[HTML][HTML] Calculation of the characteristics of rock samples based on their images using deep machine learning algorithms

BK Assilbekov, NE Kalzhanov, BE Bekbau… - Kazakhstan journal for …, 2024 - vestnik-ngo.kz
Porosity, absolute permeability and diffusion coefficient are important characteristics of the
flow of fluids in the pore space of rocks, the determination of which is resource-intensive and …

DETERMINING THE PROPERTIES OF ROCK SAMPLES USING DEEP MACHINE LEARNING

B Assilbekov - Journal of Problems in Computer Science and …, 2024 - jpcsip.kaznu.kz
Porosity, absolute permeability, and diffusion coefficient are crucial characteristics governing
fluid flow in the porous media of geological formations. Determining these properties …

[HTML][HTML] Study of the efficiency of machine learning algorithms based on data of various rocks

BK Assilbekov, NY Kalzhanov, DA Bolysbek… - Kazakhstan journal for …, 2023 - vestnik-ngo.kz
Background: Absolute permeability plays an important role in studying the fluids flow in
porous media during the development of oil and gas reservoirs, the injection of CO 2 into …

Digital rock modeling of a terrigenous oil and gas reservoirs for predicting rock permeability with its fitting using machine learning

V Berezovsky, I Belozerov, Y Bai… - … Days, RuSCDays 2019 …, 2019 - Springer
In the process of mathematical modeling of the macroscopic properties of porous media, the
problem of 3D-reconstruction of the core microstructure using machine learning apparatus …

[PDF][PDF] Application of deep learning technologies for studying thin sections on the example of Usinsk oil field

NA Popov, IS Putilov, AA Gulyaeva - OF THE TOMSK POLYTECHNIC …, 2020 - core.ac.uk
The article is devoted to development of methodological techniques for application of
machine learning technologies, including deep learning, to the problems of in-depth …

Multiple regressions and ann techniques to predict permeability from pore structure for terrigenous reservoirs, west-shebelynska area

V Antoniuk, I Bezrodna, O Petrokushyn - Monitoring 2019, 2019 - earthdoc.org
In the processes of exploration, allocation of producing intervals, and development of
hydrocarbon deposits, the important part is the accurate determination of the poro-perm …

Convolutional Neural Networks for the Classification of the Microstructure of Tight Sandstone

AG Reyna Flores, Q Fisher, P Lorinczi - International Petroleum …, 2021 - onepetro.org
Tight gas sandstone reservoirs vary widely in terms of rock type, depositional environment,
mineralogy and petrophysical properties. For this reason, estimating their permeability is a …

The application of machine learning methods for predicting porosity of rocks based on data of x-ray fluorescence analysis and gamma-ray spectrometry (Russian)

SV Shadrina, AA Shadrin - Oil Industry Journal, 2018 - onepetro.org
The PDF file of this paper is in Russian. Developing of the non-traditional hydrocarbon
reservoirs and underground water deposits allotted a number of tasks to specialists the …

Application of artificial neural network to predict permeability value of the reservoir rock

G Yasmaniar, S Prakoso… - Journal of Physics …, 2019 - iopscience.iop.org
Permeability is an important reservoir property but it is difficult to predict. An accurate
measurement of permeability values can be obtained from core data analysis. However, this …

Machine learning in reservoir permeability prediction and modelling of fluid flow in porous media

AB Zolotukhin, AT Gayubov - IOP Conference Series: Materials …, 2019 - iopscience.iop.org
Reliable data on the properties of the porous medium are necessary for the correct
description of the process of displacing hydrocarbons from the reservoirs and forecasting …