Neural network protocol to predict interfacial tension for CO<sub>2</sub>/CH<sub>4</sub>/Water-Brine ternary systems under reservoir temperature and pressure ranges-Reference-Cited by-同舟云学术

Neural network protocol to predict interfacial tension for CO₂/CH₄/Water-Brine ternary systems under reservoir temperature and pressure ranges

Published:2022-01-11 Issue:2 Volume:40 Page:181-200
ISSN:1091-6466
Container-title:Petroleum Science and Technology
language:en
Short-container-title:Petroleum Science and Technology

Author:

Pereira Andréa da Silva¹^ORCID,Oliveira Arthur Reys Carvalho de¹,Silvino Pedro F. G.¹,Bastos-Neto Moises²,Lucena Sebastião M. P.¹^ORCID

Affiliation:

1. Laboratory of Modeling and 3D Visualization, Department of Chemical Engineering, Universidade Federal do Ceará, Fortaleza, CE, Brazil

2. Laboratório de Pesquisa em Adsorção e Captura de CO2, Department of Chemical Engineering, Universidade Federal do Ceará, Fortaleza, CE, Brazil

Publisher

Informa UK Limited

Subject

Geotechnical Engineering and Engineering Geology,Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering,General Chemistry

Link

https://www.tandfonline.com/doi/pdf/10.1080/10916466.2021.1991375

Reference35 articles.

1. Evolving artificial neural network and imperialist competitive algorithm for prediction oil flow rate of the reservoir

2. Interfacial Tension and Density of Water + Branched Hydrocarbon Binary Systems in the Range 303−343 K

3. Modeling of viscosity for mixtures of Athabasca bitumen and heavy n-alkane with LSSVM algorithm

4. Estimation of natural gases water content using adaptive neuro-fuzzy inference system

5. Application of LSSVM strategy to estimate asphaltene precipitation during different production processes

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