Employing Statistical Algorithms and Clustering Techniques to Assess Lithological Facies for Identifying Optimal Reservoir Rocks: A Case Study of the Mansouri …

SH Eftekhari, M Memariani, Z Maleki, M Aleali… - Minerals, 2024 - mdpi.com
The crucial parameters influencing drilling operations, reservoir production behavior, and
well completion are lithology and reservoir rock. This study identified optimal reservoir rocks …

Hydraulic flow unit and rock types of the Asmari Formation, an application of flow zone index and fuzzy C-means clustering methods

SH Eftekhari, M Memariani, Z Maleki, M Aleali… - Scientific Reports, 2024 - nature.com
Rock types are the reservoir's most essential properties for special facies modeling in a
defined range of porosity and permeability. This study used clustering techniques to identify …

[HTML][HTML] Spatial Characterisation of Groundwater systems using Fuzzy c-Mean Clustering: A Multi-parameter approach in Crystalline Aquifers

BE Akeredolu, KAN Adiat, GM Olayanju… - Results in Earth …, 2024 - Elsevier
Similarity based approaches to groundwater system characterization has proven to be of
great value in describing groundwater system in terms of assessment and prediction of …

A fuzzy C-means clustering approach for petrophysical characterization of lithounits in the North Singhbhum Mobile Belt, Eastern India

RC Arasada, S Kumar, GS Rao, A Biswas, PR Sahoo… - Acta Geophysica, 2024 - Springer
The characterization of the various rock types through petrophysical data analysis is
essential for comprehending geological processes and enhancing the efficacy of …

Optimization of Survey Area for Auriferous-Sulphide Mineralization Using Integrated Geophysical Study: A Case Study from Gani-Kalva Fault Zone, Cuddapah Basin …

D Vijayakumar, MM Babu, GS Rao, G Rohit… - Pure and Applied …, 2023 - Springer
Abstract The Gani-Kalva fault (GKF), located in the western part of the Cuddapah basin,
India, is well known for hosting mineral deposits of iron, copper, and gold. In the present …

Integration of Airborne Geophysics Data with Fuzzy c-means Unsupervised Machine Learning Method to Predict Geological Map, Shahr-e-Babak Study Area …

M Jahantigh, HR Ramazi - Journal of Mining and Environment, 2025 - jme.shahroodut.ac.ir
Fuzzy c-means (FCM) is an unsupervised machine learning algorithm. This method assists
in integrating airborne geophysics data and extracting automatic geological map. This paper …