Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method

Accurate permeability prediction is essential for reservoir characterization, especially in building three-dimensional reservoir models. However, predicting permeability in the complex Tertiary reservoir/Ajeel oil field, with its different rock types and multi-layered formations, poses significant...

Full description

Saved in:
Bibliographic Details
Main Authors: Vian M. Ahmed, Ayad A. Al-Haleem
Format: Article
Language:English
Published: University of Baghdad 2024-12-01
Series:Journal of Engineering
Subjects:
Online Access:https://joe.uobaghdad.edu.iq/index.php/main/article/view/3412
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1846148221857955840
author Vian M. Ahmed
Ayad A. Al-Haleem
author_facet Vian M. Ahmed
Ayad A. Al-Haleem
author_sort Vian M. Ahmed
collection DOAJ
description Accurate permeability prediction is essential for reservoir characterization, especially in building three-dimensional reservoir models. However, predicting permeability in the complex Tertiary reservoir/Ajeel oil field, with its different rock types and multi-layered formations, poses significant challenges. This paper utilizes well logs and core data from cored wells to predict permeability for uncored wells and intervals, uses an approach integrating rock typing by cluster analysis techniques and the Flow Zone Indicator (FZI) method by categorizing reservoirs into hydraulic flow units(HFUs) based on a reservoir quality index(RQI). This approach includes classifying reservoir rocks and zonation based on comparable petrophysical properties in horizontal and vertical dimensions. Through cluster analysis, four distinct rock types in the Tertiary reservoir are identified, and four hydraulic flow units are defined by correlating core permeability and porosity using the FZI method. The correlation coefficient (R² = 0.81) is acceptable and supports the relationship reliability between FZI-derived permeability and core permeability. Then, four different rock types are linked to their corresponding permeability equations derived from the FZI method and the compensation of effective porosity values in these equations for permeability prediction. Ultimately, the permeability of uncored wells and intervals, depending on this approach, will be predicted using well-log data.
format Article
id doaj-art-0a084a9abd4b4614a8077c0ffae10bb3
institution Kabale University
issn 1726-4073
2520-3339
language English
publishDate 2024-12-01
publisher University of Baghdad
record_format Article
series Journal of Engineering
spelling doaj-art-0a084a9abd4b4614a8077c0ffae10bb32024-12-01T10:37:20ZengUniversity of BaghdadJournal of Engineering1726-40732520-33392024-12-01301210.31026/j.eng.2024.12.07Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI MethodVian M. Ahmed0Ayad A. Al-Haleem1Department of Petroleum Engineering, College of Engineering, University of BaghdadDepartment of Petroleum Engineering, College of Engineering, University of Baghdad Accurate permeability prediction is essential for reservoir characterization, especially in building three-dimensional reservoir models. However, predicting permeability in the complex Tertiary reservoir/Ajeel oil field, with its different rock types and multi-layered formations, poses significant challenges. This paper utilizes well logs and core data from cored wells to predict permeability for uncored wells and intervals, uses an approach integrating rock typing by cluster analysis techniques and the Flow Zone Indicator (FZI) method by categorizing reservoirs into hydraulic flow units(HFUs) based on a reservoir quality index(RQI). This approach includes classifying reservoir rocks and zonation based on comparable petrophysical properties in horizontal and vertical dimensions. Through cluster analysis, four distinct rock types in the Tertiary reservoir are identified, and four hydraulic flow units are defined by correlating core permeability and porosity using the FZI method. The correlation coefficient (R² = 0.81) is acceptable and supports the relationship reliability between FZI-derived permeability and core permeability. Then, four different rock types are linked to their corresponding permeability equations derived from the FZI method and the compensation of effective porosity values in these equations for permeability prediction. Ultimately, the permeability of uncored wells and intervals, depending on this approach, will be predicted using well-log data. https://joe.uobaghdad.edu.iq/index.php/main/article/view/3412Ajeel oil fieldCluster analysisFZI methodPermeability predictionTertiary reservoir
spellingShingle Vian M. Ahmed
Ayad A. Al-Haleem
Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method
Journal of Engineering
Ajeel oil field
Cluster analysis
FZI method
Permeability prediction
Tertiary reservoir
title Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method
title_full Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method
title_fullStr Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method
title_full_unstemmed Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method
title_short Permeability Prediction for Ajeel Oilfield/ Tertiary Reservoir by Integrating Rock Typing Approach with FZI Method
title_sort permeability prediction for ajeel oilfield tertiary reservoir by integrating rock typing approach with fzi method
topic Ajeel oil field
Cluster analysis
FZI method
Permeability prediction
Tertiary reservoir
url https://joe.uobaghdad.edu.iq/index.php/main/article/view/3412
work_keys_str_mv AT vianmahmed permeabilitypredictionforajeeloilfieldtertiaryreservoirbyintegratingrocktypingapproachwithfzimethod
AT ayadaalhaleem permeabilitypredictionforajeeloilfieldtertiaryreservoirbyintegratingrocktypingapproachwithfzimethod