Essential Components of an Integrated Data Mining Tool for the Oil and Gas Industry with an Example Application in the DJ Basin

Data mining seems to be the new buzz word. during the past several years many industriesother than the oil and gas industry have realized the potential benefits of da5ta mining andhave established sophisticated operations in order to implement this exciting technology in theirrespective organizations. data mining is not new. it has been around for many years. whatis new about its current implementation is the incorporation of machine learning techniques.the oil and gas industry has become familiar with machine learning techniques since the early1990s. neural networks, genetic optimization and fuzzy logic have been used in numerousapplications, from well log interpretations to hydraulic fracturing optimization. therefore, thenew interest in data mining in this industry is not surprising. the industry is at its peak statefor benefiting from what data mining has to offer, thanks to an abundance of digital data. aword of caution is in order, which is the main motivation behind writing this paper. as withmany other new tools and technologies, the term data mining can be, and is currently being,misused on several occasions. in this paper, an attempt has been made to answer questions suchas; what is data mining? how can it be accomplished? what are the essential components ofan integrated data mining process and what would be the benefits of such a process? in additionto answering questions such as those mentioned above, this paper will provide a road map (aset of guidelines) for a successful data mining project. finally, the paper concludes by applyingthe presented guidelines to a hydraulic fracturing data set in the oj basin of the united statesrockies for a data mining study