PETROLEUM RESEARCH
Year:2013 | Volume:23 | Issue:75|Papers Count:15

Several emulsions were synthesized using a crude oil sample named Nowruz as the oil phase، the deionized water as the water phase and Span 40-type surfactant as the emulsifier and parameters affecting the rheological properties of emulsions were studied. In order to investigate the quality of emulsions، their stability was monitored in a three month period. A power-law model was used for the dependence of emulsion viscosity on shear rate and Liu، Richardson، Mooney، and Krieger-Dougherty models were used for the dispersed phase volume fraction dependency. It was observed that the data obtained from modeling were consistent with the experimental data. The results obtained by microscopic analysis revealed that the phase inversion phenomenon took place in the range of 40 to 50% of the dispersed phase (water) content. Temperature was found to be a significantly effective factor in all the samples including the crude oil and its emulsions. It was observed that an increase in temperature could cause a considerable decrease in viscosity، shear stress، and dynamic moduli. An increase in water volume fraction caused an increase in viscosity and dynamic moduli up to the phase inversion point and resulted in a reverse trend beyond this point. The investigation of shear rate effect demonstrated a Newtonian behavior for the crude oil and shear-thinning effect for the emulsions over a wide range of shear rates. The shear-thinning effect increased with an increase in water content and surfactant concentration. The results showed a decrease in loss tangent and a notable increase in viscosity، shear stress، dynamic moduli، and elasticity of emulsions with an increase in surfactant concentration.

Porosity is one of the most important parameters in reservoir characterization which allows the specialists to design and manage، effectively، the process of oil and gas fields development. Using the core samples and well logs are two normal ways to porosity and permeability evaluation but the results are valid just in a vicinity around the well، ، By utilizing 3D seismic data، combination with the core and well log data، will allow to predict reservoir properties through the whole reservoir. This paper is based on 3D seismic data interpretation and the result of well logs data analysis. Also By using seismic Inversion on 3D seismic data and Integration seismic Attribute، reservoir characterization of Sarvak Formation in an oil field in SW of Iran has been studied. Based on the results، facies changes were recognized in the sediment، so the porosity varies in different areas of this field. However porosity significantly increased in central parts of Sarvak Formation in the study area.

One of the main problems in production of oil reservoirs is the formation of asphaltene precipitation. Blockage in porous medium، wells، and facilities has a detrimental effect on the production of asphaltenic oil. Generally، asphaltenes are heaviest and most polar fractions that can be found in crude oil. These compositions have a complex molecular structure which are series of non-hydrocarbon molecules and soluble in benzene and insoluble in normal alkanes and solvents with low molecular mass. Based on recent experiments have been supposed that these compositions can be partially solved in oils at colloidal state. The nature and behavior of asphaltene in crude oils is complex so changes in temperature، pressure and composition of crude oils during production can result in precipitation of asphaltene components. These parameters affect the chemical equilibrium in reservoirs and result precipitation. A possible way to prevent of asphaltene precipitation is by adding an asphaltene stabilizer، i.e. inhibitor. Asphaltene inhibitors act in a way similar to resins، peptizing the asphaltenes and keeping them in solution. The inhibitor efficiency depends on its chemical and structural characteristics، largely. However، the inhibitor ability to stabilize asphaltenes depends also on the solvent or dispersion medium. The main objective of this research is to investigate the effect of three different inhibitors on asphaltenes deposition using viscometric method.The results show decrease in length of hydrocarbonic chains because of branches and steric hindrance between methyl groups will decrease inhibition strength of branched DBSA compare to linear DBSA.

In this paper، the properties of a new formulation for manufacturing and production of class G cement has been proposed. The produced industry cements have no proper rheological properties، thickening time and compressive strength. This paper investigates the effects of particle size distribution changes as a basic parameter on the principal properties of cements such as rheological properties، compressive strength، thickening time and also compatibility of designed cement with certain additives used in oilwell cements formulation such as retarders and fluid loss control. The designed cement is non-uniform and coarser than conventional cements which 50 percent of particles are in the range of 3-30 µm where this amount is more than 70 percent for other standard class G cements. The designed cement has very good rheological properties and requires lesser energy for production and more compressive strength will be obtained due to 10 percent decrease in the amount of water usage in the cement system. Since the use of additional additives leads to more cost، the proposed cement designed in a way that a heavy cement will be obtained without using weighting agents.

When we are talking about economic decisions concerning management of an exploratory field or reservoir، undoubtedly، the correct understanding and realistic explanation of reservoir can lead us to make valuable decisions and choosing appropriate plan in order to improve reservoir management and exploitation; Recoverable oil in place is the most important factor which affects these decisions. This study has been performed in order to make a three dimensional model of structure، stratigraphy، and petrophysical properties of one of Southern Iran reservoirs. Well logging and petrographic data as well as core analysis information were combined and put into an integrated workflow to took advantage of them to build probabilistic models of properties like porosity and water saturation (SW)، using geostatistical routines such as Kriging and Sequential Gaussian Simulation (SGS). Comparison of these methods clearly shows that results of Sequential Gaussian simulation are more acceptable. Finally، volumetric calculations have done using the most realistic model outputs and parameters. The averages of porosity، SW and oil in place have estimated 21%، 52%، and 270 million barrel respectively.

Lack of proper atomization of liquid heavy fuels can lead to decreased efficiency of combustion. This is one of the main problems of liquid heavy fuels since they are economical alternatives for power generation. One of the methods used to improve the atomized liquid heavy fuel is using of emulsified water and fuel. In this paper، to investigate the effects of fuel and water emulsion in the combustion process، the field tests on water and fuel oil by using 7% water by weight and durable material، and also fuel oil without any additives is conducted and the results compared. The results showed the increasing of temperature of exhausted gases، increasing the percentage of oxygen in the combustion products and also reduce fuel consumption by using emulsion fuel. On the other hand، mass and energy balances and the amount of useful energy from fuel combustion in the emulsion fuel oil compared with other cases without any additives have been discussed.

