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Gazprom Neft and IBM developing innovative methods in the search and identification of new hydrocarbon reserves

Following the signing of a cooperation agreement in June 2016, Gazprom Neft and IBM have now begun implementing computer-assisted cognition (self-taught programmes) in the analysis and interpretation of well-logging data. This joint initiative in the development of innovative new software in data processing is part of Gazprom Neft’s ongoing “Technology Strategy”*. These new methodologies will allow the identification and development of promising reserves in mature fields.

Thousands of wells are in operation throughout Gazprom Neft’s fields, from which a massive volume of highly varied data is obtained every day, both during drilling and throughout the operation of each well. This information — on the condition and status of strata, and the hydrocarbons therein — is vital to effective field development.

The data obtained are heterogeneous and unstructured, meaning detailed analysis and management by individuals is not possible. Innovative techniques based on computer-assisted cognition, artificial intelligence and other modern IT-technologies not only allow the interpretation of information on reservoir characteristics (based on available algorithms) but also identifies new consistencies and patterns which are constantly adjusted to include new specifications — as a result of which the scope of such analysis is constantly being expanded.

The joint work of both companies here means, specifically, that self-learning algorithms being to emerge that can, in a short time, identify the oil-bearing parts of a field and simulate the necessary incoming well data where existing data is incomplete. In addition to which, the operation of these algorithms is automatically analysed and the likelihood of internal errors assessed. The techniques developed here will allow specialists to divert attention from routine data analysis in favour of expert appraisals with the result that the quality of geophysical analysis will be improved and, consequently, the identification of new reserves and the means for developing these.

«The oil industry is becoming more high-tech with every passing year, particularly in terms of IT technology, allowing improvements in effective field development. Through the development of ‘Big Data’ we are able to analyse massive volumes of structured and unstructured information, revealing new patterns and trends and allowing still more detailed investigation of our fields. IBM’s experience of working on similar projects has allowed the development of a new product, specifically adapted to our requirements and in line with international experience elsewhere, including in other high-technology industries».
Vadim Yakovlev
Vadim Yakovlev First Deputy CEO, Gazprom Neft
Notes for editors

* At the end of 2014 various Gazprom Neft projects, directed at improving efficiency in oil and gas production, the development of new reserves, and the implementation of the company’s strategic objectives, were brought together in a single concept document, named as the company’s “Technology Strategy”. All technological challenges facing Gazprom Neft were allocated into nine priority areas, including specific projects with clear lead times and anticipated outcomes. The company’s Joint Scientific and Technology Centre is responsible for coordinating its Technology Strategy.

The development of new software for processing well-logging data is being implemented as part of a strategy for “Enhanced oil recovery and well stimulation”. This is being developed, in part, for work with mature assets. The core objective here being the identification of residual hydrocarbon reserves and the search for effective technologies for their development. Techniques in the identification of residual oil reserves, development of which is undertaken by the Gazprom Neft Joint Scientific and Technology Centre, allow the more precise determination of reservoir structure, and their current state. In many cases this involves the development of hard-to-recover reserves, since residual reserves, as a rule, are characterised by complex geological reservoir structures, and oil with very specific properties. This initiative also involves the development and testing of new technologies in enhanced oil recovery (EOR), as well as well stimulation, water flooding, and tertiary EOR techniques.