi:10.2118/62941-ms

Conditioning reservoir models to dynamic data - a forward modeling perspective

Sanjay Srinivasan, Jef Caers

John and Willie Leone Department of Energy & Mineral Engineering (EME)

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

7 Scopus citations

Abstract

A neural network-based procedure for filtering the information related to the permeability field in flow response data is presented. It is shown that flow simulation on the simulated permeability fields match historic well test data accurately.

Original language	English (US)
Pages	107-122
Number of pages	16
DOIs	https://doi.org/10.2118/62941-ms
State	Published - 2000
Event	Proceedings 2000 SPE Annual Technical Conference and Exhibition - Production Operations and Engineering General - Dallas, TX, USA Duration: Oct 1 2000 → Oct 4 2000

Other

Other	Proceedings 2000 SPE Annual Technical Conference and Exhibition - Production Operations and Engineering General
City	Dallas, TX, USA
Period	10/1/00 → 10/4/00

All Science Journal Classification (ASJC) codes

Fuel Technology
Energy Engineering and Power Technology

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10.2118/62941-ms

Cite this

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title = "Conditioning reservoir models to dynamic data - a forward modeling perspective",

abstract = "A neural network-based procedure for filtering the information related to the permeability field in flow response data is presented. It is shown that flow simulation on the simulated permeability fields match historic well test data accurately.",

author = "Sanjay Srinivasan and Jef Caers",

year = "2000",

doi = "10.2118/62941-ms",

language = "English (US)",

pages = "107--122",

note = "Proceedings 2000 SPE Annual Technical Conference and Exhibition - Production Operations and Engineering General ; Conference date: 01-10-2000 Through 04-10-2000",

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AU - Srinivasan, Sanjay

AU - Caers, Jef

PY - 2000

Y1 - 2000

N2 - A neural network-based procedure for filtering the information related to the permeability field in flow response data is presented. It is shown that flow simulation on the simulated permeability fields match historic well test data accurately.

AB - A neural network-based procedure for filtering the information related to the permeability field in flow response data is presented. It is shown that flow simulation on the simulated permeability fields match historic well test data accurately.

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U2 - 10.2118/62941-ms

DO - 10.2118/62941-ms

M3 - Paper

AN - SCOPUS:0034502243

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T2 - Proceedings 2000 SPE Annual Technical Conference and Exhibition - Production Operations and Engineering General

Y2 - 1 October 2000 through 4 October 2000

ER -

Conditioning reservoir models to dynamic data - a forward modeling perspective

Abstract

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All Science Journal Classification (ASJC) codes

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