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- W2891343607 abstract "Reservoir characterization is one of the most important goals for the development of any oilfield. Determination of permeability and rock types are of prime importance to judge reservoir quality. In this research, Stoneley waves from dipole sonic tools were used in order to discover changes in permeability in the Bangestan reservoir, Mansouri oilfield. Index (tortuosity) could be estimated by Stoneley waves. After comparing the permeability resulting from Stoneley waves, cores and the Timur method, it was concluded that all the three permeabilities were very similar. The core porosity and effective porosity from the analysis of well logs were found to match as well. Electrofacies (EF) method, as a clustering method, was utilized to find rock types in order to define reservoir and non-reservoir zones. Simultaneous with EF clustering, gamma ray, neutron porosity, density, sonic, water saturation and porosity (PHIE) data from 78 wells were also considered and interpreted. Nine clusters were defined as a result of the analysis, being reduced to only four clusters after applying PC (capillary pressure) data. Among the four clusters, clusters 1 and 2 contained more vuggy pores than the others. Fracture abundance and solution seams were observed more frequently in EF-3 as compared to other EFs. Based on the matrix type, Archie porosity classification types I and III were recognized. The pore sizes in EFs-1 and 2 were mostly of the B type while in EF-3, it was A type. The EFs generated and determined by Stoneley waves and the well log data were also compared, showing a good correlation." @default.
- W2891343607 created "2018-09-27" @default.
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- W2891343607 date "2018-04-01" @default.
- W2891343607 modified "2023-10-06" @default.
- W2891343607 title "Stoneley Wave Predicted Permeability and Electrofacies Correlation in the Bangestan Reservoir, Mansouri Oilfield, SW Iran" @default.
- W2891343607 cites W2100040728 @default.
- W2891343607 doi "https://doi.org/10.22201/igeof.00167169p.2018.57.2.2040" @default.
- W2891343607 hasPublicationYear "2018" @default.
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