Conventional and machine learning improved prediction of hydrocarbon density using volume-translation at high-pressure high-temperature conditions
Author:
Affiliation:
1. Department of Petroleum Engineering, Covenant University, Ota, Nigeria
2. Department of Petroleum Engineering, University of Wyoming, Laramie, USA
Publisher
Informa UK Limited
Subject
Energy Engineering and Power Technology,Fuel Technology,Nuclear Energy and Engineering,Renewable Energy, Sustainability and the Environment
Link
https://www.tandfonline.com/doi/pdf/10.1080/15567036.2021.1915433
Reference33 articles.
1. Prediction of hydrocarbon densities at extreme conditions using volume-translated SRK and PR equations of state fit to high temperature, high pressure PVT data
2. Measurements and modeling of high-temperature, high-pressure density for binary mixtures of propane with n-decane and propane with n-eicosane
3. Estimating Optimal Transformations for Multiple Regression and Correlation
4. A Reference Equation of State for the Thermodynamic Properties of Ethane for Temperatures from the Melting Line to 675 K and Pressures up to 900 MPa
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