«Geology, geophysics and development of oil and gas fields»

Neural networks use for interpretation of wells geophysical surveys of Permian Carboniferous deposit in the Usinsk oil field

UDC: 556.3(470.53)+550.834.072
DOI: 10.33285/2413-5011-2022-4(364)-24-27

Authors:

¹ LUKOIL-Engineering Limited PermNIPIneft Branch Office in Perm, Perm, Russia
² Perm National Research Polytechnic University

Keywords: neural networks, well logging, reservoir prediction, effective thicknesses, lithological types of rocks, viscosity

Annotation:

The article discusses various aspects of neural networks use: reservoir identification, lithotype determination, fluids’ viscosity assessment along the wellbores in the Permian Carboniferous (PC) deposit of the Usinsk oil field.

The use of neural networks apparatus when solving various problems makes it possible to interpret well logging data, automate the process of the work performed, take into account multi-factor presence, get away from the problems of subjectivity in assessing a certain contractor, reduce the routine work of the interpreter as well as allow quickly find solutions to non-trivial tasks, which have not been previously performed, including assessing the quality (reliability) of the results obtained.

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