Regular Article
An improved modeling approach for asphaltene deposition in oil wells including particles size distribution
1
Sharif Upstream Petroleum Research Institute, Department of Chemical and Petroleum Engineering, Sharif University of Technology,
Tehran, Iran
2
School of Chemical Engineering, Iran University of Science and Technology,
Tehran, Iran
* Corresponding author: assarehm@iust.ac.ir
Received:
21
February
2018
Accepted:
25
April
2018
There are several approaches to model Asphaltene deposition process in the wellbore. There are different assumptions to simplify the problem in the previous investigations for specific conditions, limiting the prediction range of the models. In this work, the effect of precipitated asphaltene particles size is included, to extend the available modeling approaches for deposition profile. To do so, two-dimensional partial differential equations based on asphaltene micro aggregates material balance including asphaltene aggregation, diffusion and deposition are numerically discretized and solved to find asphaltene deposition profile, in radial and vertical directions of vertical oil wells. The modeling results are verified with the results of the well-known ADEPT (asphaltene deposition tool in flow lines) model of Kurup et al. (2011). The size dependent diffusion coefficients of Escobedo and Mansoori (2010) are used to extend the base model. In addition, the population balance method (PBM) was included to improve the aggregation process description with size distribution of asphaltene particles. Based on the developed model a parametric study is performed to study the effect of asphaltene particles average size, flow rate, wellbore radius and fluid viscosity. The model evaluation shows the importance of asphaltene particle size in the deposition profile. In addition, the evaluation results show that as the average asphaltene particle size increases for a given distribution, the amount of deposition in the wellbore decreases.
© L. Eyni et al., published by IFP Energies nouvelles, 2018
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.