مجله پژوهش نفت
پیاپی 74 (امرداد و شهریور 1392)

In this work, the kinetic of oxidative coupling of methane reactions using Mn/Na2WO4/TiO2 as a catalyst has been modeled. The process of the oxidative coupling of methane consists of complicated interactions between transport phenomena and chemical kinetics. Simulation and modeling have been conducted considering the details of the reaction and the kinetics of the process of the oxidative coupling of methane on laboratory scale. Kinetic experiments were designed and conducted in a catatest setup which was equipped to a differential fixed-bed reactor. In addition, more than 24 experiments were done under different operational conditions, namely at temperatures between 923-1223 K, at atmospheric pressure, at methane to oxygen ratios of 1, 2, 3, 4.5, and at GHSV’s of 8000, 10000, 14000, and 18000 h-1. The results of each experiment in terms of the amount of selectivity of hydrocarbon products (ethylene and ethane) and carbon oxide products (carbon dioxide and carbon monoxide), the methane conversion, and the efficiency of desired hydrocarbon products were assessed. The validation of the method by a comparison between the experimental data and the kinetic model outputs was also performed. Good agreement between these data declares that the kinetic model in the range of our operational conditions is valid. MATLAB was used in order to model the kinetics of the reaction. In this model, all the equations of conservation of mass were solved for all the components of the system. To optimize the model, the sensitivity analysis was also carried out. Finally, the outcomes of model were compared with the experimental results and the kinetic constants and activation energies were calculated for the reactions.

Poly (styrene-butyl acrylate)/clay nanocomposite was synthesized by activators generated by electron transfer (AGET) for atom transfer radical polymerization (ATRP). The chemical composition of the samples was studied by infra red-Furier transformation (FT-IR) spectroscopy. Number- and weight-average molecular weights of the resultant copolymer nanocomposites and their molecular weight distributions were determined by gel permeation chromatography (GPC). The polydispersity index of the nanocomposites were lower than 1.2. The effect of the nanoclay layers on the kinetics of ATRP was investigated by using a plot of ln ([M0]/[M]) versus time of the reaction and also control over the polymerization was investigated by linear relation between number-average molecular weight and monomer conversion. All of the studies confirmed the controlled/living characteristics of the AGET ATRP in the miniemulsion medium. Because of the hindrance effect of the nanoclay layers on the diffusion of the monomers toward the growing macroradicals, the rate of the polymerization decreased.

Aasphaltene consists of heavy hydrocarbon molecules which are in colloidal suspension in the oil and stabilized by resins adsorbed on their surface. A very few works currently exist on asphaltene deposition under dynamic conditions using porous media. In this work, experimental and modeling studies were conducted to determine the effect of asphaltene deposition on the reduction of the permeability of carbonate rock samples at different oil injection rates. The experimental results show that an increase in the injection flow rate can result in an increase in asphaltene deposition and thereby permeability reduction. Also, it can be observed that at a lower injection flow rate, a monotonic decrease in the permeability of the rock samples can be attained upon increasing the injection flow rate, while at higher injection rates after a decrease in rock permeability, an increasing trend is observed before a steady state condition can be reached. Sensitivity analysis was done to understand the effects of some parameters such as surface deposition rate coefficient and entrainment rate coefficient on asphaltene deposition. It can be found that the reduction of permeability decreases by increasing β. Finally, it can be concluded that reduction of permeability increases as surface deposition rate coefficient rises.

In this paper, three nanocatalysts of iron, copper, and strontium were prepared by a microemulsion method. The composition of the final catalysts, in terms of the atomic ratios, are Fe, 100 Fe/3 Cu, 100 Fe/3 Cu/2 Sr. XRD, BET, TEM, and TPR techniques were utilized for the investigation of the phase, structure, and morphology properties of the synthesized catalysts. The performances of the catalysts were tested in a fixed-bed stainless steel reactor. Nanoiron catalyst contained promoter material improved the Fischer-Tropsch synthesis (FTS) and water-gas shift (WGS) activities, while decreased methane selectivity to 7.44%; CO conversion and chain growth probability were also increased to 63.3% and 0.66 respectively.

An important step in the modeling of two-phase gas and oil flow is to have the reliable relative permeability functions. None of the previous conventional methods can predict the consistent and accurate relative permeability values to show the effect of near miscibility on the qualitative and quantitative behavior of relative permeability functions under near miscible conditions. The main contribution of this work is to select the optimum approach to relative permeability determination based on the classification of the available relative permeability methods and comparing their results in order to extract more accurate relative permeability values under near miscible conditions. In this work, the unsteady state displacement experiments were performed on two different reservoir rock samples (i.e. a dolomite and a sandstone core plug sample from the west of Iran). In addition, CO2 and light oil samples as injection fluids were used to decrease the variance error. Also, by the selection of the best relative permeability methods, the bias errors are decreased. In this study, inverse modeling is used with the Civan and Donaldson method as the initial guess for 1-D, two-phase flow simulation. The results show that the history matching as the optimum method presents a reformed relation in order to generate the relative permeability values more consistent to laboratory data under near miscible conditions. Finally, this reformed relation can be embedded in fluid flow simulators to simulate the near miscible gas injection more precisely.

