233 citations · 483 across the 14 of their papers we have counts for
7 papers · 1 filter
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…
Real-time data-driven detection of the rock type alteration during a directional drilling
Evgenya Romanenkova, Alexey Zaytsev, Nikita Klyuchnikov +8
During the directional drilling, a bit may sometimes go to a nonproductive rock layer due to the gap about 20m between the bit and high-fidelity rock type sensors. The only way to…
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…
Reconstruction of 3D Porous Media From 2D Slices
Denis Volkhonskiy, Ekaterina Muravleva, Oleg Sudakov +4
In many branches of earth sciences, the problem of rock study on the micro-level arises. However, a significant number of representative samples is not always feasible. Thus the pr…