Open Access
ARTICLE
Modeling Tracer Flow Characteristics in Different Types of Pores: Visualization and Mathematical Modeling
1 State Energy Center for Shale Oil Research and Development, Beijing, 100083, China.
2 Unconventional Petroleum Research Institute, China University of Petroleum, Beijing, 102249, China.
3 Research Institute of Petroleum Exploration and Development, Sinopec Shengli Oilfield Company, Dongying,
257015, China.
4 College of Science, China University of Petroleum, Beijing, 102249, China.
5 Oil and Gas Technology Institute, PetroChina Changqing Oilfield Company, Xi’an, 710081, China.
6 National Engineering Laboratory of Low Permeability Oil & Gas Exploration and Development, Xi’an,
710081, China.
7 Research Institute of Petroleum Exploration and Development, SINOPEC, Beijing, 100083, China.
8 School of Chemical Engineering, The University of Queensland, Brisbane, QLD 4072, Australia.
* Corresponding Author: Tongjing Liu, Email: .
(This article belongs to the Special Issue: Advances in Modeling and Simulation of Complex Heat Transfer and Fluid Flow)
Computer Modeling in Engineering & Sciences 2020, 123(3), 1205-1222. https://doi.org/10.32604/cmes.2020.08961
Received 28 October 2019; Accepted 17 March 2020; Issue published 28 May 2020
Abstract
Structure of porous media and fluid distribution in rocks can significantly affect the transport characteristics during the process of microscale tracer flow. To clarify the effect of micro heterogeneity on aqueous tracer transport, this paper demonstrates microscopic experiments at pore level and proposes an improved mathematical model for tracer transport. The visualization results show a faster tracer movement into movable water than it into bound water, and quicker occupancy in flowing pores than in storage pores caused by the difference of tracer velocity. Moreover, the proposed mathematical model includes the effects of bound water and flowing porosity by applying interstitial flow velocity expression. The new model also distinguishes flowing and storage pores, accounting for different tracer transport mechanisms (dispersion, diffusion and adsorption) in different types of pores. The resulting analytical solution better matches with tracer production data than the standard model. The residual sum of squares (RSS) from the new model is 0.0005, which is 100 times smaller than the RSS from the standard model. The sensitivity analysis indicates that the dispersion coefficient and flowing porosity shows a negative correlation with the tracer breakthrough time and the increasing slope, whereas the superficial velocity and bound water saturation show a positive correlation.Keywords
Cite This Article
Citations
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.