One of the most important operations for reservoir characterization and simulation is well logging. Sonic, density and gamma ray logs are run in most of oil/gas wells to determine reservoir properties such as porosity, permeability and lithology. Also these logs can be used for estimation and modeling of pore pressure which is the main subject of this paper. Direct measurement of pore pressure by conventional tools is expensive and produces local data but well logs are less expensive and have continuous data. In this paper, first pore pressure models are reviewed and then pore pressure model of hydrocarbon reservoir located in Southwest of Iran is constructed. This reservoir is old and some of wells had no sonic log, thus this log predicted using artificial neural network method. T-student test showed that predicted sonic logs have acceptable accuracy. In next stage, first for all of wells pore pressure estimated using Eaton’s model and then in one well, the estimated pore pressure log was compared to measured pore pressure data. This comparison showed that the estimated pore pressure log is very close to measured pore pressure. Therefore the pore pressure model for field was constructed using Geostatistics method

In this study, the effects of polymer-surfactant flooding on oil recovery from dead-ends in a glass micromodel are experimentally investigated. A micromodel containing a long capillary connected to some dead-ends having different aspect ratios is designed and fabricated. Different polymer flooding solutions and combinations of polymer surfactant flooding experiments are carried out at a constant injection rate. The obtained results show that by increasing the concentration of polymer in flooding fluid, the efficiency of sweep from dead-end increases considerably, which could be attributed to the increase of shear stress and the hole-pressure in the dead-ends. The results also show that an increase in the percentage of hydrolyzed and sulfonated groups in polyacrylamide chains leads to higher efficiency of oil sweep from dead-ends. Moreover, the results confirm that the addition of surfactant to polymer flooding solution increases the efficiency of oil sweep from dead-ends considerably, which is much more significant for highly sulfonated polyacrylamide polymers

Seismic attributes are robust tools in the interpretation of stratigraphic phenomena. Use of seismic attributes helps us to detect geological events which normally cannot be revealed in the seismic sections (such as channels). Channels filled with porous rocks and surrounded in a nonporous matrix play an important role in stratigraphic explorations. Although coherence attribute and other edge-sensitive attributes are among the most popular means of mapping channel boundaries, they are relatively insensitive to channel thickness. In contrast, instantaneous spectral attributes obtained using spectral decomposition, due to sensitivity to the variation of channel thickness, can be used to delineate channel thickness. In this paper, we studied the utility of instantaneous spectral attributes extracted from spectral decomposition methods in the detection of channels in one of the southwest Iran oil fields. We first used signal-frequency sections derived by using matching pursuit decomposition (MPD). We then utilized the combination of instantaneous spectral attributes with seismic coherence in order to better reveal channels. The results show that the composite plot of the combination of instantaneous spectral attributes and coherence better illustrate the channel boundaries.

Multiple networks systems have been proposed for the purpose of decreasing the error and increasing the accuracy of the results of artificial neural network (ANN) method. In these systems, the results of several single ANN’s, which are trained solely and separately, are combined using a suitable method. In this work, the effective porosity in one of hydrocarbon reservoirs of giant Southern Pars field is estimated using multiple networks systems. Single ANN’s trained using early stopping back propagation (BP) method are used as the components of multiple networks systems. Well logging data acquired from 4 wells in the field at the depth interval corresponding to Kangan formation are used. Acoustic, density, gamma ray, and neutron porosity well log data are considered as the inputs of the networks and the effective porosity data are assigned as the output of the networks. The ensemble combination of networks, which have a parallel structure, are applied for making multiple networks systems. The results show that suitable ensemble combinations improve the results of the ANN’s trained using early stopping BP method. The best obtained ensemble combination is a three-network combination compared to the best obtained single ANN, which reduces the mean of squares of errors (MSE) of porosity prediction in the training and test steps by 14.7% and 12.5% respectively.

Currently, to measure drilling fluid loss, API standard test is used by filter paper with a pore opening of about 2.7 micron, which perform permeability reservoir role; this is usually different than the real well conditions and, in many cases test, the results are quite different from the real conditions. API standard test shows only the amount of fluid loss in a static state and cannot investigate fluid loss invasion depth. In this study, a sand bed sized with a mesh of 20-40 (0.29-0.51 mm) and pressed under a force of 1 kg is used as a filter paper replacement in order to measure drilling fluid loss in the real formation and identify fluid invasion depth. Then, different fluids are used and in comparison with filter paper a significant difference between fluid loss and its invasion depth in presence of sand bed is seen. Hence it can be concluded that fluid loss measured by filter paper does not identify reservoir specification; therefore, more practical methods such as sand bed filtration should be used to investigate this phenomenon. The function of some materials as fluid loss controller and formation damage prevention can also be evaluated by this method while they cannot be evaluated by API laboratory filtration test method.

The Persian Gulf or Persian sea is a flood channel which is situated in prolongation of Oman Sea and between Iran and Saudi Arabia peninsula. The validity of this region has been approved since the initial of human being, and even in now that oil has been appeared as the fundamental of economic prosperity. Iran, Oman, Iraq, Saudi Arabia, Kuwait, U.A.E., Qatar, and Bahrain have surrounded the Persian Gulf, and the north part of Persian Gulf bank is strategic Situation. The leakage of oil from offshore platform is the main source of pollution in this gulf; therefore, the importance of the determination and analysis of hydrocarbon mixture from crude oil in these platforms of the Persian Gulf is of great importance. Hence the recognition of the source of pollution and the volume of this pollutant pouring into the sea for politicizing national and regional planning with the aim of the Persian Gulf conservation and biogeography related to it is so useful and effective. This article aims to scrutinize aliphatic hydrocarbons (AH) in the composition of crude oil from offshore oil platform of the Persian Gulf, and then compare and deliberate the compound and its physical and chemical specifications of each platform. Sampling method is practiced with SARA method and the amount of aliphatic hydrocarbons of each platform is determined using gas chromatography. Furthermore, several chemical and physical characteristics of crude oil from these platforms were checked and measured and then reported by drawing graphs or studying concerning offshore oil platforms. The results of the determination of aliphatic hydrocarbons in each platform show that crude oil of each platform, its physical and chemical characteristics in the Persian Gulf, and the percentage of aliphatic hydrocarbons leaking from each platform in this gulf differs from each other.