Effective Thermal Conductivity Modeling of Sandstones: SVM Framework Analysis

Alireza Rostami, Mohammad Masoudi, Alireza Ghaderi-Ardakani, Milad Arabloo, Mahmood Amani

Research output: Contribution to journalArticle

28 Citations (Scopus)

Abstract

Among the most significant physical characteristics of porous media, the effective thermal conductivity (ETC) is used for estimating the thermal enhanced oil recovery process efficiency, hydrocarbon reservoir thermal design, and numerical simulation. This paper reports the implementation of an innovative least square support vector machine (LS-SVM) algorithm for the development of enhanced model capable of predicting the ETCs of dry sandstones. By means of several statistical parameters, the validity of the presented model was evaluated. The prediction of the developed model for determining the ETCs of dry sandstones was in excellent agreement with the reported data with a coefficient of determination value (Formula presented.) of 0.983 and an average absolute relative deviation of 0.35 %. Results from present research show that the proposed LS-SVM model is robust, reliable, and efficient in calculating the ETCs of sandstones.

Original languageEnglish
Article number59
JournalInternational Journal of Thermophysics
Volume37
Issue number6
DOIs
Publication statusPublished - 1 Jun 2016

Fingerprint

sandstones
thermal conductivity
oil recovery
estimating
hydrocarbons
deviation
coefficients
predictions
simulation

Keywords

  • Dry sandstone
  • Effective thermal conductivity (ETC)
  • Porous media
  • Support vector machine (SVM)

ASJC Scopus subject areas

  • Condensed Matter Physics

Cite this

Effective Thermal Conductivity Modeling of Sandstones : SVM Framework Analysis. / Rostami, Alireza; Masoudi, Mohammad; Ghaderi-Ardakani, Alireza; Arabloo, Milad; Amani, Mahmood.

In: International Journal of Thermophysics, Vol. 37, No. 6, 59, 01.06.2016.

Research output: Contribution to journalArticle

Rostami, Alireza ; Masoudi, Mohammad ; Ghaderi-Ardakani, Alireza ; Arabloo, Milad ; Amani, Mahmood. / Effective Thermal Conductivity Modeling of Sandstones : SVM Framework Analysis. In: International Journal of Thermophysics. 2016 ; Vol. 37, No. 6.
@article{4bdd395c80b74bb5a443e3d0a379931f,
title = "Effective Thermal Conductivity Modeling of Sandstones: SVM Framework Analysis",
abstract = "Among the most significant physical characteristics of porous media, the effective thermal conductivity (ETC) is used for estimating the thermal enhanced oil recovery process efficiency, hydrocarbon reservoir thermal design, and numerical simulation. This paper reports the implementation of an innovative least square support vector machine (LS-SVM) algorithm for the development of enhanced model capable of predicting the ETCs of dry sandstones. By means of several statistical parameters, the validity of the presented model was evaluated. The prediction of the developed model for determining the ETCs of dry sandstones was in excellent agreement with the reported data with a coefficient of determination value (Formula presented.) of 0.983 and an average absolute relative deviation of 0.35 {\%}. Results from present research show that the proposed LS-SVM model is robust, reliable, and efficient in calculating the ETCs of sandstones.",
keywords = "Dry sandstone, Effective thermal conductivity (ETC), Porous media, Support vector machine (SVM)",
author = "Alireza Rostami and Mohammad Masoudi and Alireza Ghaderi-Ardakani and Milad Arabloo and Mahmood Amani",
year = "2016",
month = "6",
day = "1",
doi = "10.1007/s10765-016-2057-x",
language = "English",
volume = "37",
journal = "International Journal of Thermophysics",
issn = "0195-928X",
publisher = "Springer New York",
number = "6",

}

TY - JOUR

T1 - Effective Thermal Conductivity Modeling of Sandstones

T2 - SVM Framework Analysis

AU - Rostami, Alireza

AU - Masoudi, Mohammad

AU - Ghaderi-Ardakani, Alireza

AU - Arabloo, Milad

AU - Amani, Mahmood

PY - 2016/6/1

Y1 - 2016/6/1

N2 - Among the most significant physical characteristics of porous media, the effective thermal conductivity (ETC) is used for estimating the thermal enhanced oil recovery process efficiency, hydrocarbon reservoir thermal design, and numerical simulation. This paper reports the implementation of an innovative least square support vector machine (LS-SVM) algorithm for the development of enhanced model capable of predicting the ETCs of dry sandstones. By means of several statistical parameters, the validity of the presented model was evaluated. The prediction of the developed model for determining the ETCs of dry sandstones was in excellent agreement with the reported data with a coefficient of determination value (Formula presented.) of 0.983 and an average absolute relative deviation of 0.35 %. Results from present research show that the proposed LS-SVM model is robust, reliable, and efficient in calculating the ETCs of sandstones.

AB - Among the most significant physical characteristics of porous media, the effective thermal conductivity (ETC) is used for estimating the thermal enhanced oil recovery process efficiency, hydrocarbon reservoir thermal design, and numerical simulation. This paper reports the implementation of an innovative least square support vector machine (LS-SVM) algorithm for the development of enhanced model capable of predicting the ETCs of dry sandstones. By means of several statistical parameters, the validity of the presented model was evaluated. The prediction of the developed model for determining the ETCs of dry sandstones was in excellent agreement with the reported data with a coefficient of determination value (Formula presented.) of 0.983 and an average absolute relative deviation of 0.35 %. Results from present research show that the proposed LS-SVM model is robust, reliable, and efficient in calculating the ETCs of sandstones.

KW - Dry sandstone

KW - Effective thermal conductivity (ETC)

KW - Porous media

KW - Support vector machine (SVM)

UR - http://www.scopus.com/inward/record.url?scp=84964282791&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84964282791&partnerID=8YFLogxK

U2 - 10.1007/s10765-016-2057-x

DO - 10.1007/s10765-016-2057-x

M3 - Article

AN - SCOPUS:84964282791

VL - 37

JO - International Journal of Thermophysics

JF - International Journal of Thermophysics

SN - 0195-928X

IS - 6

M1 - 59

ER -