Experimental investigation and intelligent modeling of pore structure changes in type III kerogen-rich shale artificially matured by hydrous and anhydrous pyrolysis
B Liu, MR Mohammadi, Z Ma, L Bai, L Wang, Z Wen… - Energy, 2023 - Elsevier
The occurrence and enrichment of shale plays are highly controlled by pore characteristics
of the formation. In this study, an immature sample rich in kerogen type III from the …
of the formation. In this study, an immature sample rich in kerogen type III from the …
Machine learning prediction of methane, nitrogen, and natural gas mixture viscosities under normal and harsh conditions
The accurate estimation of gas viscosity remains a pivotal concern for petroleum engineers,
exerting substantial influence on the modeling efficacy of natural gas operations. Due to …
exerting substantial influence on the modeling efficacy of natural gas operations. Due to …
Computational prediction of the drilling rate of penetration (ROP): A comparison of various machine learning approaches and traditional models
E Brenjkar, EB Delijani - Journal of Petroleum Science and Engineering, 2022 - Elsevier
Rate of penetration (ROP) prediction, can assist precise planning of drilling operations and
can reduce drilling costs. However, easy estimation of this key factor by traditional or …
can reduce drilling costs. However, easy estimation of this key factor by traditional or …
[HTML][HTML] Integrating experimental study and intelligent modeling of pore evolution in the Bakken during simulated thermal progression for CO2 storage goals
C Wang, B Liu, MR Mohammadi, L Fu, E Fattahi… - Applied Energy, 2024 - Elsevier
Pore characteristics of the formation exert significant control over both the development and
enrichment of shale plays, as well as CO 2 storage capacity of shale reservoirs. This …
enrichment of shale plays, as well as CO 2 storage capacity of shale reservoirs. This …
Seizure detection based on improved genetic algorithm optimized multilayer network
Y **ong, F Dong, D Wu, L Jiang, J Liu, B Li - IEEE Access, 2022 - ieeexplore.ieee.org
With the increasment of epilepsy patients, traditional epileptic seizure recognition is
generally completed by encephalography (EEG) technicians, which is time-consuming and …
generally completed by encephalography (EEG) technicians, which is time-consuming and …
Compositional modeling of gas-condensate viscosity using ensemble approach
In gas-condensate reservoirs, liquid dropout occurs by reducing the pressure below the dew
point pressure in the area near the wellbore. Estimation of production rate in these …
point pressure in the area near the wellbore. Estimation of production rate in these …
Modeling liquid rate through wellhead chokes using machine learning techniques
MS Dabiri, F Hadavimoghaddam, S Ashoorian… - Scientific Reports, 2024 - nature.com
Precise measurement and prediction of the fluid flow rates in production wells are crucial for
anticipating the production volume and hydrocarbon recovery and creating a steady and …
anticipating the production volume and hydrocarbon recovery and creating a steady and …
On the evaluation of surface tension of biodiesel
F Rezaei, MR Arab Juneghani… - Scientific Reports, 2024 - nature.com
Over time, with the increase in population and the subsequent increase in energy
consumption and also due to the non-renewability of fossil fuels, the study of alternative …
consumption and also due to the non-renewability of fossil fuels, the study of alternative …
Performance evaluation of ferro-fluids flooding in enhanced oil recovery operations based on machine learning
The process of enhanced oil recovery (EOR) and core flooding involves various challenges
such as preserving cores, configuring experiment setup, scaling from the laboratory to the …
such as preserving cores, configuring experiment setup, scaling from the laboratory to the …
Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms.
Abstract Radial Basis Function Neural Network (RBFNN) ensembles have long suffered
from non-efficient training, where incorrect parameter settings can be computationally …
from non-efficient training, where incorrect parameter settings can be computationally …