Enhanced group method of data handling (GMDH) for permeability prediction based on the modified Levenberg Marquardt technique from well log data

AK Mulashani, C Shen, BM Nkurlu, CN Mkono… - Energy, 2022 - Elsevier
Permeability is the key variable for reservoir characterization used for estimating the flow
patterns and volume of hydrocarbons. Modern computer advancement has highlighted the …

Research Advances in Machine Learning Techniques in Gas Hydrate Applications

H Osei, CB Bavoh, B Lal - ACS omega, 2024 - ACS Publications
The complex modeling accuracy of gas hydrate models has been recently improved owing
to the existence of data for machine learning tools. In this review, we discuss most of the …

Prediction of hydrate formation temperature using gene expression programming

MN Amar - Journal of Natural Gas Science and Engineering, 2021 - Elsevier
The accurate determination of hydrate formation temperature (HFT) is an extremely vital step
in the context of designing processes containing hydrates. Due to the prohibitive time and …

Application of GMDH to Predict Pore Pressure from Well Logs Data: A Case Study from Southeast Sichuan Basin, China

MM Mgimba, S Jiang, EE Nyakilla… - Natural Resources …, 2023 - Springer
Pore pressure prediction is significant in the petroleum industry because, compared to direct
measurement, it is cost-effective and it generates an extensive range of data. Mathematical …

[HTML][HTML] The prospect of natural gas hydrate (NGH) under the vision of peak carbon dioxide emissions in China

N Wei, R Bai, J Zhao, Y Zhang, J Xue - Petroleum, 2021 - Elsevier
To achieve the goals of Peak Carbon Dioxide Emissions and Carbon Neutrality, China's
energy system will continue to accelerate the transition to a clean and low-carbon one. As …

Development of explicit models to predict methane hydrate equilibrium conditions in pure water and brine solutions: A machine learning approach

M Hosseini, Y Leonenko - Chemical Engineering Science, 2024 - Elsevier
An important phase in the design of processes involving gas hydrates is predicting the
hydrate formation conditions. In this study, three explicit correlations based on machine …

Deterministic tools to estimate induction time for methane hydrate formation in the presence of Luvicap 55 W solutions

M Zare, S Zendehboudi, MA Abdi - Journal of Molecular Liquids, 2022 - Elsevier
The formation of gas hydrates in offshore pipelines is a severe flow assurance issue. The
hydrates may form quickly in pipelines without any warning. Thus, effective remediation …

Wellbore temperature and pressure field in deep-water drilling and the applications in prediction of hydrate formation region

W Sun, N Wei, J Zhao, S Zhou, L Zhang, Q Li… - Frontiers in Energy …, 2021 - frontiersin.org
In the process of deep-water drilling, gas hydrate is easily formed in wellbores due to the low
temperature and high pressure environment. In this study, a new, systematic, and accurate …

An artificial neural network model for predicting the hydrate formation temperature

AN El-hoshoudy, A Ahmed, S Gomaa… - Arabian Journal for …, 2022 - Springer
Gas hydrate is one of the crucial flow assurance problems in the petroleum industry.
Inaccurate predictions of gas-hydrate conditions could lead to severe technical and …

[HTML][HTML] Evaluation of phase equilibrium conditions of clathrate hydrates in natural gas binary mixtures: Machine learning approach

R Behvandi, A Tatar, A Shokrollahi… - Geoenergy Science and …, 2023 - Elsevier
Hydrate formation temperature (T) is an important parameter for any industrial process that
deals with natural gas hydrates. In this study, the Group Method of Data Handling (GMDH) …