We analyze how artificial intelligence changes a significant part of the energy sector, the oil
and gas industry. We focus on the upstream segment as the most capital-intensive part of oil …

This paper presents a review of measurement while drilling (MWD) technology as applied to
the mining industry, describes its development path, provides a global review of literature on …

Abstract Machine learning models are often considered as black-box solutions which is one
of the main reasons why they are still not widely used in operation of process engineering …

Abstract The Petaflops supercomputer “Zhores” recently launched in the “Center for
Computational and Data-Intensive Science and Engineering”(CDISE) of Skolkovo Institute of …

In this paper, the application of deep learning in the mining and processing of ores is
reviewed. Deep learning is strongly impacting the development of sensor systems …

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 …

Rock type classification is one of the most crucial steps of geological and geotechnical core
logging. In conventional core logging, rock type classification is subjective and time …

Tunnels in cold regions will encounter serious frost damage during operation. Based on the
Tongsheng Tunnel, an unsteady heat transfer model of surrounding rock, tunnel lining, and …

We develop a neural network (NN) architecture aimed at the midterm prediction of
earthquakes. Our data-based model aims to predict if an earthquake with a magnitude …

Despite the increasing global usage of Measure While Drilling (MWD) data in tunnel
projects, the application of machine learning (ML) techniques for real-time rock type …