Review of recent advances in petroleum fluid properties and their representation
It is well-known that petroleum fluid properties (also known as Pressure-Temperature-
Volume-PVT) is needed for many petroleum engineering and other interdisciplinary …
Volume-PVT) is needed for many petroleum engineering and other interdisciplinary …
Hybrid machine learning algorithms to predict condensate viscosity in the near wellbore regions of gas condensate reservoirs
ARB Abad, S Mousavi, N Mohamadian… - Journal of Natural Gas …, 2021 - Elsevier
Gas condensate reservoirs display unique phase behavior and are highly sensitive to
reservoir pressure changes. This makes it difficult to determine their PVT characteristics …
reservoir pressure changes. This makes it difficult to determine their PVT characteristics …
Detection of faults in subsea pipelines by flow monitoring with regression supervised machine learning
This study investigates the relationship between pressure change, velocity change, and
temperature of crude oil through a pipeline and presents a method of using a regression …
temperature of crude oil through a pipeline and presents a method of using a regression …
Prediction of petroleum viscosity from molecular weight and density
Abstract 165 crude oils with viscosity, density, and molecular weight variation in the range
0.54–24135cP; 0.746–1.016 g/cm 3; 117–579 g/mol respectively were examined for …
0.54–24135cP; 0.746–1.016 g/cm 3; 117–579 g/mol respectively were examined for …
[HTML][HTML] Predicting physical properties of oxygenated gasoline and diesel range fuels using machine learning
Understanding the physical properties of distillate petroleum fuels like gasoline and diesel is
very critical to ensure the normal operation of internal combustion (IC) engines with regards …
very critical to ensure the normal operation of internal combustion (IC) engines with regards …
Prediction of molecular weight of petroleum fluids by empirical correlations and artificial neuron networks
The exactitude of petroleum fluid molecular weight correlations affects significantly the
precision of petroleum engineering calculations and can make process design and trouble …
precision of petroleum engineering calculations and can make process design and trouble …
New correlations to predict oil viscosity using data mining techniques
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 …
Prediction of refractive index of petroleum fluids by empirical correlations and ANN
The refractive index is an important physical property that is used to estimate the structural
characteristics, thermodynamic, and transport properties of petroleum fluids, and to …
characteristics, thermodynamic, and transport properties of petroleum fluids, and to …
Chain-based machine learning for full PVT data prediction
Building machine learning (ML) models based on pressure-volume-temperature (PVT) data
is of paramount importance to capture trends and predict fluid behavior in a very …
is of paramount importance to capture trends and predict fluid behavior in a very …
[HTML][HTML] Enhanced intelligent approach for determination of crude oil viscosity at reservoir conditions
Oil viscosity plays a prominent role in all areas of petroleum engineering, such as simulating
reservoirs, predicting production rate, evaluating oil well performance, and even planning for …
reservoirs, predicting production rate, evaluating oil well performance, and even planning for …