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Implementation of SVM framework to estimate PVT properties of reservoir oil

Rafiee Taghanaki, S ; Sharif University of Technology | 2013

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  1. Type of Document: Article
  2. DOI: 10.1016/j.fluid.2013.02.012
  3. Publisher: 2013
  4. Abstract:
  5. Through this work, a novel mathematical-based approach was proposed to develop reliable models for calculation of PVT properties of crude oils at various reservoir conditions. For this purpose, a new soft computing approach namely Least Square Support Vector Machine (LSSVM) modeling optimized with Coupled Simulated Annealing (CSA) optimization technique was implemented. The constructed models are evaluated by carrying out extensive experimental data reported in open literature. Results obtained by the proposed models were compared with the corresponding experimental values. Moreover, in-depth comparative studies have been carried out between these models and all other predictive models. The results indicate that the proposed models are more robust, reliable and efficient than existing techniques for prediction of PVT properties. Results from present research show that implementation of CSA-LSSVM in crude oil PVT calculations can lead to more accurate and reliable estimation of reservoir oil PVT properties
  6. Keywords:
  7. Coupled Simulated Annealing ; Empirical correlation ; Least Square Support Vector Machine ; Oil formation volume factor ; Comparative studies ; Empirical correlations ; Least square support vector machines ; Oil formation volume factors ; Optimization techniques ; Reservoir conditions ; Saturation pressure ; Soft computing approaches ; Crude oil ; Petroleum analysis ; Simulated annealing ; Soft computing ; Support vector machines ; Petroleum reservoir engineering
  8. Source: Fluid Phase Equilibria ; Volume 346 , May , 2013 , Pages 25-32 ; 03783812 (ISSN)
  9. URL: http://www.sciencedirect.com/science/article/pii/S0378381213000940