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Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells

[Image: see text] The world is gradually moving toward a severe energy crisis, with an ever-increasing demand for energy overstepping its supply. Therefore, the energy crisis in the world has shed important light on the need for enhanced oil recovery to provide an affordable energy supply. Inaccurat...

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Autores principales: Shahat, John S., Soliman, Ahmed Ashraf, Gomaa, Sayed, Attia, Attia Mahmoud
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2023
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249038/
https://www.ncbi.nlm.nih.gov/pubmed/37305282
http://dx.doi.org/10.1021/acsomega.3c00904
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author Shahat, John S.
Soliman, Ahmed Ashraf
Gomaa, Sayed
Attia, Attia Mahmoud
author_facet Shahat, John S.
Soliman, Ahmed Ashraf
Gomaa, Sayed
Attia, Attia Mahmoud
author_sort Shahat, John S.
collection PubMed
description [Image: see text] The world is gradually moving toward a severe energy crisis, with an ever-increasing demand for energy overstepping its supply. Therefore, the energy crisis in the world has shed important light on the need for enhanced oil recovery to provide an affordable energy supply. Inaccurate reservoir characterization may lead to the failure of enhanced oil recovery projects. Thus, the accurate establishment of reservoir characterization techniques is required to successfully plan and execute the enhanced oil recovery projects. The main objective of this research is to obtain an accurate approach that can be used to estimate rock types, flow zone indicators, permeability, tortuosity, and irreducible water saturation for uncored wells based on electrical rock properties that were obtained from only logging tools. The new technique is obtained by modifying the Resistivity Zone Index (RZI) equation that was presented by Shahat et al. by taking the tortuosity factor into consideration. When true formation resistivity (R(t)) and inverse porosity (1/Φ) are correlated on a log–log scale, unit slope parallel straight lines are produced, where each line represents a distinct electrical flow unit (EFU). Each line’s intercept with the y-axis at 1/Φ = 1 yields a unique parameter specified as the Electrical Tortuosity Index (ETI). The proposed approach was validated successfully by testing it on log data from 21 logged wells and comparing it to the Amaefule technique, which was applied to 1135 core samples taken from the same reservoir. Electrical Tortuosity Index (ETI) values show marked accuracy for representing reservoir compared with Flow Zone Indicator (FZI) values obtained by the Amaefule technique and Resistivity Zone Index (RZI) values obtained by the Shahat et al. technique, with correlation coefficients of determination (R(2)) values equal to 0.98 and 0.99, respectively. Hence, by using the new technique, the Flow Zone Indicator, permeability, tortuosity, and irreducible water saturation were estimated and then compared with the obtained results from the core analysis, which showed a great match with the R(2)-values of 0.98, 0.96, 0.98, and 0.99, respectively.
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spelling pubmed-102490382023-06-09 Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells Shahat, John S. Soliman, Ahmed Ashraf Gomaa, Sayed Attia, Attia Mahmoud ACS Omega [Image: see text] The world is gradually moving toward a severe energy crisis, with an ever-increasing demand for energy overstepping its supply. Therefore, the energy crisis in the world has shed important light on the need for enhanced oil recovery to provide an affordable energy supply. Inaccurate reservoir characterization may lead to the failure of enhanced oil recovery projects. Thus, the accurate establishment of reservoir characterization techniques is required to successfully plan and execute the enhanced oil recovery projects. The main objective of this research is to obtain an accurate approach that can be used to estimate rock types, flow zone indicators, permeability, tortuosity, and irreducible water saturation for uncored wells based on electrical rock properties that were obtained from only logging tools. The new technique is obtained by modifying the Resistivity Zone Index (RZI) equation that was presented by Shahat et al. by taking the tortuosity factor into consideration. When true formation resistivity (R(t)) and inverse porosity (1/Φ) are correlated on a log–log scale, unit slope parallel straight lines are produced, where each line represents a distinct electrical flow unit (EFU). Each line’s intercept with the y-axis at 1/Φ = 1 yields a unique parameter specified as the Electrical Tortuosity Index (ETI). The proposed approach was validated successfully by testing it on log data from 21 logged wells and comparing it to the Amaefule technique, which was applied to 1135 core samples taken from the same reservoir. Electrical Tortuosity Index (ETI) values show marked accuracy for representing reservoir compared with Flow Zone Indicator (FZI) values obtained by the Amaefule technique and Resistivity Zone Index (RZI) values obtained by the Shahat et al. technique, with correlation coefficients of determination (R(2)) values equal to 0.98 and 0.99, respectively. Hence, by using the new technique, the Flow Zone Indicator, permeability, tortuosity, and irreducible water saturation were estimated and then compared with the obtained results from the core analysis, which showed a great match with the R(2)-values of 0.98, 0.96, 0.98, and 0.99, respectively. American Chemical Society 2023-05-24 /pmc/articles/PMC10249038/ /pubmed/37305282 http://dx.doi.org/10.1021/acsomega.3c00904 Text en © 2023 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Shahat, John S.
Soliman, Ahmed Ashraf
Gomaa, Sayed
Attia, Attia Mahmoud
Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells
title Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells
title_full Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells
title_fullStr Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells
title_full_unstemmed Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells
title_short Electrical Tortuosity Index: A New Approach for Identifying Rock Typing to Enhance Reservoir Characterization Using Well-Log Data of Uncored Wells
title_sort electrical tortuosity index: a new approach for identifying rock typing to enhance reservoir characterization using well-log data of uncored wells
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10249038/
https://www.ncbi.nlm.nih.gov/pubmed/37305282
http://dx.doi.org/10.1021/acsomega.3c00904
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