Nanoparticles have been speculated as good in-situ agents for solving reservoir engineering problems. Some selected types of nanoparticles that are likely to be used include oxides of Aluminium, Zinc, Magnesium, Iron, Zirconium, Nickel, Tin and Silicon. It is therefore imperative to find out the effect of these nanoparticle oxides on oil recovery since this is the primary objective of the oil industry. These nanoparticles were used to conduct EOR experiments under surface conditions. Distilled water, brine, ethanol and diesel were used as the dispersing media for the nanoparticles. Two sets of experiments were conducted. The first involved displacing the injected oil with the nanofluids. In the second case, the sands were soaked in nanofluids for 60 days before oil was injected into the system and displaced with low salinity brine. Generally, using nanofluids to displace injected oil produced a better result. Results obtained from the experiments indicate that Aluminium oxide and Silicon oxide are good agents for EOR. Aluminium oxide nanoparticle is good for oil recovery when used with distilled water and brine as dispersing agents. For the use of ethanol, Silane treated Silicon oxide gave the highest recovery in all the conducted experiments while hydrophobic Silicon oxide in ethanol also yielded good results. Aluminium oxide reduces oil viscosity while Silicon oxide changes rock wettability in addition to reduction of interfacial tension between oil and water caused by the presence of ethanol. For the use of diesel as a nanoparticle dispersing fluid, because diesel and crude oil are miscible, the actual crude oil recovery cannot be determined but the overall result with Aluminium, Nickel and Iron oxides appears good. Magnesium oxide and Zinc oxide dispersed in distilled water and brine cause permeability problems. Generally, distilled water lowers oil recovery. This emphasizes the significant role a fluid plays as a nanoparticle dispersing agent in the formation because it can contribute positively or negatively in oil recovery apart from the effect of the nanoparticles.
This paper presents comparisons between drainage capillary pressure curves computed directly from 3D micro-tomographic images (micro-CT) and laboratory measurements conducted on the same core samples. It is now possible to calculate a wide range of petrophysical and transport properties directly from micro-CT images or from equivalent network models extracted from these images. Capillary pressure is sensitive to rock microstructure and the comparisons presented are the first direct validation of image based computations. The measured data include centrifuge and mercury injection drainage capillary pressure for fired Berea, Bentheimer and Obernkirchner sandstones and unfired Mount Gambier carbonate. The measurements cover a wide range of porosities and permeabilities. The measurements are made on core samples with different diameters (2.5 cm, 1.5 cm, 1 cm and 0.5 cm) to assess the effect of up-scaling on capillary pressure measurements. The smallest diameter samples were also used to obtain the 3D micro-CT images. Good agreement is obtained between the experimental measurements and direct computations on 3D micro-CT images. 1. Introduction Recent advances in imaging technology now make it possible to routinely image rock microstructure in 3D at the pore scale. Coupling this with an ability to computationally predict petrophysical and multiphase flow properties directly on the 3D digitised tomographic images or on equivalent networks (digital core technology) results in a powerful tool to interpret conventionally measured core data and to extend the range of available data by examining rock fragments which cannot be tested by conventional means (sidewall cores, drill cuttings and unconsolidated or poorly consolidated rocks). A number of studies (Auzerias et al., 1996; Arns et al., 2001; Knackstedt et al., 2004) suggest that computations of permeability, formation factor and mercury injection capillary pressure on digitised image of a small rock fragments cut from a core plug are consistent with laboratory measurements performed on the same plug even though the computations and measurements are performed at significantly different scales. Micro-CT imaging is currently limited to small sample sizes; pore scale imaging on most materials requires resolutions of 3–5 microns, and image size is limited to approximately 2000 cubed---this limits the sample sizes for imaging studies to 5mm-1cm which is significantly smaller than conventional core plug scale. Moreover, computational times usually limit the computational domain used to a smaller sub-set of the imaged volume. Conventional laboratory measurements, on the other hand, are carried on core plugs and composite cores at scales several orders of magnitude larger than that for the image based computations. We investigate this scale effect by performing laboratory measurements at a number of different scales from the core plug scale down to a scale closer to that imaged using micro-CT. We limit the investigation to what are usually considered to be homogeneous or model rock types. These are the rock types normally used to validate image based calculations of a wide range of rock properties.
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Fines migration in reservoirs is a serious problem because it gives rise to several problems in hydrocarbon production. Several methods have been proposed and applied to manage this problem but some have failed, some have been ineffective while others consolidate wellbore formations. Rendering formation fines immobile by attaching them to the formation matrix is the best option in controlling migrating fines in reservoir formations. There are indications that the presence of certain nanoparticles in the formation can prevent fines migration by fixing them to the formation. This project therefore investigates the fines trapping capacity of nine nanoparticles in sand packs. The ability of nano treated sands to retain the clays they contain at high flow rates of low salinity water capable of moving fines was examined. The effect of hydrocarbons on the performance of these nanoparticles and other conditions that affect ce their performances were studied. The best performing nanoparticles and the ideal dispersing fluids that aids in accomplishing this task were determined. Experimental results show that dispersing the right kind of nanoparticles in reservoir formations can control fines migration thereby preventing the primary and secondary problems caused by unconsolidated reservoir formations. Field application of this technique will in addition optimize hydrocarbon production and flow assurance.
Surfactant flooding, a chemical IOR technique is one of the viable EOR processes for recovering additional oil after water flooding. This is because it reduces the interfacial tension between the oil and water and allows trapped oil to be released for mobilization by a polymer.In this research, two sets of experiments were performed. First, the optimum surfactant concentration was determined through surfactant polymer flooding using a range of surfactant concentration of 0.1% to 0.6% and 15% of polymer. Secondly, another set of experiments to determine the optimum flow rate for surfactant flooding was carried out using the optimum surfactant concentration obtained. Lauryl Sulphate (Sodium Dodecyl Sulphate, SDS), an anionic surfactant, was used to alter the interfacial tension and reduce capillary pressure while Gum Arabic, an organic adhesive gotten from the hardened sap of the Acacia Senegal and Acacia Seyal trees, having a similar molecular structure and chemical characteristics with Xanthan Gum, was the polymer used to mobilize the oil.The results show that above 0.5%, oil recovery decreases with increase in concentration such that between 0.5 and 0.6%, a decrease of (20% -19%) is recorded. This suggests that it would be uneconomical to exceed surfactant concentration of 0.5%. It is shown in the result of the first set of experiments that a range of oil recovery of 59% to 76% for water flooding and a range of 11.64% to 20.02% additional oil recovery for surfactant Polymer flooding for a range of surfactant flow rate of surfactant concentration of 0.1% to 0.6%. For the second sets of experiments, a range of oil recovery of 64% to 68% for water flooding and a range of 15% to 24% additional oil recovery for surfactant flooding for a range of surfactant flow rate of surfactant flow rate of 1cc/min to 6cc/min. The Optimum surfactant flow rate resulting in the highest oil recovery for the chosen core size is 3cc/min. It's highly encouraged that the critical displacement rate is maintained to prevent the development of slug fingers.In summary, an optimum Surfactant flow rate is required for better performance of a Surfactant flooding.
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