130 citations · 132 across the 3 of their papers we have counts for
5 papers
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…
Application of Machine Learning to accidents detection at directional drilling
Ekaterina Gurina, Nikita Klyuchnikov, Alexey Zaytsev +5
We present a data-driven algorithm and mathematical model for anomaly alarming at directional drilling. The algorithm is based on machine learning. It compares the real-time drilli…
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…
Gradient Boosting to Boost the Efficiency of Hydraulic Fracturing
Ivan Makhotin, Dmitry Koroteev, Evgeny Burnaev
In this paper, we present a data-driven model for forecasting the production increase after hydraulic fracturing (HF). We use data from fracturing jobs performed at one of the Sibe…
Deep Neural Networks Predicting Oil Movement in a Development Unit
Pavel Temirchev, Maxim Simonov, Ruslan Kostoev +6
We present a novel technique for assessing the dynamics of multiphase fluid flow in the oil reservoir. We demonstrate an efficient workflow for handling the 3D reservoir simulation…