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09/06/2022
Making the black-box brighter: interpreting machine learning algorithm for forecasting drilling accidents
We present an approach for interpreting a black-box alarming system for ...
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03/22/2022
On a workflow for efficient computation of the permeability of tight sandstones
The paper presents a workflow for fast pore-scale simulation of single-p...
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03/10/2022
Forecasting the abnormal events at well drilling with machine learning
We present a data-driven and physics-informed algorithm for drilling acc...
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10/07/2020
Machine learning for recovery factor estimation of an oil reservoir: a tool for de-risking at a hydrocarbon asset evaluation
Well known oil recovery factor estimation techniques such as analogy, vo...
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06/06/2019
Failures detection at directional drilling using real-time analogues search
One of the main challenges in the construction of oil and gas wells is t...
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03/27/2019
Real-time data-driven detection of the rock type alteration during a directional drilling
During the directional drilling, a bit may sometimes go to a nonproducti...
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02/18/2019
Prediction of Porosity and Permeability Alteration based on Machine Learning Algorithms
The objective of this work is to study the applicability of various Mach...
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02/05/2019
Gradient Boosting to Boost the Efficiency of Hydraulic Fracturing
In this paper we present a data-driven model for forecasting the product...
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01/29/2019
Reconstruction of 3D Porous Media From 2D Slices
We propose a novel deep learning architecture for three-dimensional poro...
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01/08/2019
Deep Neural Networks Predicting Oil Movement in a Development Unit
We present a novel technique for assessing the dynamics of multiphase fl...
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06/08/2018
Data-driven model for the identification of the rock type at a drilling bit
In order to bridge the gap of more than 15m between the drilling bit and...
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03/02/2018