Applying ANN, ANFIS, and LSSVM Models for Estimation of Acid Solvent Solubility in Supercritical CO
A Bemani, A Baghban, S Shamshirband… - arXiv preprint arXiv …, 2019 - arxiv.org
In the present work, a novel and the robust computational investigation is carried out to
estimate solubility of different acids in supercritical carbon dioxide. Four different algorithms …
estimate solubility of different acids in supercritical carbon dioxide. Four different algorithms …
Modeling CO2 wettability behavior at the interface of brine/CO2/mineral: Application to CO2 geo-sequestration
Carbon capture and storage (CCS) has been introduced as an effective method for
reduction of CO 2 emissions to the atmosphere. While different aspects and controlling …
reduction of CO 2 emissions to the atmosphere. While different aspects and controlling …
Applying Monte Carlo dropout to quantify the uncertainty of skip connection-based convolutional neural networks optimized by big data
Although Deep Learning (DL) models have been introduced in various fields as effective
prediction tools, they often do not care about uncertainty. This can be a barrier to their …
prediction tools, they often do not care about uncertainty. This can be a barrier to their …
Modeling of kinetic adsorption of natural surfactants on sandstone minerals: Spotlight on accurate prediction and data evaluation
Surfactant injection is a tertiary enhanced oil recovery (EOR) method which aims to improve
trapped oil production by wettability alteration of rock surface and also interfacial tension …
trapped oil production by wettability alteration of rock surface and also interfacial tension …
Modeling apparent viscosity of waxy crude oils doped with polymeric wax inhibitors
M Madani, MK Moraveji, M Sharifi - Journal of Petroleum Science and …, 2021 - Elsevier
Wax precipitation which frequently occurs throughout transportation and production of waxy
crude oils results in various pitfalls including wax deposition, gel formation, and flow …
crude oils results in various pitfalls including wax deposition, gel formation, and flow …
Predictive analytics for octane number: a novel hybrid approach of KPCA and GS-PSO-SVR model
B Li, C Qin - IEEE Access, 2021 - ieeexplore.ieee.org
Octane number is the most important indicator of reflecting the combustion performance, and
a great deal of research has been devoted to improving it. In this paper, a new analytical …
a great deal of research has been devoted to improving it. In this paper, a new analytical …
Prediction of dynamic viscosity of n-alkanes at high pressures using a rigorous approach
A Daryasafar, K Shahbazi - Petroleum Science and Technology, 2018 - Taylor & Francis
An adaptive neuro-fuzzy interference system has been developed for estimating the
dynamic viscosity of n-alkanes in a wide range of operating conditions. In this study, for the …
dynamic viscosity of n-alkanes in a wide range of operating conditions. In this study, for the …
Modeling of CO2-brine interfacial tension: Application to enhanced oil recovery
Development of reliable and accurate models to estimate carbon dioxide–brine interfacial
tension (IFT) is necessary, since its experimental measurement is time-consuming and …
tension (IFT) is necessary, since its experimental measurement is time-consuming and …
Novel robust Elman neural network-based predictive models for bubble point oil formation volume factor and solution gas–oil ratio using experimental data
K Kohzadvand, M Mahmoudi Kouhi, M Ghasemi… - Neural Computing and …, 2024 - Springer
Bubble point oil formation volume factor (B ob) and solution gas–oil ratio (R s) are two
crucial PVT parameters used for modeling and volumetric calculations in petroleum industry …
crucial PVT parameters used for modeling and volumetric calculations in petroleum industry …
Gas-oil gravity drainage mechanism in fractured oil reservoirs: surrogate model development and sensitivity analysis
M Madani, M Alipour - Computational Geosciences, 2022 - Springer
In this study, a surrogate model is developed based on single porosity modelling approach
to predict the gas-oil gravity drainage recovery curves. The single porosity model is …
to predict the gas-oil gravity drainage recovery curves. The single porosity model is …