INTECO is ready to connect to the artificial intelligence system
Russian scientists have created an artificial intelligence system that can predict how much oil can be extracted from a particular field using multi-stage fracturing.
This is reported by the press service of the SKOLKOVO Institute of science and technology with reference to an article in the Journal of Petroleum Science and Engineering. «Our approach opens up opportunities for creating a system that will give engineers recommendations on the optimal set of parameters for hydraulic fracturing, or at least information about narrower ranges to find the right set of design parameters», said one of the developers, Skoltech Professor Andrey Osiptsov.
Over the past century, geologists have discovered many deposits of oil and other hydrocarbons, «sealed» inside the deposits of shale rocks. They contain large reserves of minerals, but until recently it was either impossible or unprofitable to extract them. About 50 years ago, engineers solved this problem by inventing a technique for hydraulic fracturing.
Its essence is that oil workers drill a special network of wells in the oil-bearing rock, into which a specially selected viscous liquid with solid particles is pumped under pressure. As a result, many cracks are formed in the rocks, through which hydrocarbons can be pumped out.
INTECO BUR works with advanced technologies. The management supports any startups associated with development and modernization. According to the head of the drilling Department INTECO BUR, «hydraulic fracturing is now used for oil production in the United States, Canada, and other countries with large deposits of shale rocks. In Russia it can be applied to develop so-called Bazhenov group – an oil shale, a giant reservoir of which formed in the late Jurassic at the bottom of the sea located on the site of the modern Western Siberia. According to experts, they contain from 1 to 60 billion tons of oil».
In recent years, the technique of hydraulic fracturing has become so complex that it requires calculating all the properties of the field using very accurate computer models. And even such calculations, as practice shows, do not always give a completely optimal result. Because of this, a significant part of the oil remains inside the rock.
Scientists have found a solution to this problem. They adapted a machine learning system to predict how much oil can be extracted from an arbitrary rock formation using multi-stage hydraulic fracturing.
Russian oil workers and scientists have been collecting a detailed database for two years, which includes comprehensive information on the volume of production and the nature of the device for about six thousand wells and 20 oil fields in Western Siberia.
Using this data, mathematicians from Skoltech trained the AI system to accurately calculate how a well will behave during production and how much oil can be extracted from it, using the current parameters of hydraulic fracturing. Withal, as scientists note, this algorithm can be adapted to solve the inverse problem – to choose the optimal parameters for hydraulic fracturing.
In addition, the same approach can be used for scientific research, in particular, to determine how the composition of the liquid, the amount of solid particles in it, and other parameters of work affect the amount of oil extracted and other important aspects of well operation. These calculations will help oil companies more optimally and safely extract hydrocarbons from the earth’s interior, scientists conclude.
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