Prediction of Hydrodynamic Parameters of the State of the Bottomhole Zone of Wells Using Machine Learning Methods

Prediction of Hydrodynamic Parameters of the State of the Bottomhole Zone of Wells Using Machine Learning Methods

The relevance of the development of a methodology for the operational assessment of the bottom-hole formation zone (the permeability of the bottom-hole formation zone and the skin factor) is primarily due to economic considerations, since existing approaches to its definition based on hydrodynamic s...

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Bibliographic Details
Main Authors: Andrey V. Soromotin, Dmitriy A. Martyushev, Alexander A. Melekhin
Format: Article
Language:English
Published: Georesursy Ltd. 2024-03-01
Series:Georesursy
Subjects:
sandstone reservoir
bottom-hole formation zone
permeability
skin factor
machine learning
neural network
Online Access:https://geors.ru/archive/article/1303/

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