Determination of Permeability Transforms from Geophysical Logs using Statistical Pattern Recognition: The Mardie Greensand

Yujin Zhang; Patrick A. Lollback; Henry A. Salisch; Jorg Schulz-Rojahn

doi:10.1071/EG997181

ISSN: 0812-3985
E-ISSN: 1834-7533

Determination of Permeability Transforms from Geophysical Logs using Statistical Pattern Recognition: The Mardie Greensand
Authors Yujin Zhang^a, Patrick A. Lollback^a, Henry A. Salisch^a and Jorg Schulz-Rojahn^b
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^a Centre for Petroleum Engineering, University of New South Wales, , 2052, , Australia, . Phone (02) 9385 5974, Facsimile (02) 9385 5936, e-mail: Z.yujin @ unsw. edu.au ^b West Australian Petroleum Pty. Ltd, , Western Australia, 6001, .
Publisher: Australian Society of Exploration Geophysicists
Source: Exploration Geophysics, Volume 28, Issue 1-2, Mar 1997, p. 181 - 184
DOI: https://doi.org/10.1071/EG997181
- Published online: 01 Mar 1997

Abstract

Many permeability models and equations are empirical in log analysis and evaluation. Therefore, their application is restricted to a given set of lithology conditions. It is essential to select the correct transform relationships for each type of lithology in order to determine accurately permeability from well logs. This is especially true in the Mardie Greensand, a lithologically complex formation. There are four porosity and permeability transforms determined based on the core data in the sandstone formations of the Mardie ‘B’ and ‘C intervals in the Barrow Field, Carnarvon Basin, Western Australia. The aim in this study was to determine which porosity and permeability transform is applied at which formation from well logs, using statistical pattern recognition of electrofacies. In this paper a number of electrofacies corresponding to these porosity and permeability transforms were determined in the complex formation. The application of pattern recognition to this complex lithology makes it possible to identify electrofacies and select corresponding transforms to calculate permeabilities from well logs. Results indicate that it can reduce the uncertainty of log-derived permeability and help to simplify the problem of complex lithologies in log interpretation by recognising known lithologies within a formation, thereby improving the precision of permeability determination in this complex formation.

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References

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Derek, H., Johns, R. and Pasternack, E., 1990, Comparative study of back propagation neural network and statistical pattern recognition techniques in identifying sandstone lithofacies: Conference on Artificial Intelligence in Petroleum Exploration and Production, Proceedings: Texas A&M University, College Station, 41-49.
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Johnson, W.W., 1994, Permeability determination from well logs and core data: Presented at the Permian Basin Oil and Gas Recovery Conference, Society of Petroleum Engineers.
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Zhang, Y.J., Lollback, P.A. and Salisch, H.A., 1996, Transforms to relate porosity and permeability in the Mardie Greensand – a case study in the Carnarvon Basin, Western Australia: Proceedings of The Second Well Logging Symposium of Japan, Paper O.

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Article Type: Research Article

Keyword(s): complex formation; electrofacies; geophysical logs; permeability transform; statistical pattern recognition

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Determination of Permeability Transforms from Geophysical Logs using Statistical Pattern Recognition: The Mardie Greensand

Abstract

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