Abstract Nowadays Machine Learning approaches are getting popular in almost all the
domains of Engineering Applications. One such widely used approach is Artificial Neural …

Abstract Machine learning has emerged as a powerful tool in various fields, including
computer vision, natural language processing, and speech recognition. It can unravel …

An inversion algorithm is commonly used to estimate the elastic properties, such as P-wave
velocity (VP), S-wave velocity (VS), and density (ρ) of the earth's subsurface. Generally, the …

Oil/gas exploration, drilling, production, and reservoir management are challenging these
days since most oil and gas conventional sources are already discovered and have been …

The geological sequestration of CO2 in deep saline aquifers is one of the most effective
strategies to reduce greenhouse emissions from the stationary point sources of CO2 …

Artificial neural systems have been used in a variety of problems in the fields of science and
engineering. Here we describe a study of the applicability of neural networks to solving …

The rapid development of machine learning algorithms and the massive accumulation of
well data from continuous monitoring has enabled new applications in the oil and gas …

The seismic interpretation in Maari 3D prospect of the Taranaki basin in New Zealand based
on artificial neural network has brought out gas migration pathways from the source rock …

Deep learning algorithms have shown great potential in geophysical areas such as seismic
interpretation and seismic inversion. However, when applied to seismic inversion, high …

We describe a new method based on the Machine Learning (ML) technique for normal
moveout correction (NMO) and estimation of stacking velocity. A Recurrent Neural Network …