2005
DOI: 10.2118/84301-pa
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The Role of Electrofacies, Lithofacies, and Hydraulic Flow Units in Permeability Prediction From Well Logs: A Comparative Analysis Using Classification Trees

Abstract: Summary Predicting permeability from well logs typically involves classification of the well-log response into relatively homogeneous subgroups based on electrofacies, Lithofacies, or hydraulic flow units (HFUs). The electrofacies-based classification involves identifying clusters in the well-log response that reflect "similar" minerals and lithofacies within the logged interval. This statistical procedure is straightforward and inexpensive. However, identification of lithofacies and HFUs rel… Show more

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Cited by 87 publications
(23 citation statements)
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“…Thus, electrofacies bind all these properties mathematically (see Steps 4 through 8). Pérez et al (2005) proved that electrofacies are superior compared with other competing techniques.…”
Section: Discussion and Validationmentioning
confidence: 99%
“…Thus, electrofacies bind all these properties mathematically (see Steps 4 through 8). Pérez et al (2005) proved that electrofacies are superior compared with other competing techniques.…”
Section: Discussion and Validationmentioning
confidence: 99%
“…Hydraulic flow units cannot be characterized efficiently unless there is enough core and well logs data. The resulted permeability has specific link to porosity at every characterized flow zone unit (Lacentre, et al, 2003;Perez and Gupta, 2005;Teh and Willhite, 2012;Yerramilli, et al, 2013).…”
Section: Permeability Estimationmentioning
confidence: 99%
“…They confirmed the algorithm on the basis of core analysis, and from that they proposed rock types for uncored intervals. Perez et al (2005) defined a dimensionless capillary pressure function, and by using classification-tree analysis on wireline logs and core analysis, they predicted the rock types. Lawal and Onyekonwu (2005) defined flow-unit delineators for sandstones and carbonates by geometrically averaging all characterizing parameters from five existing flow-unit models.…”
Section: Literaturementioning
confidence: 99%