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Prediction of air quality index using machine learning techniques: a comparative analysis
NS Gupta, Y Mohta, K Heda, R Armaan… - … and Public Health, 2023 - Wiley Online Library
An index for reporting air quality is called the air quality index (AQI). It measures the impact
of air pollution on a person's health over a short period of time. The purpose of the AQI is to …
of air pollution on a person's health over a short period of time. The purpose of the AQI is to …
Permeability prediction of heterogeneous carbonate gas condensate reservoirs applying group method of data handling
Carbonate petroleum reservoirs typically have lower permeabilities and recovery factors
than sandstone reservoirs, so the natural fractures they often incorporate have positive …
than sandstone reservoirs, so the natural fractures they often incorporate have positive …
Predicting shear wave velocity from conventional well logs with deep and hybrid machine learning algorithms
Shear wave velocity (VS) data from sedimentary rock sequences is a prerequisite for
implementing most mathematical models of petroleum engineering geomechanics …
implementing most mathematical models of petroleum engineering geomechanics …
Optimized machine learning models for natural fractures prediction using conventional well logs
Identifying and characterizing natural fractures is essential for understanding fluid flow and
drainage in many oil and gas reservoirs, particularly carbonate. The presence of fractures …
drainage in many oil and gas reservoirs, particularly carbonate. The presence of fractures …
Machine learning-a novel approach to predict the porosity curve using geophysical logs data: an example from the Lower Goru sand reservoir in the Southern Indus …
Porosity estimation is one of the essential issues in oil and natural gas industries to evaluate
the reservoir characteristics properly. Therefore, it is imperative to predict porosity with the …
the reservoir characteristics properly. Therefore, it is imperative to predict porosity with the …
[HTML][HTML] A robust approach to pore pressure prediction applying petrophysical log data aided by machine learning techniques
Determination of pore pressure (PP), a key reservoir parameter that is beneficial for
evaluating geomechanical parameters of the reservoir, is so important in oil and gas fields …
evaluating geomechanical parameters of the reservoir, is so important in oil and gas fields …
Novel hybrid machine learning optimizer algorithms to prediction of fracture density by petrophysical data
One of the challenges in reservoir management is determining the fracture density (FVDC)
in reservoir rock. Given the high cost of coring operations and image logs, the ability to …
in reservoir rock. Given the high cost of coring operations and image logs, the ability to …
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 …
M Ali, M Ehsan… - Geoenergy Science and …, 2023 - Elsevier
The present study aims to better understand the mineralogy and thermal structure of the
Yingxiu-Beichuan fault zone (YBFZ), Sichuan basin, China, which was lacking previously …
Yingxiu-Beichuan fault zone (YBFZ), Sichuan basin, China, which was lacking previously …
[HTML][HTML] Data driven models to predict pore pressure using drilling and petrophysical data
F Jafarizadeh, M Rajabi, S Tabasi, R Seyedkamali… - Energy Reports, 2022 - Elsevier
The mud weight window (MW) determination is one of the most important parameters in
drilling oil and gas wells, where accurate design can secure the drilled well and deliver a …
drilling oil and gas wells, where accurate design can secure the drilled well and deliver a …