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Application of Large Online Data Sets for Improved Understanding of the Subsurface

Timothy R. Carr, Kurt Look, Jeremy Bartley, and Keith L. Hunsinger
Kansas Geological Survey, University of Kansas, Lawrence, KS

Over the last few years, rapid improvements in computing power, data-storage volume, connectivity and data-capture technology have increased exponentially the speed and quantity of available of online data that can be accessed, analyzed and displayed to provide a better understanding of the subsurface. In Kansas, data relevant to the petroleum industry is automatically gathered through multiple channels, loaded into relational databases, and provided on demand through custom search, analysis and display tools. In addition, conversion of large volumes of historical data from visual “paper” files has added to the knowledge database being rapidly accumulated. Data gathering and storage techniques are constantly being improved to increase efficiency, volume and speed.

Available quantitative techniques, computing capabilities, and large volumes of accessible digital data, are being applied to large-scale geological questions. Major improvements in regional and local subsurface mapping - with integration of multiple datasets and 3D visualization- provide significant new insights into subsurface processes such as the relation of fluid migration and petroleum accumulations to regional structure. Geostatistical techniques are being used to integrate large volumes of data at multiple scales (e.g., core wire-line logs, and production) to improve our quantitative understanding of local and regional depositional processes. Examples include controls on the accumulation of carbonate shoals across a broad platform and the formation of karst on a regional unconformity. Through recent improvements in online interactive modeling and graphical display the ability and efficiency of the individual geoscientist understand the regional and local geology from the desktop has been increased.