Biofilm accumulation in porous media can cause pore plugging and change many of the physical properties of porous media. Engineering bioplugging may have significant applications for many industrial processes, while improved knowledge on biofilm accumulation in porous media at porescale in general has broad relevance for a range of industries as well as environmental and water research. The experimental results by means of microscopic imaging over a T-shape microchannel clearly show that increase in fluid velocity could facilitate biofilm growth, but that above a velocity threshold, biofilm detachment and inhibition of biofilm formation due to high shear stress were observed. High nutrient concentration prompts the biofilm growth; however, the generated biofilm displays a weak adhesive strength. This paper provides an overview of biofilm development in a hydrodynamic environment for better prediction and modelling of bioplugging processes associated with porous systems in petroleum industry, hydrogeology and water purification.
In this paper we derive a pore-scale model for permeable biofilm formation in a two-dimensional pore. The pore is divided in two phases: water and biofilm. The biofilm is assumed to consist of four components: water, extracellular polymeric substances (EPS), active bacteria, and dead bacteria. The flow of water is modeled by the Stokes equation whereas a diffusion-convection equation is involved for the transport of nutrients. At the water/biofilm interface, nutrient transport and shear forces due to the water flux are considered. In the biofilm, the Brinkman equation for the water flow, transport of nutrients due to diffusion and convection, displacement of the biofilm components due to reproduction/dead of bacteria, and production of EPS are considered. A segregated finite element algorithm is used to solve the mathematical equations. Numerical simulations are performed based on experimentally determined parameters. The stress coefficient is fitted to the experimental data. To identify the critical model parameters, a sensitivity analysis is performed. The Sobol sensitivity indices of the input parameters are computed based on uniform perturbation by ±10% of the nominal parameter values. The sensitivity analysis confirms that the variability or uncertainty in none of the parameters should be neglected. keywords: Biofilm · Numerical simulations · Laboratory experiments · Microbial enhanced oil recovery · Porosity 1 arXiv:1807.03400v3 [physics.flu-dyn] 31 Aug 2018• the development of a multidimensional, comprehensive pore-scale mathematical model for biofilm formation,• the inclusion of a biofilm porosity,
The focus of this paper is the derivation of a non-standard model for microbial enhanced oil recovery (MEOR) that includes the interfacial area (IFA) between the oil and water. We consider the continuity equations for water and oil, a balance equation for the oil-water interface and advective-dispersive transport equations for bacteria, nutrients and surfactants. Surfactants lower the interfacial tension (IFT), which improves the oil recovery. Therefore, we include in the model parameterizations of the IFT reduction and residual oil saturation as a function of the surfactant concentration. We consider for the first time in context of MEOR, the role of IFA in enhanced oil recovery (EOR). The motivation to include the IFA in the model is to reduce the hysteresis in the capillary pressure relationship, include the effects of observed bacteria migration towards the oil-water interface and biological production of surfactants at the oil-water interface. An efficient and robust linearization scheme was implemented, in which we use an implicit scheme that considers a linear approximation of the capillary pressure gradient, resulting in an efficient and stable scheme. A comprehensive, 2D implementation based on two-point flux approximation (TPFA) has been achieved. Illustrative numerical simulations are presented. We give an explanation of the differences in the oil recovery profiles obtained when we consider the IFA and MEOR effects. The model can also be used to design new experiments in order to gain a better understanding and optimization of MEOR.Among the various sources of energy, oil remains as one of the most valuable ones, considering its extensive use in the daily life, such as in the production of gasoline, plastic, etc. After discovering a petroleum reservoir, one can extract about 15-50% of the oil by using and maintaining the initial pressure in the reservoir through water flooding (first and second phase oil recovery); however, 50-85% of oil remains in the reservoir after this, so called conventional recovery [34]. This is the motivation for developing new extraction techniques in order to recover the most oil possible. One of these EOR techniques consists of adding bacteria to the reservoirs and using their bioproducts and effects to improve the oil production, which is called MEOR. Besides all MEOR experiments [3,16], it is worth pointing out that MEOR has been already used successfully in oil reservoirs [24,34]. Nevertheless, the MEOR technology is not yet completely understood and there is a strong need for reliable mathematical models and numerical tools to be used for optimizing MEOR.The bioproducts formed due to microbial activity are acids, biomass, gases, polymers, solvents and surfactants [41]. The main purpose of using microbes (bacteria) is to modify the fluid and rock properties in order to enhance the oil recovery. These microbes and the produced surfactants have the advantage to be biodegradable, temperature tolerant, pH-hardy, non-harmful to humans and lower concentrations of them can produ...
The Schwinger model with N f ≥ 2 flavors is a simple example for a fermionic model with zero chiral condensate Σ (in the chiral limit). We consider numerical data for two light flavors, based on simulations with dynamical chiral lattice fermions. We test properties and predictions that were put forward in the recent literature for models with Σ = 0, which include IR conformal theories. In particular we probe the decorrelation of low lying Dirac eigenvalues, and we discuss the mass anomalous dimension and its IR extrapolation. Here we encounter subtleties, which may urge caution with analogous efforts in other models, such as multi-flavor QCD.1 Chiral symmetry and the microscopic Dirac spectrum Chiral symmetry plays a key rôle in our understanding of systems with light fermions. The chiral condensate Σ = − Ψ Ψ is the order parameter, which indicates whether this symmetry is intact (Σ = 0) or broken (Σ > 0). The latter is generic at finite fermion mass m, but in the chiral limit m → 0 both scenarios occur, depending on the model and its parameters:• Σ(m → 0) > 0 is the familiar situation in QCD at low temperature, where the SU(N f ) L ⊗ SU(N f ) R chiral flavor symmetry breaks spontaneously down to SU(N f ) L+R . In our world we encounter 2 (or 3) light quark flavors and quasi-spontaneous chiral symmetry breaking. This gives rise to 2 1
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