130 citations · 152 across the 7 of their papers we have counts for
7 papers
Core Box Image Recognition and its Improvement with a New Augmentation Technique
E. E. Baraboshkin, A. E. Demidov, D. M. Orlov +1
Most methods for automated full-bore rock core image analysis (description, colour, properties distribution, etc.) are based on separate core column analyses. The core is usually i…
On a workflow for efficient computation of the permeability of tight sandstones
Vladislav Pimanov, Vladislav Lukoshkin, Pavel Toktaliev +7
The paper presents a workflow for fast pore-scale simulation of single-phase flow in tight reservoirs typically characterized by low, multiscale porosity. Multiscale porosity impli…
End-to-end neural network approach to 3D reservoir simulation and adaptation
E. Illarionov, P. Temirchev, D. Voloskov +5
Reservoir simulation and adaptation (also known as history matching) are typically considered as separate problems. While a set of models are aimed at the solution of the forward s…
Machine learning for recovery factor estimation of an oil reservoir: a tool for de-risking at a hydrocarbon asset evaluation
Ivan Makhotin, Denis Orlov, Dmitry Koroteev +3
Well known oil recovery factor estimation techniques such as analogy, volumetric calculations, material balance, decline curve analysis, hydrodynamic simulations have certain limit…
Deep Convolutions for In-Depth Automated Rock Typing
E. E. Baraboshkin, L. S. Ismailova, D. M. Orlov +5
The description of rocks is one of the most time-consuming tasks in the everyday work of a geologist, especially when very accurate description is required. We here present a metho…
Prediction of Porosity and Permeability Alteration based on Machine Learning Algorithms
Andrei Erofeev, Denis Orlov, Alexey Ryzhov +1
The objective of this work is to study the applicability of various Machine Learning algorithms for prediction of some rock properties which geoscientists usually define due to spe…