Geophysical logging series are valuable geological data that record the physical and
chemical information of borehole walls and in-situ formations, and are widely used by …

Numerous borehole logging datasets gathered for commercial and scientific purposes are
available around the globe. However, studies valorising the chronostratigraphic potential of …

This research aims to explore the application of an unsupervised machine learning and
inverse modeling-based methods to map the aquifers geometry and investigate the …

Cluster analysis is a valuable data analysis and data mining technique. Nature-inspired
population-based metaheuristics are promising search methods for solving optimization …

Cluster analysis by k-means algorithm by R programmingis the scope of the current paper.
The study assesses the similarity ofthe sampling data derived from the GIS project by …

The Hungarian water management plan has lately identified 185 groundwater bodies based
on the concepts given by the European Water Framework Directive. Achieving and …

A novel clustering method is applied to well logs for improved rock type identification in
hydrocarbon formations. For grouping the objects in the multi-dimensional data space, we …

The classification of low permeability-tight reservoirs is the premise of development. The
deep reservoir of Shahejie 3 member contains rich low permeability-tight reserves, but the …

This research proposes an innovative approach utilizing geophysical well logging data
analyzed with multiple machine learning (ML) methods including, self-organizing maps …

Tight sandstone reservoirs are a primary focus of research on the geological exploration of
petroleum. However, many reservoir classification criteria are of limited applicability due to …