4.5 Article

A viscosity prediction model for Kuwaiti heavy crude oils at elevated temperatures

Journal

JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING
Volume 120, Issue -, Pages 102-110

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.petrol.2014.05.027

Keywords

correlations; dead oil viscosity; heavy oil viscosity; Kuwait

Funding

  1. Kuwait University [EP 02/08]
  2. General Facility Research Grant [GE 01/07]

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Viscosity is a key fluid property for characterization, evaluation, management and development of petroleum reservoirs. The accurate prediction of dynamic viscosity will be helpful for heavy oil recovery methods including primary production, thermal production, and enhanced oil recovery (EOR). Reservoir oil viscosity is usually measured isothermally at reservoir temperature. However, at temperatures other than reservoir, dynamic viscosity is estimated by empirical correlations. Most of the published correlations have been performing well at the reservoir temperature, especially for conventional crudes. However, the published literature has lack of reliable methods for viscosity estimation due to an acute shortage of dead oil data at elevated temperatures. These methods are essential and employed in planning thermal recovery methods (Kuwait as well as worldwide). In this study, the API gravity and viscosity of 50 dead crude oil samples collected from various areas of Kuwaiti oil fields were measured. These oil samples have API gravity ranging from 10 degrees to 20 degrees. The viscosities were determined at temperatures ranging from 20 degrees C to 160 degrees C. Consequently the results of the heavy oil viscosity data were used to develop a reliable model and to compare the proposed model with the published models. Both quantitative and qualitative analytical methods were implemented using statistical parameters and performance plot, respectively. From the general evaluation it has been shown that the proposed model has the lowest average absolute error of 11.04% and highest coefficients of correlation of 92% for training and 96% for the testing data. The performance of the proposed correlation has also been tested using dead heavy crude oil data from the region as well as various parts of the world. Compositional data of heavy oil viscosity has been used to compare predicted viscosity from the proposed correlation with that from Lorenz-Bray-Clark (LBC) and Pederson models. These comparisons show that the proposed correlation performed better than the other correlations, corresponding state and EOS-based methods for the dead heavy crude oils considered. (C) 2014 Elsevier B.V. All rights reserved.

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