Assessment of asphaltene deposition due to titration technique

Ali Chamkalani, Mahmood Amani, Mohammad Amin Kiani, Reza Chamkalani

Research output: Contribution to journalArticle

31 Citations (Scopus)

Abstract

Due to problems followed by asphaltene deposition, which cause many remedial processes and costs, it seemed necessary to develop equations for determining asphaltene precipitation quantitatively or qualitatively. In this study a new scaling equation as a function of temperature, molecular weight, and dilution ratio (solvent) has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of different precipitants (solvents). The proposed methodology utilizes least square support vector machines/regression (LSSVM/LSSVR) to perform nonlinear modeling. This paper proposes a new feature selection mechanism based on coupled simulated annealing (CSA) optimization in an attempt to tune the optimal parameters. CSA-LSSVM has the good capability of characterizing the nonlinear behavior. The performance of the proposed LSSVM algorithm is highly satisfactory and demonstrated by residuals and statistical indicator and was compared with previous works. The results showed its superiority to previous and highly dependent performance.

Original languageEnglish
Pages (from-to)72-80
Number of pages9
JournalFluid Phase Equilibria
Volume339
DOIs
Publication statusPublished - 15 Feb 2013

Fingerprint

Simulated annealing
Titration
titration
simulated annealing
Dilution
Support vector machines
Feature extraction
Molecular weight
dilution
regression analysis
molecular weight
methodology
costs
scaling
Costs
optimization
causes
Temperature
asphaltene
temperature

Keywords

  • Asphaltene precipitation
  • Coupled simulated annealing
  • Least square support vector machine
  • Scaling equation

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Physical and Theoretical Chemistry
  • Physics and Astronomy(all)

Cite this

Assessment of asphaltene deposition due to titration technique. / Chamkalani, Ali; Amani, Mahmood; Kiani, Mohammad Amin; Chamkalani, Reza.

In: Fluid Phase Equilibria, Vol. 339, 15.02.2013, p. 72-80.

Research output: Contribution to journalArticle

Chamkalani, Ali ; Amani, Mahmood ; Kiani, Mohammad Amin ; Chamkalani, Reza. / Assessment of asphaltene deposition due to titration technique. In: Fluid Phase Equilibria. 2013 ; Vol. 339. pp. 72-80.
@article{8d3f179f97a044e69da83408a761b46e,
title = "Assessment of asphaltene deposition due to titration technique",
abstract = "Due to problems followed by asphaltene deposition, which cause many remedial processes and costs, it seemed necessary to develop equations for determining asphaltene precipitation quantitatively or qualitatively. In this study a new scaling equation as a function of temperature, molecular weight, and dilution ratio (solvent) has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of different precipitants (solvents). The proposed methodology utilizes least square support vector machines/regression (LSSVM/LSSVR) to perform nonlinear modeling. This paper proposes a new feature selection mechanism based on coupled simulated annealing (CSA) optimization in an attempt to tune the optimal parameters. CSA-LSSVM has the good capability of characterizing the nonlinear behavior. The performance of the proposed LSSVM algorithm is highly satisfactory and demonstrated by residuals and statistical indicator and was compared with previous works. The results showed its superiority to previous and highly dependent performance.",
keywords = "Asphaltene precipitation, Coupled simulated annealing, Least square support vector machine, Scaling equation",
author = "Ali Chamkalani and Mahmood Amani and Kiani, {Mohammad Amin} and Reza Chamkalani",
year = "2013",
month = "2",
day = "15",
doi = "10.1016/j.fluid.2012.11.037",
language = "English",
volume = "339",
pages = "72--80",
journal = "Fluid Phase Equilibria",
issn = "0378-3812",
publisher = "Elsevier",

}

TY - JOUR

T1 - Assessment of asphaltene deposition due to titration technique

AU - Chamkalani, Ali

AU - Amani, Mahmood

AU - Kiani, Mohammad Amin

AU - Chamkalani, Reza

PY - 2013/2/15

Y1 - 2013/2/15

N2 - Due to problems followed by asphaltene deposition, which cause many remedial processes and costs, it seemed necessary to develop equations for determining asphaltene precipitation quantitatively or qualitatively. In this study a new scaling equation as a function of temperature, molecular weight, and dilution ratio (solvent) has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of different precipitants (solvents). The proposed methodology utilizes least square support vector machines/regression (LSSVM/LSSVR) to perform nonlinear modeling. This paper proposes a new feature selection mechanism based on coupled simulated annealing (CSA) optimization in an attempt to tune the optimal parameters. CSA-LSSVM has the good capability of characterizing the nonlinear behavior. The performance of the proposed LSSVM algorithm is highly satisfactory and demonstrated by residuals and statistical indicator and was compared with previous works. The results showed its superiority to previous and highly dependent performance.

AB - Due to problems followed by asphaltene deposition, which cause many remedial processes and costs, it seemed necessary to develop equations for determining asphaltene precipitation quantitatively or qualitatively. In this study a new scaling equation as a function of temperature, molecular weight, and dilution ratio (solvent) has been developed. This equation can be used to determine the weight percent of precipitated asphaltene in the presence of different precipitants (solvents). The proposed methodology utilizes least square support vector machines/regression (LSSVM/LSSVR) to perform nonlinear modeling. This paper proposes a new feature selection mechanism based on coupled simulated annealing (CSA) optimization in an attempt to tune the optimal parameters. CSA-LSSVM has the good capability of characterizing the nonlinear behavior. The performance of the proposed LSSVM algorithm is highly satisfactory and demonstrated by residuals and statistical indicator and was compared with previous works. The results showed its superiority to previous and highly dependent performance.

KW - Asphaltene precipitation

KW - Coupled simulated annealing

KW - Least square support vector machine

KW - Scaling equation

UR - http://www.scopus.com/inward/record.url?scp=84871456988&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84871456988&partnerID=8YFLogxK

U2 - 10.1016/j.fluid.2012.11.037

DO - 10.1016/j.fluid.2012.11.037

M3 - Article

VL - 339

SP - 72

EP - 80

JO - Fluid Phase Equilibria

JF - Fluid Phase Equilibria

SN - 0378-3812

ER -