Big data is a nebulous and much-hyped concept in IT. IT companies have noted that exploration and production involves handling and storing large, and ever-increasing, amounts of data. They are therefore positioning their various "big data" products as solutions in search of E&P problems. This paper presents an overview of big data technologies and discusses ways in which these technologies could be used to improved exploration and production operations. The paper will present a working definition of what big data is for the upstream oil and gas industry. Big data is a repackaging of a variety of IT technologies, including pattern analysis and recursive estimation using streaming data, management of large-scale parallel databases, in-memory computing, fast search, natural-language processing and the statistical analysis of large datasets. In many ways, the E&P industry has been a pioneer in these areas, where the technology push has been driven by geophysicists and engineers rather than computer scientists and statisticians. The message presented is that these tools give allow faster processing, searching and analysis of data, but the their full benefits will only be obtained when they are (a) combined with physical insight and models, (b) used by talented and experienced engineers and (c) deployed to solve real and pressing business problems and (d) integrated with corporate IT. The paper will discuss the organizational and ethical implications of big data, including issues such as: the use of big data in small organizations; the roles of IT companies and traditional service companies in implementing big data; the maintenance of security, privacy and accountability using big data and the use of big data in collaborative workflows and integrated operations.

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