A PSO-ANFIS framework for prediction of density of bitumen diluted with solvents. (17th January 2018)

• Record Type: Journal Article
• Authors: Banashooshtari, Hooman; Ashtari Larki, Saeed; Shokrollahzadeh Behbahani, Hassan
• Is Part Of: Petroleum science and technology. Volume 36:Number 2(2018)
• Page Start: 122
• Page End: 129
• Publication Date: 2018-01-17
• Subjects: bitumen -- density -- ANFIS -- PSO -- prediction; Liquid fuels -- Periodicals; Petroleum -- Periodicals; 665.505
• DOI: 10.1080/10916466.2017.1407788
• Languages: English
• ISSNs: 1091-6466

Abstract

ABSTRACT: One of the important properties in petroleum engineering calculations in heavy oil reservoirs is the density of bitumen diluted with solvents. It is required in newly developed solvent based enhanced oil recovery methods. Hence, developing accurate models for prediction of this parameter is essential. To tackle this issue, this study presents an accurate model based on adaptive neuro-fuzzy inference system trained by particle swarm optimization (PSO-ANFIS) for estimation of density of bitumen diluted with solvents and hydrocarbon mixtures using experimental data from literature. The accuracy and reliability of results were evaluated by utilizing various statistical and graphical approaches and comparing the predictions of the developed model with literature models. The analysis showed that the PSO-ANFIS model is capable to predict the experimental data with acceptable error and high accuracy. The predictions of the PSO-ANFIS model were also better than the literature models.