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Data-driven model for the identification of the rock type at a drilling
  bit
v1v2v3 (latest)

Data-driven model for the identification of the rock type at a drilling bit

8 June 2018
Nikita Klyuchnikov
Alexey Zaytsev
A. Gruzdev
Georgiy Ovchinnikov
Ksenia Antipova
L. Ismailova
E. Muravleva
Evgeny Burnaev
A. Semenikhin
A. Cherepanov
V. Koryabkin
I. Simon
A. Tsurgan
Fedor V Krasnov
D. Koroteev
ArXiv (abs)PDFHTML

Papers citing "Data-driven model for the identification of the rock type at a drilling bit"

10 / 10 papers shown
Self-supervised similarity models based on well-logging data
Self-supervised similarity models based on well-logging dataSocial Science Research Network (SSRN), 2022
S. Egorov
Narek Gevorgyan
Alexey Zaytsev
SSL
171
5
0
26 Sep 2022
Making the black-box brighter: interpreting machine learning algorithm
  for forecasting drilling accidents
Making the black-box brighter: interpreting machine learning algorithm for forecasting drilling accidentsJournal of Petroleum Science and Engineering (JPSE), 2022
E. Gurina
Nikita Klyuchnikov
Ksenia Antipova
D. Koroteev
FAtt
299
12
0
06 Sep 2022
Hybrid Machine Learning Modeling of Engineering Systems -- A
  Probabilistic Perspective Tested on a Multiphase Flow Modeling Case Study
Hybrid Machine Learning Modeling of Engineering Systems -- A Probabilistic Perspective Tested on a Multiphase Flow Modeling Case Study
Timur Bikmukhametov
J. Jäschke
AI4CE
153
0
0
18 May 2022
Recurrent Convolutional Neural Networks help to predict location of
  Earthquakes
Recurrent Convolutional Neural Networks help to predict location of EarthquakesIEEE Geoscience and Remote Sensing Letters (GRSL), 2020
Roma Kail
Alexey Zaytsev
Evgeny Burnaev
234
47
0
20 Apr 2020
Boosting algorithms in energy research: A systematic review
Boosting algorithms in energy research: A systematic review
Hristos Tyralis
Georgia Papacharalampous
301
71
0
01 Apr 2020
Application of Machine Learning to accidents detection at directional
  drilling
Application of Machine Learning to accidents detection at directional drillingJournal of Petroleum Science and Engineering (JPSE), 2019
E. Gurina
Nikita Klyuchnikov
Alexey Zaytsev
Galina Boeva
Ksenia Antipova
I. Simon
V. Makarov
D. Koroteev
291
59
0
06 Jun 2019
Artificial Neural Network Surrogate Modeling of Oil Reservoir: a Case
  Study
Artificial Neural Network Surrogate Modeling of Oil Reservoir: a Case StudyInternational Symposium on Neural Networks (ISNN), 2019
O. Sudakov
D. Koroteev
B. Belozerov
Evgeny Burnaev
166
11
0
20 May 2019
Real-time data-driven detection of the rock type alteration during a
  directional drilling
Real-time data-driven detection of the rock type alteration during a directional drilling
Galina Boeva
Alexey Zaytsev
Nikita Klyuchnikov
A. Gruzdev
Ksenia Antipova
...
Evgeny Burnaev
A. Semenikhin
V. Koryabkin
I. Simon
D. Koroteev
225
34
0
27 Mar 2019
'Zhores' -- Petaflops supercomputer for data-driven modeling, machine
  learning and artificial intelligence installed in Skolkovo Institute of
  Science and Technology
'Zhores' -- Petaflops supercomputer for data-driven modeling, machine learning and artificial intelligence installed in Skolkovo Institute of Science and Technology
Igor Zacharov
R. Arslanov
Maxim Gunin
D. Stefonishin
Sergey Pavlov
O. Panarin
Anton K. Maliutin
S. Rykovanov
M. Fedorov
AI4CEVLM
247
198
0
20 Feb 2019
Gradient Boosting to Boost the Efficiency of Hydraulic Fracturing
Gradient Boosting to Boost the Efficiency of Hydraulic Fracturing
I. Makhotin
D. Koroteev
Evgeny Burnaev
AI4CE
311
31
0
05 Feb 2019
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