Geometallurgy is an important addition to any evaluation project or mining operation. As an
integrated approach, it establishes 3D models which enable the optimisation of net present …

In recent years, geoscientists have been employing machine learning techniques to
automate lithological identification by integrating well logging data. However, in geologically …

Effective identification of lithology using well logs is one of the most important steps for
reservoir characterization. A lot of methods have been developed to identify lithology …

Lithology prediction, especially for reservoirs consisting of complex lithologies, is universally
considered as a critical underlying task for petroleum exploration, because lithological data …

This research aims to enhance the classification of the rock mass in underground mining, a
common problem due to geological alterations that do not fit existing methods. Artificial …

The collection of sensor-based data is dramatically increased in the mining industry. One of
the widely used applications of the collected data is to identify rock domains and to estimate …

Lithology identification is one of the keys to understand the nature of hydrocarbon reservoir.
Deep learning has become a popular and reliable method for image classification and in …

A separator and multiphase flow meters are considered the most accurate tools used to
measure the surface oil flow rates. However, these tools are expensive and time consuming …

In the banded iron formation-hosted iron ore deposits in the Hamersley Range of Western
Australia, the stratigraphic boundaries are generally modelled using data from exploration …

Bubble point pressure and gas solubility are considered vital pressure-volume-temperature
properties of crude oil samples as both play a significant role in reservoir and production …