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AAPG Bulletin

Abstract

AAPG Bulletin, V. 96, No. 11 (November 2012), P. 21212142.

Copyright copy2012. The American Association of Petroleum Geologists. All rights reserved.

DOI:10.1306/04251212009

Geographic information system–based fuzzy-logic analysis for petroleum exploration with a case study of northern South America

Lisa Bingham,1 Raul Zurita-Milla,2 Alejandro Escalona3

1Department of Petroleum Engineering, University of Stavanger, Stavanger, Norway; [email protected]
2Faculty of Geo-Information Science and Earth Observation (ITC), University of Twente, the Netherlands; [email protected]
3Department of Petroleum Engineering, University of Stavanger, Stavanger, Norway; [email protected]

ABSTRACT

The petroleum industry is increasingly using geographic information systems (GISs) for mapping and spatial database needs because they are useful for elucidating and exploiting spatial relationships between geologic and geophysical data. However, the petroleum industry, in general, does not exploit the full potential of GIS as an analysis tool. In particular, GIS offers spatial and analytical support for multicriteria evaluation (MCE) methods, which are used to combine data to show areas best fulfilling specific criteria. Petroleum explorations would benefit from an MCE method that is spatial, is flexible for combining heterogeneous data, considers the interpretive nature of the data, is geologically applicable, and is applicable for frontier areas or where little information exists regarding probabilities of the presence of petroleum.

This study proposes a GIS-based MCE method for petroleum exploration based on fuzzy logic, which fulfills the previously stated requirements using 16 subcriteria and one constraint combined in tiers to produce a favorability map of potential exploration areas.

A case study applied to northern South America, chosen because of its centrality to petroleum exploration, shows potential new exploration areas in the Cretaceous–Paleogene and Miocene–Holocene. The method was validated by comparing the favorability maps of one non–geologic age–specific and of two geologic age–specific favorability maps to known producing fields.

We conclude that the method can be applied in an exploration setting and, as such, is applicable for other regions of the world.

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