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Data mining applications in hydrocarbon exploration

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Abstract

This paper presents a review of the use of intelligent data analysis techniques in Hydrocarbon Exploration. The term “intelligent” is used in its broadest sense. The process of hydrocarbon exploration exploits data which have been collected from different sources. Different dimensions of data are analyzed by using Statistical Analysis, Data Mining, Artificial Neural Networks and Artificial Intelligence. This review is meant not only to describe the evolution of intelligent data analysis techniques used in different phases of hydrocarbon exploration but also signifying the growing use of Data Mining in various application domains; we avoided a general review of Data Mining and other intelligent data analysis techniques in this paper. The volume of general literature might affect the precision of our view regarding the application of these techniques in hydrocarbon exploration. The review reveals the suitability of existing techniques to data collected from diverse sources in addition to the use of analytical techniques for the process of hydrocarbon exploration.

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Authors and Affiliations

  1. University of Engineering & Technology, Lahore, Pakistan

    Muhammad Shaheen, Muhammad Shahbaz & Zahoor ur Rehman

  2. Information Technology Management, Ryerson University, Toronto, ON, Canada

    Aziz Guergachi

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  1. Muhammad Shaheen
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  2. Muhammad Shahbaz
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  3. Zahoor ur Rehman
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  4. Aziz Guergachi
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Correspondence to Muhammad Shaheen.

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Shaheen, M., Shahbaz, M., ur Rehman, Z. et al. Data mining applications in hydrocarbon exploration. Artif Intell Rev 35, 1–18 (2011). https://doi.org/10.1007/s10462-010-9180-z

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