Prediction of dead oil viscosity: Machine learning vs. classical correlations
Dead oil viscosity is a critical parameter to solve numerous reservoir engineering problems
and one of the most unreliable properties to predict with classical black oil correlations …
and one of the most unreliable properties to predict with classical black oil correlations …
Reservoir oil viscosity determination using a rigorous approach
Viscosity of crude oil is a fundamental factor in simulating reservoirs, forecasting production
as well as planning thermal enhanced oil recovery methods which make its accurate …
as well as planning thermal enhanced oil recovery methods which make its accurate …
Toward reservoir oil viscosity correlation
A Hemmati-Sarapardeh, M Khishvand, A Naseri… - Chemical Engineering …, 2013 - Elsevier
Oil viscosity plays a key role in reservoir simulation and production forecasting, as well as
planning thermal enhanced oil recovery methods and these make its accurate determination …
planning thermal enhanced oil recovery methods and these make its accurate determination …
Assessment and development of heavy-oil viscosity correlations
Heavy oil always poses a great challenge to production and transportation systems due to
its high viscosity. This paper evaluates fourteen dead, eight saturated and nine under …
its high viscosity. This paper evaluates fourteen dead, eight saturated and nine under …
Predicting the condensate viscosity near the wellbore by ELM and ANFIS-PSO strategies
F Mousazadeh, MHT Naeem, R Daneshfar… - Journal of Petroleum …, 2021 - Elsevier
By lowering the pressure beneath the dew point as the result of production in gas
condensate (GC) reservoirs, liquid droplets are formed in the borehole zone. Accurate …
condensate (GC) reservoirs, liquid droplets are formed in the borehole zone. Accurate …
New correlations to predict oil viscosity using data mining techniques
E Bahonar, M Chahardowli, Y Ghalenoei… - Journal of Petroleum …, 2022 - Elsevier
Oil viscosity is used in any fluid transport calculation in both subsurface and surface
conditions. It is possible to determine oil viscosity from laboratory measurements or …
conditions. It is possible to determine oil viscosity from laboratory measurements or …
A further study in the prediction of viscosity for Iranian crude oil reservoirs by utilizing a robust radial basis function (RBF) neural network model
In this study, a robust radial basis function neural network (RBF-NN) is developed for
predicting Iranian crude oil viscosity in an extensive and precise way. Experimental data …
predicting Iranian crude oil viscosity in an extensive and precise way. Experimental data …
Machine learning-based improved pressure–volume–temperature correlations for black oil reservoirs
Abstract Pressure–volume–temperature (PVT) properties of crude oil are considered the
most important properties in petroleum engineering applications as they are virtually used in …
most important properties in petroleum engineering applications as they are virtually used in …
PVT correlations for Indian crude using artificial neural networks
S Dutta, JP Gupta - Journal of Petroleum Science and Engineering, 2010 - Elsevier
Correlations for bubble point pressure, solution gas–oil ratio (GOR), oil formation volume
factor (OFVF)(for both saturated and undersaturated crude) and viscosity (for both saturated …
factor (OFVF)(for both saturated and undersaturated crude) and viscosity (for both saturated …
Evaluation of empirically derived PVT properties for Pakistani crude oils
MA Mahmood, MA Al-Marhoun - Journal of Petroleum Science and …, 1996 - Elsevier
This study evaluates the most frequently used pressure-volume-temperature (PVT) empirical
correlations for Pakistani crude oil samples. The evaluation is performed by using an …
correlations for Pakistani crude oil samples. The evaluation is performed by using an …