Application of pore network modeling in deep bed filtration analysis
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Application of pore network modeling in deep bed filtration analysis Ali Shabani1 · Davood Zivar2 · Hamid Reza Jahangiri3 · Abbas Shahrabadi4 Received: 4 November 2019 / Accepted: 17 August 2020 © Springer Nature Switzerland AG 2020
Abstract Particle invasion in porous media is an important phenomenon that could lead to formation damage during different operations, such as waterflooding, workover, and drilling. In this paper, a 3D pore network model coupled with a particle tracking method was developed to investigate particle retention and permeability reduction of a pore network system. The proposed model considers the effect of hydraulic drag, gravity, and friction forces. Three mechanisms, including surface deposition, straining, and bridging, have been considered in the development of the proposed pore network model. The results of the proposed model show good agreement with experimental data. A sharp permeability reduction is observed in the early time of the injection, which indicates the blockage of the small radius throats by particles, as well as unstable fluid flow due to the distribution of the particles. Moreover, the number of throats with a small radius and different contributing mechanisms cause the discontinuous decrease of the porous media permeability. The proposed pore network modeling demonstrates that a small section of the pore network can reproduce the results of the experiment, and a big pore network that is too time and cost consuming is not required. Keywords Deep bed filtration · Pore network modeling · Bridging · Straining · Surface deposition List of symbols FH Hydrodynamic force (N) FB Buoyancy force (N) FW Weight of particle (N) Ff Friction force (N) FF Resultant of forces in the opposite direction of particle movement K Permeability of the medium (m2) K0 Initial permeability of the medium (m2) Lij Length of the throat connecting pore i to pore j (m) P Pressure (Pa) rblocking Blocking radius of the throat (m) re Effective radius of the throat (m) ri Initial radius of the throat (m) rp Particle radius (m) 𝛽 An arbitrary integer number between 3 and 7
Uf Magnitude of the fluid velocity in the throat (m/s) Up Magnitude of the particle velocity in the throat (m/s) 𝜇 Viscosity of the injected liquid (cp) 𝜌f Density of injected fluid (gr/cc) 𝜌p Density of particles (gr/cc) 𝜑 Porosity of the porous media 𝜑t Porosity of the throat 𝜃 The angle between the throat and the horizon y Coefficient for blocking radius calculation
* Ali Shabani, [email protected] | 1Department of Chemical and Petroleum Engineering, Sharif University of Technology, Tehran, Iran. 2Centre of Research in Enhanced Oil Recovery, Universiti Teknologi PETRONAS, Perak, Malaysia. 3Department of Chemical and Petroleum Engineering, Iran University of Science and Technology, Tehran, Iran. 4Upstream Technologies Research Center, Research Institute of Petroleum Industry (RIPI), West Blvd. of Azadi Sports Complex, Tehran, Iran. SN Applied Sciences
(2020) 2:1537
| https://doi.org/10.1007/s42
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