ArticleScientific reports2024
Hydraulic flow unit and rock types of the Asmari Formation, an application of flow zone index and fuzzy C-means clustering methods.
Article in Scientific reports, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
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11 citing papers in PubMed, 38 citations in OpenAlex.
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- Integrating NMR and machine learning for pore-type driven rock classification in the heterogeneous Asmari carbonate reservoirs.Scientific reports · 2025Article
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- Integrating machine learning and geomorphic indices to assess tectonic geomorphology in the Karoun River Basin, Zagros, SW Iran.Scientific reports · 2025Article
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- Reservoir characterization of Yolde Formation, Kolmani Field, Gongola Basin, Nigeria using pressure, temperature, PVT, and well log data.Scientific reports · 2025Article
- Exploring the time-dependent behaviors of the rock mass roof of tunnels in open underground spaces of coal mines through numerical investigation.Scientific reports · 2025Article
- Investigating the effect of hole size, bottom hole temperature, and composition on cement bonding quality of exploratory wells in Iran.Scientific reports · 2024Article
- Unraveling time-dependent roof stability dynamics in Iran's coal mines through laboratory-based rock displacement testing.Scientific reports · 2024Article
- Scaling-up dynamic elastic logs to pseudo-static elastic moduli of rocks using a wellbore stability analysis approach in the Marun oilfield, SW Iran.Scientific reports · 2024Article
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5 authors at 2 institutions in 1 country.
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Abstract
Rock types are the reservoir's most essential properties for special facies modeling in a defined range of porosity and permeability. This study used clustering techniques to identify rock types in 280 core samples from one of the wells drilled in the Asmari reservoir in the Mansouri field, SW Iran. Four hydraulic flow units (HFUs) were determined for studied data utilizing histogram analysis, normal probability analysis, and the sum of squared errors (SSE) statistical methods. Then, two flow zone index (FZI) and fuzzy c-means (FCM) clustering methods were used to determine the rock types in the given well according to the results obtained from the HFU continuity index acts in-depth. The FCM method, with a continuity number of 3.12, compared to the FZI, with a continuity number of 2.77, shows more continuity in depth. The relationship between permeability and porosity improved considerably by utilizing HFU techniques. This improvement is achieved using the FZI method study. Generally, all samples increased from 0.55 to 0.81 in the first HFU and finally to 0.94 in the fourth HFU. Similar flow properties in an HFU characterized the samples. In comparison, the correlation coefficients obtained in the FCM method are less than those in the general case of all HFUs. This study aims to determine the flowing fluid in the porous medium of the Asmari reservoir employing the c-mean fuzzy logic. Also, by determining the facies of the rock units, especially the siliceous-clastic facies and log data in the Asmari Formation, the third and fourth flow units have the highest reservoir quality and permeability. Results can be compared to determining HFU in nearby wellbores without cores.
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