With the advancement of machine learning and artificial intelligence, the automated
estimation of a bed's complex lithology has become one of the most crucial requirements in …

In this paper, we propose an unsupervised learning framework that aims at evaluating the
applicability of the broad domain knowledge from natural images and videos in assisting …

The growing demand for hydrocarbons has driven the exploration of riskier prospects in
depths, pressures, and temperatures. Substantial volumes of hydrocarbons lie within deep …

Featured Application This article demonstrates SQp and SQs methods as the new AVO
attributes that sensitive to determine facies and fluid analysis. Abstract Amplitude versus …

Characterization and evaluation of (oil and gas) reservoirs is typically achieved using a
combination of seismic and well data. It is therefore critical that the two data types are well …

Mineral resources play an important part in the development of a country. Pakistan being an
energy deficient country, is blessed with several energy mineral resources in the form of coal …

This review illustrates the most recent improvements and implementations of ANN in
characterizing reservoirs in different regions for faster understanding of young petroleum …

Abstract The Artificial Neural Network (ANN) is widely used to map and estimate reservoir
properties. Since ANN has the ability of non-linear computing and self-error correction, it …

A subsurface resistivity model is important in hydrocarbon exploration primarily in the
controlled-source electromagnetic (CSEM) method. CSEM forward modelling workflow uses …

The ultimate objective in the oil and gas industry is to find hydrocarbon (HC). Currently, the
common method for hydrocarbon identification and reservoir recognition on well log data is …