Investigations on the relationship among the porosity, permeability and pore throat size of transition zone samples in carbonate reservoirs using multiple regression analysis, artificial neural network and adaptive neuro-fuzzy interface system

A new approach for porosity and permeability prediction from well logs using artificial neural network and curve fitting techniques: A case study of Niger Delta, Nigeria

(2020) Job G. Urang et al.   JOURNAL OF APPLIED GEOPHYSICS

A new correction method for mercury injection capillary pressure (MICP) to characterize the pore structure of shale

(2019) Yuxi Yu et al.   Journal of Natural Gas Science and Engineering

Analysis of pore size distribution and fractal dimension in tight sandstone with mercury intrusion porosimetry

(2019) Fuyong Wang et al.   Results in Physics

Prediction of reservoir quality using well logs and seismic attributes analysis with artificial neural network: A case study from Farrud reservoir, Al-Ghani field, Libya

(2018) Abdulaziz M. Abdulaziz et al.   JOURNAL OF APPLIED GEOPHYSICS

New insights into the prediction of heterogeneous carbonate reservoir permeability from well logs using artificial intelligence network

(2017) Salaheldin Elkatatny et al.   NEURAL COMPUTING & APPLICATIONS

Neuro-fuzzy system to predict permeability and porosity from well log data: A case study of Hassi R׳Mel gas field, Algeria

(2014) Tahar Aïfa et al.   JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING