Improved Oil Viscosity Characterization by Low-Field NMR Using Feature Engineering and Supervised Learning Algorithms-Reference-Cited by-同舟云学术

Improved Oil Viscosity Characterization by Low-Field NMR Using Feature Engineering and Supervised Learning Algorithms

Published:2020-10-21 Issue:11 Volume:34 Page:13799-13813
ISSN:0887-0624
Container-title:Energy & Fuels
language:en
Short-container-title:Energy Fuels

Author:

Markovic Strahinja¹²^ORCID,Bryan Jonathan L.³,Ishimtsev Vladislav¹,Turakhanov Aman¹,Rezaee Reza²,Cheremisin Alexey¹,Kantzas Apostolos³,Koroteev Dmitry¹,Mehta Sudarshan A.³

Affiliation:

1. Center for Hydrocarbon Recovery, Skolkovo Institute of Science and Technology, Sikorsky Street 11, Moscow 121205, Russian Federation

2. Curtin University, Kent Street, Bentley, Perth, WA 6845, Australia

3. University of Calgary, Calgary, Alberta T2N 1N4, Canada

Publisher

American Chemical Society (ACS)

Subject

Energy Engineering and Power Technology,Fuel Technology,General Chemical Engineering

Link

https://pubs.acs.org/doi/pdf/10.1021/acs.energyfuels.0c02565

Reference65 articles.

1. Meyer, R.; Attanasi, E.; Freeman, P. Heavy Oil and Natural Bitumen Resources in Geological Basins of the World, Open-File Report 2007-1084; USGS, 2007; p 36.

2. Effects of asphaltene content on the heavy oil viscosity at different temperatures

3. Elucidating the 1H NMR Relaxation Mechanism in Polydisperse Polymers and Bitumen Using Measurements, MD Simulations, and Models

4. Interpretation of NMR Relaxation in Bitumen and Organic Shale Using Polymer–Heptane Mixes

5. Improved Correlations for Heavy-Oil Viscosity Prediction with NMR

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