In this study، hydrate formation conditions for refrigerants R-134a، R-141b، and R-152a are simulated employing the cubic plus association equation of state (CPA) and van der Waals –Platteeuw model. Based on the experimental data for the hydrate formation of these refrigerants and the reference properties for structure I and II reported by Sloan، Kihara parameters for these refrigerants are estimated by an implicit optimization scheme through the minimization of the chemical potential difference of water in the hydrate and in the liquid phase. The minimization was performed by applying a genetic algorithm.

Vugs and fractures widely develop in the carbonate reservoirs. Existence of these porosities in addition to matrix porosity leads a complex triple porosity system in the carbonate reservoirs. Accurate understanding of porosity system is vital in reservoir simulation and petrophysical evaluation of heterogeneous carbonates. Image logs are high resolution un-conventional logs which provide a pseudo azimuthal picture from borehole wall. Fractures and vugs can be separated from matrix in image log by utilizing image processing techniques. After recognition of vugs and fractures، the amount of each one can be determined. By integrating conventional logs and FMI (Fullbore Formation Micro Imager) (a type of image logs) a triple porosity reservoir can be quantitatively characterized. We applied aforementioned method to Sarvak reservoir formation in an oilfield in SW of Iran، to characterize its porosity system. The results verified by manually detected fractures in the FMI and also secondary porosity calculated by wire line logs. Comparison of porosity logs derived by means of proposed method with FMI›s fracture density logs shows that except in highly shaly carbonate layers، which this method ignore all vuggy porosity، the proposed method works well and the result can be employed for further petrophysical and reservoir simulation purposes.

PVC/ZnO mixed matrix membranes were prepared and characterized for gas separation properties. The effects of ZnO loading ratio and feed pressure on the gas separation performance of the prepared membranes were investigated. Testing gases were He، N2، CH4، and CO2. The results indicated that the permeability of all the gases increased with an increase in ZnO loading ratio. At a ZnO loading ratio of 15% and a pressure of 8 bar، the permeability of He، N2، CH4، CO2 increased from 3.56، 0.01، 0.007، 0.21 to 49.9، 1.6، 12، 26.4 respectively. Moreover، the permeability of the studying gases showed an increasing manner. The selectivity of pair gases (CO2/N2)، (CO2/CH4)، and (N2/CH4) decreased with an increase in feed pressure. Furthermore، the mechanical properties analysis of the prepared membranes showed that the presence of ZnO nanoparticles in membrane structure night improve tensile module.

The accuracy of the measured data is very important for better quality prediction by soft sensors. In order to determine the quality of the treated gas oil، a soft sensor is designed. The soft sensor design is based on a new machine learning technique called support vector regression (SVR). An integrated technique was developed for data preprocessing. In this technique، wavelet analysis and vector quantization were being used sequentially for random error elimination، data compression، and unusual data omitting. Different methods of wavelet analysis were used to remove the random errors and the best method was selected. Random errors were deleted using Harr and Daubechies basis function where Rigrsure، Minimaxi، Heursure، and Sqtwolog were the threshold algorithms. The results showed that the db4 basis function with Rigrsure threshold algorithms provided the best results for error removal. AARE and RMSE for this method was better than the other types of wavelet functions. Additionally، the results of SVR training based on the pilot plant data showed AARE of 0.053. This showed the high accuracy of the SVR model for predicting treated gas oil quality.

Total organic carbon (TOC) is one of the main parameters for geochemical evaluation of oil and gas source rocks. In this study، we propose a two-step approach to predict total organic carbon content from well log data. Initially، the well log data are classified into a set of electrofacies (EF). The methods used to characterize and identify EF consist of self-organizing maps (SOM) and hierarchical cluster analysis (HCA). The results obtained from both methods are compared and the best method based on cluster validity tests is chosen for clustering petrophysical data into a certain number of EF. Afterwards، the TOC values are estimated from well log data by using individual artificial neural network (ANN) models constructed for each EF. In the second approach، the TOC data are estimated for the total interval by using a similar ANN model regardless of data clustering and EF determination. The results of two prediction methods are compared to each other and also with a third conventional Δlog R technique. The results show that clustering of a formation into specific units (electrofacies) provides better results in TOC prediction compared to the models constructed for the whole dataset as a single cluster. In addition، intelligent systems are more efficient than the previous conventional techniques based on Δlog R method. The proposed methodology is illustrated using a case study of the world’s largest non-associated gas reservoir، i.e. Iran South Pars Gas Field، located in the Persian Gulf.

Asphaltene deposition is an issue that has received much attention since it has been shown to be the cause of major production challenges. Asphaltene precipitation can occur during primary depletion of highly under-saturated reservoirs or during hydrocarbon gas or CO2 injection for improved oil recovery. Numerous laboratory researches and oilfield reports have investigated the effect of asphaltene deposition and its remediation under dynamic flow on reservoir rock properties. All techniques available into proper it، have proven costly and not highly effective، so prevention is the best way to counteract the problem. Revelation of the deposition mechanisms and determination of the parameters they influence it are essential in order to devise reliable prevention strategies. In this work، an experimental effort is made to investigate the permeability impairment of core samples، under natural depletion conditions and identify the dominant deposition mechanisms. The main tools that applied to do these experiments are permeability calculation، analysis of asphaltene concentration and high pressure and high temperature viscometer. Experiment carried on sandstone rock type. In addition، the study provides the deposition mechanism changes during production and it is strong dependent of oil injection rate.