We study through numerical simulations the dependence of the hydraulic permeability of granular materials on the particle shape and the grain size distribution. Several models of sand are constructed by simulating the settling under gravity of the grains; the friction coefficient is varied to construct packs of different porosity. The size distribution and shapes of the grains mimic real sands. Fluid flow is simulated in the resulting packs using a finite element method and the permeability of the packs is successfully compared with available experimental data. Packs of nonspherical particles are less permeable than sphere packs of the same porosity. Our results indicate that the details of grain shape and size distribution have only a small effect on the permeabilty of the systems studied.

We present a finite element (FEM) simulation method for pore geometry fluid flow. Within the pore space, we solve the single-phase Reynold's lubrication equation-a simplified form of the incompressible Navier-Stokes equation yielding the velocity field in a two-step solution approach. (1) Laplace's equation is solved with homogeneous boundary conditions and a right-hand source term, (2) pore pressure is computed, and the velocity field obtained for no slip conditions at the grain boundaries. From the computed velocity field, we estimate the effective permeability of porous media samples characterized by section micrographs or micro-CT scans. This two-step process is much simpler than solving the full Navier-Stokes equation and, therefore, provides the opportunity to study pore geometries with hundreds of thousands of pores in a computationally more cost effective manner than solving the full Navier-Stokes' equation. Given the realistic laminar flow field, dispersion in the medium can also be estimated. Our numerical model is verified with an analytical solution and validated on two 2D micro-CT scans from samples, the permeabilities, and porosities of which were pre-determined in laboratory experiments. Comparisons were also made with published experimental, approximate, and exact permeability data. With the future aim to simulate multiphase flow within the pore space, we also compute the radii and derive capillary pressure from the Young-Laplace's equation. This permits the determination of model parameters for the classical Brooks-Corey and van-Genuchten models, so that relative permeabilities can be estimated.

In this work, a neuro-fuzzy (NF) simulation study was conducted in order to screen candidate reservoirs for enhanced oil recovery (EOR) projects in Angolan oilfields. First, a knowledge pattern is extracted by combining both the searching potential of fuzzy-logic (FL) and the learning capability of neural network (NN) to make a priori decisions. The extracted knowledge pattern is validated against rock and fluid data trained from successful EOR projects around the world. Then, data from Block K offshore Angolan oilfields are then mined and analysed using box-plot technique for the investigation of the degree of suitability for EOR projects. The trained and validated model is then tested on the Angolan field data (Block K) where EOR application is yet to be fully established. The results from the NF simulation technique applied in this investigation show that polymer, hydrocarbon gas, and combustion are the suitable EOR techniques.

A statistical technique for the pore-scale analyses of heterogeneity and representative elemental volume (REV) in unconventional shale rocks is hereby presented. First, core samples were obtained from shale formations. The images were scanned using microcomputed tomography (micro-CT) machine at 6.7 lm resolution with voxels of 990 9 990 9 1000. These were then processed, digitised, thresholded, segmented and features captured using numerical algorithms. This allows the segmentation of each sample into four distinct morphological entities consisting of pores, organic matter, shale grains and minerals. In order to analyse the degree of heterogeneity, Eagle Ford parallel sample was further cropped into 96 subsamples. Descriptive statistical approach was then used to evaluate the existence of heterogeneity within the subsamples. Furthermore, the Eagle Ford parallel and perpendicular samples were analysed for volumetric entities representative of the petrophysical variable, porosity, using corner point cropping technique. The results of porosity REV for Eagle ford parallel and perpendicular indicated sample representation at 300 lm voxel edge. Both pore volume distribution and descriptive statistical analyses suggested that a wide variation of heterogeneity exists at this scale of investigation. Furthermore, this experiment allows for adequate extraction of necessary information and structural parameters for pore-scale modelling and simulation. Additional studies focusing on re-evaluation at higher resolution are recommended.

In this study, we investigate potential application of environment-friendly bio-surfactants (EFBS) in EOR processes. We assess the prospect of combining the EFBS with controlled salinity (CS) water injection in optimising oil recovery using rhamnolipid and protein-enzyme as case study. Rock component analysis, bio-surfactant solubility in brine of varied concentration and composition, crude oil-brine interfacial tension (IFT) and bio-surfactants emulsification activity test were carried out as part of the preliminary investigations. Following these preliminary analyses, a series of comprehensive core flooding displacement experiments were used to investigate the EOR potential of CSBS injection process. Finally, effluent analyses were conducted to study the effect of this combined process on dynamic oil-brine-rock interactions. Results of the IFT tests using 0.0083-3M brine concentrations show IFT reduction from 3.40-2.5 mN/m with increasing salinity for protein-enzyme while increase in IFT from 0.11-0.34mN/m was observed with increasing salinity for rhamnolipid. However, using a fixed brine concentration of 8.3mM with varied bio-surfactant concentration, IFT reduction with increase in concentration was observed for both of them. Also, the two bio-surfactants exhibited stable emulsion active in varied brine salinity investigated. Protein-enzyme is soluble in varied brine formulation while rhamnolipid solubility was found to be dependent on the brine composition and system pH rather than the ionic strength. Furthermore, from the secondary injection of CS and CSBS, the highest recovery factor of 82.76% was achieved with CSBS (protein-enzyme). However, in the tertiary applications, the highest recovery of 83.40% was achieved in the CS injection. Finally, increased pH, Ca2+ and Mg2+ concentrations was observed with both CS and CSBS flooding. This suggests reaction between excess cations and previously adsorbed carboxylic group of crude-oil led to increased recovery. Whereas, at residual oil saturation, interaction between bio-surfactant molecules and rock surface resulted in increased water-wetness and release of oil.