Big Data Approach for Geological Study of the Big Region West Siberia

Abstract

Big Data technologies are now being actively integrated into the oil and gas sector owing to the need to improve operational efficiency and to optimize a variety of processes. Successful projects in data processing automation have already been implemented, for example, new breakthroughs are expected in digital field modelling projects /1/. Geological and geophysical information accumulated over decades of studies in oil and gas bearing basins and fields development is a huge amount of data; Big Data approaches can be effectively applied to them, such as data mining, predictive analytics, training of a system on the reference objects. 3D seismic data is a classic example of Big Data. Their interpretation conventionally involves approaches based on Neural Networks, various classification and clustering algorithms /2/. According to the experts, the West Siberian Petroleum Basin being a holistic system, has unique properties such as existence of giant and unique hydrocarbon accumulations /3/. The potential of the basin has not yet been determined. The authors focused their attention on the Achimov play. Applying the Big Data approach to a regional database may allow establishing new patterns in fields distribution and will contribute to the development of new unique exploration criteria.