EconPapers    
Economics at your fingertips  
 

Workflows to Optimally Select Undersaturated Oil Viscosity Correlations for Reservoir Flow Simulations

Sofianos Panagiotis Fotias, Andreas Georgakopoulos and Vassilis Gaganis ()
Additional contact information
Sofianos Panagiotis Fotias: Department of Mineralogy-Petrology-Economic Geology, School of Geology, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Andreas Georgakopoulos: Department of Mineralogy-Petrology-Economic Geology, School of Geology, Aristotle University of Thessaloniki, 541 24 Thessaloniki, Greece
Vassilis Gaganis: Mining and Metallurgical Engineering, National Technical University of Athens, 157 73 Athens, Greece

Energies, 2022, vol. 15, issue 24, 1-23

Abstract: Undersaturated oil viscosity is one of the most important PVT parameters to be measured and/or predicted in a fluid sample. Since direct experimental measurements are expensive and time-costly, prediction methods are essential. In this work, viscosity data from more than five hundred fluid reports are utilized, and all correlation methods available in the literature and implemented in commercial software for reservoir and production engineering calculations, including fracked systems, are evaluated against the dataset. The results of this work are intended to set up workflows that give insight as to which method should be selected when running flow simulations, with emphasis on complex simulations such as in the case of EOR. The developed workflows provide the optimal choice of the viscosity correlation for the case of distinct viscosity ranges, as well as when overall performance is sought. A surprising result is that one of the oldest known correlations from the literature gives the best results (minimizes average absolute relative error) when tested against this large dataset. This may be attributed to the high locality that alternative correlations exhibit, which makes them generalize poorly.

Keywords: undersaturated oil viscosity; correlations; reservoir simulation; EOR (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
https://www.mdpi.com/1996-1073/15/24/9320/pdf (application/pdf)
https://www.mdpi.com/1996-1073/15/24/9320/ (text/html)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:gam:jeners:v:15:y:2022:i:24:p:9320-:d:998057

Access Statistics for this article

Energies is currently edited by Ms. Agatha Cao

More articles in Energies from MDPI
Bibliographic data for series maintained by MDPI Indexing Manager ().

 
Page updated 2025-03-19
Handle: RePEc:gam:jeners:v:15:y:2022:i:24:p:9320-:d:998057