91 citations · 165 across the 4 of their papers we have counts for
4 papers
Estimating oil recovery factor using machine learning: Applications of XGBoost classification
Alireza Roustazadeh, Behzad Ghanbarian, Frank Male +3
In petroleum engineering, it is essential to determine the ultimate recovery factor, RF, particularly before exploitation and exploration. However, accurately estimating requires d…
Estimating oil and gas recovery factors via machine learning: Database-dependent accuracy and reliability
Alireza Roustazadeh, Behzad Ghanbarian, Mohammad B. Shadmand +2
With recent advances in artificial intelligence, machine learning (ML) approaches have become an attractive tool in petroleum engineering, particularly for reservoir characterizati…
Scale-Dependent Pedotransfer Functions Reliability for Estimating Saturated Hydraulic Conductivity
Behzad Ghanbarian, Vahid Taslimitehrani, Yakov A. Pachepsky
Saturated hydraulic conductivity Ksat is a fundamental characteristic in modeling flow and contaminant transport in soils and sediments. Therefore, many models have been developed…
Measurement Scale Effect on Prediction of Soil Water Retention Curve and Saturated Hydraulic Conductivity
Behzad Ghanbarian, Vahid Taslimitehrani, Guozhu Dong +1
Soil water retention curve (SWRC) and saturated hydraulic conductivity (SHC) are key hydraulic properties for unsaturated zone hydrology and groundwater. In particular, SWRC provid…