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Petroleum Science and Technology Volume 31, 2013 - Issue 9
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Original Articles

Prediction of Asphaltene Precipitation in Live and Tank Crude Oil Using Gaussian Process Regression

H. Rostami Department of Electrical Engineering, School of Engineering, Persian Gulf University, Bushehr, Iran
&
A. Khaksar Manshad Department of Chemical Engineering, School of Engineering, Persian Gulf University, Bushehr, Iran
Pages 913-922 | Received 31 Aug 2010, Accepted 08 Oct 2010, Published online: 08 Apr 2013

Citations (6)

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Read on this site (1)

A. K. Manshad & H. Rostami. (2015) Prediction of Wax Precipitation in Crude Oil Systems Using Gaussian Processes. Energy Sources, Part A: Recovery, Utilization, and Environmental Effects 37:1, pages 84-91.
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Articles from other publishers (5)

Fahd Saeed Alakbari, Mysara Eissa Mohyaldinn, Mohammed Abdalla Ayoub, Ali Samer Muhsan & Ibnelwaleed A. Hussein. (2023) A robust Gaussian process regression-based model for the determination of static Young’s modulus for sandstone rocks. Neural Computing and Applications 35:21, pages 15693-15707.
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Ali Qasim & Bhajan Lal. 2023. Machine Learning and Flow Assurance in Oil and Gas Production. Machine Learning and Flow Assurance in Oil and Gas Production 81 103 .
David Onalo, Sunday Adedigba, Olalere Oloruntobi, Faisal Khan, Lesley A. James & Stephen Butt. (2020) Data-driven model for shear wave transit time prediction for formation evaluation. Journal of Petroleum Exploration and Production Technology 10:4, pages 1429-1447.
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S. Alimohammadi, Javad Sayyad Amin & E. Nikooee. (2015) Estimation of asphaltene precipitation in light, medium and heavy oils: experimental study and neural network modeling. Neural Computing and Applications 28:4, pages 679-694.
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Abbas Khaksar Manshad, Habib Rostami, Hojjat Rezaei & Seyed Moein Hosseini. (2015) Application of Artificial Neural Network-Particle Swarm Optimization Algorithm for Prediction of Asphaltene Precipitation During Gas Injection Process and Comparison With Gaussian Process Algorithm. Journal of Energy Resources Technology 137:6.
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