<title>Parallel approach to identifying the well-test interpretation model using a neurocomputer</title>

Assessing the Non-Uniqueness of a Well Test Interpretation Model Using a Bayesian Approach

10.2118/200617-ms ◽

2020 ◽

Author(s):

J A Cumming ◽

T Botsas ◽

I H Jermyn ◽

A C Gringarten

Keyword(s):

Bayesian Approach ◽

Test Interpretation ◽

Well Test ◽

Interpretation Model

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A new well test interpretation model for complex fracture networks in horizontal wells with multi-stage volume fracturing in tight gas reservoirs

Natural Gas Industry B ◽

10.1016/j.ngib.2020.09.009 ◽

2020 ◽

Vol 7 (5) ◽

pp. 514-522

Author(s):

Weiping Ouyang ◽

Hedong Sun ◽

Hongxu Han

Keyword(s):

Horizontal Wells ◽

Test Interpretation ◽

Tight Gas ◽

Well Test ◽

Gas Reservoirs ◽

Tight Gas Reservoirs ◽

Complex Fracture ◽

Multi Stage ◽

Volume Fracturing ◽

Interpretation Model

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Development of the HT-BP Neural Network System for the Identification of a Well-Test Interpretation Model

SPE Computer Applications ◽

10.2118/30974-pa ◽

1996 ◽

Vol 8 (04) ◽

pp. 102-105 ◽

Cited By ~ 3

Author(s):

W. Sung ◽

I. Yoo ◽

S. Ra ◽

H. Park

Keyword(s):

Neural Network ◽

Bp Neural Network ◽

Network System ◽

Test Interpretation ◽

Well Test ◽

Neural Network System ◽

Interpretation Model

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Application of Neural Network to the Determination of Well-Test Interpretation Model for Horizontal Wells

10.2118/77878-ms ◽

2002 ◽

Cited By ~ 5

Author(s):

Mir Asif Sultan ◽

Abdulaziz U. Al-Kaabi

Keyword(s):

Neural Network ◽

Horizontal Wells ◽

Test Interpretation ◽

Well Test ◽

Interpretation Model

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Assessing the Non-uniqueness of the Well Test Interpretation Model Using Deconvolution - (SPE-164870)

London 2013, 75th eage conference en exhibition incorporating SPE Europec ◽

10.3997/2214-4609.20130164 ◽

2013 ◽

Author(s):

T.M. Whittle ◽

J. Cumming ◽

D. Wooff ◽

R. Crossman ◽

A.C. Gringarten

Keyword(s):

Test Interpretation ◽

Well Test ◽

Interpretation Model

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An Artificial Neural Network Approach To Identify the Well Test Interpretation Model: Applications

10.2118/20552-ms ◽

1990 ◽

Cited By ~ 13

Author(s):

A.U. Al-Kaabi ◽

W.J. Lee

Keyword(s):

Neural Network ◽

Artificial Neural Network ◽

Test Interpretation ◽

Well Test ◽

Network Approach ◽

Neural Network Approach ◽

Artificial Neural ◽

Interpretation Model ◽

Artificial Neural Network Approach

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Assessing the Non-Uniqueness of the Well Test Interpretation Model Using Deconvolution

10.2118/164870-ms ◽

2013 ◽

Cited By ~ 4

Author(s):

J. A. Cumming ◽

D. A. Wooff ◽

T. Whittle ◽

R. J Crossman ◽

A. C. Gringarten

Keyword(s):

Test Interpretation ◽

Well Test ◽

Interpretation Model

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Development of HT- BP Neural Network System for the Identification of Well Test Interpretation Model

10.2118/30974-ms ◽

1995 ◽

Cited By ~ 4

Author(s):

W. Sung ◽

I. Yoo ◽

S. Ra ◽

H. Park

Keyword(s):

Neural Network ◽

Bp Neural Network ◽

Network System ◽

Test Interpretation ◽

Well Test ◽

Neural Network System ◽

Interpretation Model

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Well Test interpretation Model on Power-law Non-linear Percolation Pattern in Low-permeability Reservoirs

10.2118/132271-ms ◽

2010 ◽

Cited By ~ 5

Author(s):

Shun Liu ◽

Kai Zhang ◽

Rui Han

Keyword(s):

Power Law ◽

Low Permeability ◽

Test Interpretation ◽

Well Test ◽

Non Linear ◽

Low Permeability Reservoirs ◽

Interpretation Model

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Using an Expert System To Identify a Well-Test-Interpretation Model

Journal of Petroleum Technology ◽

10.2118/18158-pa ◽

1990 ◽

Vol 42 (05) ◽

pp. 654-661 ◽

Cited By ~ 6

Author(s):

Abdul-Aziz U. Al-Kaabl ◽

Duane A. McVay ◽

John W. Lee

Keyword(s):

Expert System ◽

Test Interpretation ◽

Well Test ◽

Interpretation Model

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