Understanding capture of non‐Brownian particles in porous media with network model

Abstract

Particles can invade porous media such as reservoir rocks and deep-bed filters, causing severe damage to their permeabilities. The mechanisms of permeability decline are attributed to surface deposition, bridging and size exclusion of particles in porous media. Traditional models are empirical correlations heavily dependent on filtration data. In this paper, a 2D square network model incorporating the damaging mechanisms is used to study the capture of non-Brownian particles in porous media and the resultant permeability damage. The model employs certain assumptions to imitate the characteristics of real porous media. The proposed procedure applies force analysis to obtain particle invasion depth, and determines damaging mechanisms by pore size to particle size ratio. The method is validated with test data and reasonably good results are obtained. The new model provides more insights into the capture process and does not rely on core flooding data. 

Experimental study of colloidal flow in porous media at high velocities

“…When particles are smaller than pore throats, they invade a porous medium and through bridges form an internal filter cake. [5] Time intervals for the retained concentration decline are significantly shorter than those where the retained concentrations increase with time (pore volumes injected; Fig. 6).…”

“…According to Gao, [5] deposition of particles in filters occurs within several millimeters from the inlet of a filter. Non-uniform particle distribution for very short filters was reported by Al-Abduwani [33] with the amount of deposited particles exponentially decreasing with distance from the inlet of a filter according to Chang.…”

“…Such processes include fouling/clogging of membranes and filters, [1,2] transport of contaminants in groundwater, [3] permeability reduction during aquifer remediation, [4] and injectivity decline of oil reservoirs because of particle invasion. [5] Among main problems during oil production by waterflooding of oilfields are well injectivity with fines lifting and straining due to high velocity flow or water salinity alteration during seawater flooding, re-injection of produced water, or disposal of produced water in aquifers. [5][6][7] Mathematical models when applied to field data allow behavior prediction of the aforementioned technological processes and form the basis for the respective process design.…”

“…[5] Among main problems during oil production by waterflooding of oilfields are well injectivity with fines lifting and straining due to high velocity flow or water salinity alteration during seawater flooding, re-injection of produced water, or disposal of produced water in aquifers. [5][6][7] Mathematical models when applied to field data allow behavior prediction of the aforementioned technological processes and form the basis for the respective process design.…”

“…This resulted in studies into colloidal transport on micro scale [18] : population balance models, [19,20] random walk equations, [21,22] and direct pore scale simulation [23] and network models. [5] Factors such as drag force, difference between equilibrium and current velocities, and difference between the equilibrium and current colloidal/suspension concentrations [3,5,24,25] are equally important for particle attachment and detachment. The particle is attached to the internal cake surface under the action of electrostatic, drag, lifting, and gravitational forces until it is in the mechanical equilibrium.…”