A systematic review of data science and machine learning applications to the oil and gas industry
This study offered a detailed review of data sciences and machine learning (ML) roles in
different petroleum engineering and geosciences segments such as petroleum exploration …
different petroleum engineering and geosciences segments such as petroleum exploration …
On the evaluation of the viscosity of nanofluid systems: Modeling and data assessment
A Hemmati-Sarapardeh, A Varamesh… - … and Sustainable Energy …, 2018 - Elsevier
Viscosity of nanofluids can significantly affect pumping power, pressure drop, workability of
the nanofluid as well as its convective heat transfer coefficient. Experimental measurements …
the nanofluid as well as its convective heat transfer coefficient. Experimental measurements …
Biochar performance evaluation for heavy metals removal from industrial wastewater based on machine learning: application for environmental protection
Industrial wastewaters contaminated with heavy and toxic metals cause serious risks to
human health and other forms of life. The performance of biochar for the elimination of heavy …
human health and other forms of life. The performance of biochar for the elimination of heavy …
Machine learning assisted predictions for hydrogen storage in metal-organic frameworks
Metal organic frameworks (MOFs) have been studied vastly for hydrogen storage purposes
due to their unique properties. In the present work hydrogen storage capacity is modeled …
due to their unique properties. In the present work hydrogen storage capacity is modeled …
Application of Artificial Intelligence-based predictive methods in Ionic liquid studies: A review
Comprehensive experimental investigation and accurate predictive models are required to
understand the dynamics in Ionic liquid (IL) properties. Examples of these predictive models …
understand the dynamics in Ionic liquid (IL) properties. Examples of these predictive models …
Determination of bubble point pressure & oil formation volume factor of crude oils applying multiple hidden layers extreme learning machine algorithms
An important requirement of reservoir management is to understand the properties of
reservoir fluids and dependent phase behaviors. This makes it possible to determine the …
reservoir fluids and dependent phase behaviors. This makes it possible to determine the …
Comprehensive outlook into critical roles of pressure, volume, and temperature (PVT) and phase behavior on the exploration and development of shale oil
B Liu, S Gao, E Mohammadian… - Energy & …, 2022 - ACS Publications
Shale oil has received increasing attention as an essential replacement for conventional oil
resources. Shale oil recovery is a complex process controlled by interactions of many factors …
resources. Shale oil recovery is a complex process controlled by interactions of many factors …
Artificial neural network, support vector machine, decision tree, random forest, and committee machine intelligent system help to improve performance prediction of …
A large body of experimental research supports the effectiveness of Low Salinity Water
Injection (LSWI) for enhanced oil recovery from carbonate reservoirs in laboratory scale …
Injection (LSWI) for enhanced oil recovery from carbonate reservoirs in laboratory scale …
[HTML][HTML] Predicting thermal conductivity of carbon dioxide using group of data-driven models
MN Amar, AJ Ghahfarokhi, N Zeraibi - Journal of the Taiwan Institute of …, 2020 - Elsevier
Thermal conductivity of carbon dioxide (CO 2) is a vital thermophysical parameter that
significantly affects the heat transfer modeling related to CO 2 transportation, pipelines …
significantly affects the heat transfer modeling related to CO 2 transportation, pipelines …
New smart models for minimum fluidization velocity forecasting in the tapered fluidized beds based on particle size distribution
The most important design parameter of “minimum fluidization velocity” in tapered fluidized
beds is studied by robust smart models focusing on the particle size distribution. The smart …
beds is studied by robust smart models focusing on the particle size distribution. The smart …