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

Authors
Tatiana Olneva (Gazpromneft NTC) | Dmitryi Kuzmin (Gazpromneft NTC) | Svetlana Rasskazova (Gazpromneft NTC) | Azamat Timirgalin (Gazpromneft NTC)
DOI
https://doi.org/10.2118/191726-MS
Document ID
SPE-191726-MS
Publisher
Society of Petroleum Engineers
Source
SPE Annual Technical Conference and Exhibition, 24-26 September, Dallas, Texas, USA
Publication Date
2018
Document Type
Conference Paper
Language
English
ISBN
978-1-61399-572-3
Copyright
2018. Society of Petroleum Engineers
Disciplines
6.1 HSSE & Social Responsibility Management, 7 Management and Information, 7.6.4 Data Mining, 6 Health, Safety, Security, Environment and Social Responsibility, 7.6 Information Management and Systems, 6.1.5 Human Resources, Competence and Training
Keywords
cluster, Big Data, training set, Neocomian Achimov Formation, object-oriented interpretation
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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.

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Khasanov M.M., Prokofiev D.O., Ushmaev O.S., Belozerov B.V., Gilmanov R.R., Margarit A.S. The advanced Big Data technologies in petroleum engineering: experience of Gazprom Neft Company, Neftyanoe Khoziaistvo, Dec. 2006, pp.76-79

Rodon R. Seismic interpretation in the Age of Big Data. 2017 SEG international Exposition and 86th Annual Meeting, p.4911-4914.

Nezhdanov A.A.Geology and petroleum potential of the Achimov series of Western Siberia, Moscow: Akademiya gornykh nauk, 2000.

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