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Permeability Prediction Using Different Methods in Carbonate Reservoir
https://orcid.org/https://orcid.org/0000-0001-8154-1893
https://orcid.org/https://orcid.org/0000-0001-5447-1332
This study aims to predict Yamama layers formation permeability of five wells: N1, N2, N3, N4, and N5, each containing Yamama, Yamama B and Yamama C layers. The permeability was calculated through two methods, namely the basic analysis and well-log techniques. The basic analysis method was conducted in the laboratory using a PERL-200 device. The results obtained using this method were more accurate as they matched the well-log results. Employing Matlab software, a neural network predicted permeability for 14 layers of 5 wells, with the second and fifth wells having only two layers. By constructing a 13-layer neural network, an appropriate network configuration can be achieved to discover the relationship between the input and output and produce a matching target result.
Permeability Prediction Using Different Methods in Carbonate Reservoir
https://orcid.org/https://orcid.org/0000-0001-8154-1893
https://orcid.org/https://orcid.org/0000-0001-5447-1332
This study aims to predict Yamama layers formation permeability of five wells: N1, N2, N3, N4, and N5, each containing Yamama, Yamama B and Yamama C layers. The permeability was calculated through two methods, namely the basic analysis and well-log techniques. The basic analysis method was conducted in the laboratory using a PERL-200 device. The results obtained using this method were more accurate as they matched the well-log results. Employing Matlab software, a neural network predicted permeability for 14 layers of 5 wells, with the second and fifth wells having only two layers. By constructing a 13-layer neural network, an appropriate network configuration can be achieved to discover the relationship between the input and output and produce a matching target result.
Permeability Prediction Using Different Methods in Carbonate Reservoir
https://orcid.org/https://orcid.org/0000-0001-8154-1893
https://orcid.org/https://orcid.org/0000-0001-5447-1332
This study aims to predict Yamama layers formation permeability of five wells: N1, N2, N3, N4, and N5, each containing Yamama, Yamama B and Yamama C layers. The permeability was calculated through two methods, namely the basic analysis and well-log techniques. The basic analysis method was conducted in the laboratory using a PERL-200 device. The results obtained using this method were more accurate as they matched the well-log results. Employing Matlab software, a neural network predicted permeability for 14 layers of 5 wells, with the second and fifth wells having only two layers. By constructing a 13-layer neural network, an appropriate network configuration can be achieved to discover the relationship between the input and output and produce a matching target result.
Permeability Prediction Using Different Methods in Carbonate Reservoir
Pet. Chem.
Ramadhan, Ahmad A. (Autor:in) / Kadhim, Fadhil S. (Autor:in) / Mohammed, Noor Al-Huda A. (Autor:in) / Salman, Adyanh K. (Autor:in) / Jabbar, Mariam A. (Autor:in)
Petroleum Chemistry ; 64 ; 891-899
01.07.2024
9 pages
Aufsatz (Zeitschrift)
Elektronische Ressource
Englisch
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