Computational derivation of conditions for upscalability of bioclogging in pore network models

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During the primary oil recovery, wells are drilled into the reservoir, and due to natural driving forces, the oil flows to the surface through these production wells. Unfortunately, the production of oil in this first stage is typically between only five and ten percent of the oil in place in the reservoir. In the secondary oil recovery some wells (used in the previous stage for production) are converted into injection wells and water or gas are injected into the reservoir to displace the oil to the surface. However, even after primary and secondary oil recovery about 60% of the oil-in-place remains in the reservoir. Microbial Enhanced Oil Recovery (MEOR) is a tertiary enhanced oil recovery technique used to extract the remaining oil after the secondary recovery. MEOR technique was proposed since the 1920’s however it was until 1940’s that it was considered seriously. In MEOR, bacteria and the resulting bioproducts are used to increase the mobilization of oil in the reservoir. Bacterial growth can produce gases that increase the pressure of the reservoir and decrease the viscosity of oil. Biosurfactants decrease the oil viscosity which may lead to an increase of the mobility of oil. Furthermore, bacteria can selectively plug the high permeability zones which changes the direction of water flow to the areas where the oil is still trapped. Selective plugging by bacteria is a process that is used simultaneously with a waterflooding operation. Among all the effects of biofilm growth, selective plugging and interfacial tension reduction are thought to have the greatest impact on oil recovery. The applicability of selective plugging to divert the flow of water has been shown in laboratory experiments. However, on the field scale the applicability of MEOR techniques is still under investigation since the MEOR techniques in pilot fields have produced different outcomes. In this study, we present a new 2D microscopic pore network biofilm growth model that takes into account that nutrients might not be able to penetrate the biofilm completely. This phenomenon occurs if the consumption of nutrients is faster than the diffusion of them. We incorporate in the model a characteristic volume related to the penetration depth of the nutrients within the biofilm. This inclusion allows a more accurate description of the biofilm growth in porous media. In addition, we model the continuous spreading of the biofilm through the whole network, which is a phenomenon that has been observed experimentally. Our numerical experiments show that the nutrients spread fast throughout the whole network during the early stages of the process. Since the nutrients are present in the whole network, the biofilm grows and spreads to the neighbouring tubes. For a longer period of time the biofilm grows uniformly through the network, however after this, the depletion of nutrients is observed and the biofilm grows preferentially near the inlet of the network causing the complete blockage of the network. Our model describes the transition between uniform biofilm growth and heterogeneous biofilm growth.