Journal of Petroleum Science and Technology
Volume:1 Issue: 2, Summer 2011

Among the air pollutants, sulfur dioxide has been given special emphasis for posing dangers to the environment. SO2 emissions in the air have harmful effects on human health and the environment. Respiratory diseases and exacerbation of heart diseases are among dangerous symptoms for human health, especially when high concentrations of SO2 are emitted. Therefore, in the present study, a wide variety of dry and wet processes were investigated to identify an appropriate process to reduce the amount of sulfur dioxide. Ultimately, the use of a fluidized bed containing metal oxides in a dry process was selected due to the factors such as simplicity of the process, forming a minimum of waste water and gas and ability to reduce pollution levels to acceptable environmental standards. In order to examine the performance of this type of fluidized beds, a laboratory scale set-up was constructed to investigate the effects of various operational parameters including temperature, inlet gas rate and concentration on the amount of sulfur dioxide adsorption by copper oxide

A hydrogel was prepared by crosslinking aqueous solutions of sulfonated polyacrylamide/chromium triacetate for use in water shut off operations. Gel swelling and the effects of salinity, injection time and flow rate on residual resistance factor (Frr) were investigated. In the presence of electrolytes, gel swelling decreased by about 80%. Results showed that oil permeability increased as injection time increased. The results also indicated that the effect of gel treatment increased with decreasing injection rate. However, when sand packed was water flooded by formation water, Frrw decreased by about 26%. According to the results, Disproportionate Permeability Reduction (DPR) was the result of gel swelling by water injection and dehydration by oil injection.

Water flooding is a well-known secondary mechanism for improving oil recovery. Conventional approach to evaluate the performance of a water flooding process (e.g. breakthrough and post breakthrough behavior) is to establish a reliable geological reservoir model, upscale it, and then perform flow simulations. To evaluate the uncertainty in the breakthrough time or post breakthrough behavior, this procedure has to be repeated for many realizations of the geological model, which takes many hours of CPU time. Moreover, during the early stage of reservoir life, when data is scare, breakthrough and post breakthrough time behavior prediction are usually based on analogues or rules of thumb. Alternative statistical approach is to use percolation theory to predict breakthrough and post breakthrough bahavior. The main contribution is to evaluate the applicability of the existing scaling laws of the breakthrough time by the numerical flow simulation results using the Burgan formation dataset of Norouz offshore oilfield in the south of Iran. Moreover, we extend the scaling to the post breakthrough behavior. There is good agreement between the predictions from the percolation based expressions and the numerical simulation results. Moreover, the prediction from the scaling law took a fraction of a second of CPU times (as it only needs some algebraic calculations) compared with many hours required for the conventional numerical simulations.

Microbial fuel cells (MFCs) are processes used for simultanuous bioenergy capturing and waste treatment. In this study, a model for MFCs based upon a conduction mechanism for electron transfer is proposed, which integrates substrate utilization, current production and conduction and microbial distribution and growth in batch flow mode. The outputs of the model and that of a mediator based model are compared with respect to reference experimental results under a well controled conditions using time evolution of produced current. The comparison shows that the electron shuttling mechanism appears to fail to predict the experimental data accurately enough while the conduction based model is able to reproduce measurements consistently.

A multilayer composite ceramic membrane was prepared by depositing a nano-scale layer of SiO2 on top of a modified porous alumina support by chemical vapor deposition (CVD) method. The modification of the support was carried out by adding a graded layer of Al2O3 (γ-alumina phase), using sol-gel method. An optimized temperature of 700 K for intermediate layer calcination was gained by XRD analysis. Cross-sectional images obtained from SEM showed that the intermediate γ-alumina layer had a thickness of about 2 μm and the top selective silica layer was quite dense and uniform with a thickness of about 90-100 nm. Permeation tests showed a very good flux of 10-6-10-7 mol m-2 s-2 Pa-1 for H2 with selectivities over CO2, N2 and CH4 up to 500. By performing different tests with various deposition times, it was concluded that by changing CVD time from 3 h to 6 h H2/CO2 selectivity increased from 32 to 573, although H2 permeation flux reduced about 50 percent.

Although CO2 injection is one of the most common methods in enhanced oil recovery, it could alter fluid properties of oil and cause some problems such as asphaltene precipitation. The maximum amount of asphaltene precipitation occurs near the fluid pressure and concentration saturation. According to the description of asphaltene deposition onset, the bubble point pressure has a very special importance in optimization of the miscible CO2 injection. The purpose of this research is to predict the onset of asphaltene and bubble point pressure of fluid reservoir using artificial intelligence developed models including a software simulator called “Intelligent Proxy Simulator (IPS)” based on structure artificial neural networks and “adaptive neural fuzzy inference system”, which is a combination of fuzzy logic and neural networks. To evaluate the predictions by artificial intelligence networks at the onset of deposition, a solid model using Winprop software was employed. Standing correlations were used for comparison of bubble point pressure. The results obtained using artificial intelligence models in prediction of the onset of asphaltene deposition and bubble point pressure during injection of CO2 were more accurate than those obtained from the thermodynamics Solid model and the Standing correlation respectively.

In this article, the effects of viscous dissipation and inertial force on the velocity and temperature distributions of the mixed convection laminar flow in a vertical channel partly filled with a saturated porous medium have been studied. In this regard, the Brinkman–Forchheimer extended Darcy model was adopted for the fluid flow in the porous region. In addition, three different viscous dissipation models with isoflux-isothermal boundary conditions were applied. To determine the velocity and temperature distributions for both the regions, the coupled non-linear governing equations were solved using two parameter perturbation and numerical methods. Moreover, the results of the numerical method were validated against those predicted by the perturbation method for small values of the dimensionless perturbation parameters. Furthermore, the results obtained for both regions were compared in terms of Grashof, Reynolds, Forchheimer, and Brinkman numbers. The predicted results clearly indicate that the type of viscous dissipation model has a significant effect on the temperature and velocity distributions.

A mixed proton–electron conducting perovskite was synthesized by liquid-citrate method and the corresponding membrane was prepared by pressing followed by sintering. The hydrogen permeability of BaCe0.9Yb0.1O3-δ was studied as a function of temperature and hydrogen partial pressure (PH2) gradient. Using 100% dry hydrogen at 1173 K, the hydrogen permeation rate of dense membranes (1.63 mm thick) for a mixture of 60% H2/He was 0.000293 mol/(m2 s). The phase structure of powder was characterized by X-ray diffraction and thermogravimetry (TG). Scanning electron microscopy (SEM) was used to investigate the microstructure of sintered membrane. Activation energy estimated with Arrhenius equation was 29 kJ/mol.