Deep convolutions for in-depth automated rock typing

EE Baraboshkin, LS Ismailova, DM Orlov… - Computers & …, 2020 - Elsevier
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 method …

Faciesvit: Vision transformer for an improved core lithofacies prediction

A Koeshidayatullah, S Al-Azani… - Frontiers in Earth …, 2022 - frontiersin.org
Lithofacies classification is a fundamental step to perform depositional and reservoir
characterizations in the subsurface. However, such a classification is often hindered by …

MudrockNet: Semantic segmentation of mudrock SEM images through deep learning

A Bihani, H Daigle, JE Santos, C Landry… - Computers & …, 2022 - Elsevier
Segmentation and analysis of individual pores and grains of mudrocks from scanning
electron microscope images is non-trivial because of imaging artifacts, variation in pixel …

Technology predictions for arctic hydrocarbon development: Digitalization potential

N Tretyakov, A Cherepovitsyn… - … Transformation: A New …, 2021 - Springer
A key factor in the development of the Arctic is the projects aimed at the development of oil
and gas-bearing offshore and onshore fields, whose reserves are estimated at 13% of the …

Automated Full-Bore Core Description Application for Production Purposes. From an Idea to IT-Product

EE Baraboshkin, AE Demidov… - Data Science in Oil …, 2021 - earthdoc.org
The automatization is a modern trend in various field of geology. In this work we present a
system which were constructed based on convolutional neural network (CNN) for automated …

Foundational Study of Artificial Intelligence Reservoir Simulation by Integrating Digital Core Technology and Logging Data to Optimise Recovery

A Lener - Abu Dhabi International Petroleum Exhibition and …, 2022 - onepetro.org
In strategising development of hydrocarbon reservoirs, substantial uncertainty in recovery
potential is often attributed to subsurface heterogeneity. Challenged reservoir …

СИСТЕМА АВТОМАТИЧЕСКОГО ОПИСАНИЯ КЕРНА В ПРОИЗВОДСТВЕННОМ ПРОЦЕССЕ. ОПЫТ ПРИМЕНЕНИЯ

ЕЕ Барабошкин, ЕА Панченко, АЕ Демидов… - Пути реализации …, 2022 - elibrary.ru
Текущий уровень технологий позволяет автоматизировать и облегчить выполнение
многих задач. В работе представлен опыт применения и внедрения технологии …

СОЗДАНИЕ И ПРОВЕРКА МОДЕЛИ ЭКСПРЕСС-КЛАССИФИКАЦИИ КЕРНА КАК СРЕДСТВО БЫСТРОЙ ОЦЕНКИ ПЕРСПЕКТИВНОСТИ МЕСТОРОЖДЕНИЯ

ЕЕ Барабошкин, АЕ Демидов, ДМ Орлов… - … технологии: наука и …, 2022 - elibrary.ru
Целью работы является улучшение понимания распространения полезных компонент
в объеме месторождения за счёт автоматизированного детального описания керна …

Внедрение системы автоматического описания керна в производственный процесс. От идеи до продукта

ЕЕ Барабошкин, АЕ Демидов, ЕА Панченко… - … анализ данных в …, 2021 - elibrary.ru
The automatization is a modern trend in various field of geology. In this work we present a
system which were constructed based on convolutional neural network (CNN) for automated …