Iranian Journal of Oil and Gas Science and Technology

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Abstract The oil content of the wax produced in a dewaxing process is the key economic parameter that should be reduced as much as possible. Some factors such as the type of solvents, cooling rate, temperature, and solvent to oil ratio influence the dewaxing process. Due to the fact that crude oil differs from place to place and since the operational conditions for wax extraction vary for different types of crude oil, the objective of this work is to study the operational conditions for wax production from an Iranian raffinate sample used in Sepahan Oil Company. All the experiments are conducted based on a design of experiment (DOE) technique for minimizing the oil content of the wax produced. The effects of five factors have been determined quantitatively and appropriate levels are suggested for reducing the oil content. The results show that the solvent ratio, solvent composition, and cooling rate play the most important role in minimizing the oil content of the produced wax.

Abstract Hydrocarbons are prone to bacterial and fungal contamination. Bacteria and fungi live and proliferate in water droplets within the fuels and on surfaces surrounding them. This can cause corrosion in oil exploration and production, clogging of fuel lines in aviation and higher emissions in diesel combustion engines to state few examples. State-of-the-art is the addition of biocides to fuels, which is associated with several disadvantages like costs and environmental burden. A novel technology to prevent biofouling in hydrocarbons is presented here. By applying an anti-microbial coating to the surfaces of hydrocarbon processing units, pipelines, and fuel containers, microbial growth can effectively be reduced. The coating can be a paint or varnish, for instance, epoxy resin as already used in aircraft fuel tanks to today. It contains transition metal oxides, thus an acidic surface is produced. This acidic surface was shown to eliminate up to 10⁹ colony forming units per milliliter (CFU.ml^-1) of bacteria of the species of agrobacterium tumefaciens and others in diesel, kerosene, and biodiesel, where other anti-microbial coatings based on silver did not perform. The technology has the potential to bring huge cost savings to the oil and gas industry, alongside an increase in safety and equipment reliability.

Abstract Seismic facies analysis (SFA) aims to classify similar seismic traces based on amplitude, phase, frequency, and other seismic attributes. SFA has proven useful in interpreting seismic data, allowing significant information on subsurface geological structures to be extracted. While facies analysis has been widely investigated through unsupervised-classification-based studies, there are few cases associated with supervised classification methods. In this study, we follow supervised classification scheme under classifiers, the support vector classifier (SVC), and multilayer perceptrons (MLP) to provide an opportunity for directly assessing the feasibility of different classifiers. Before choosing classifier, we evaluate extracted seismic attributes using forward feature selection (FFS) and backward feature selection (BFS) methods for logical SFA. The analyses are examined with data from an oil field in Iran, and the results are discussed in detail. The numerical relative errors associated with these two classifiers as a proxy for the robustness of SFA confirm reliable interpretations. The higher performance of SVC comparing to MLP classifier for SFA is proved in two validation steps. The results also demonstrate the power and flexibility of SVC compared with MLP for SFA.

Abstract In last decades, oil spill pollution has become an important issue of concern due to its serious environmental impacts; therefore, necessary actions should be taken to prevent or reduce these types of pollution and their environmental consequences. Natural organic sorbents are emerging as proper choices for oil spill cleanup due to their availability, eco-friendliness, and low cost. In this study, phragmites australis, sugarcane leaves straw, and sugarcane bagasse were used for crude oil sorption in dry (only oil) systems. The results indicated that sugarcane bagasse had a higher oil sorption capacity compared to the others. Therefore, sugarcane bagasse was selected as the preferred sorbent and the effects of sorbent contact time and its particle size on oil adsorption capacity were evaluated for the systems of dry and crude oil layer on water. The results showed that the maximum adsorption capacity of raw sugarcane bagasse for dry system and crude oil layer system was about 8 and 6.6 gram crude oil per gram sorbent respectively.

Abstract Seismic inversion is a method that extracts acoustic impedance data from the seismic traces. Source wavelets are band-limited, and thus seismic traces do not contain low and high frequency information. Therefore, there is a serious problem when the deterministic seismic inversion is applied to real data and the result of deterministic inversion is smooth. Low frequency component is obtained from well log data; however, but when well log and seismic data are used together, it faces a problem which is a function of the support of scale of measurements. Well log data have a high vertical resolution while seismic data represent low details in vertical direction. Geostatistical seismic inversion (GSI) is a method to overcome the aforementioned limitations. GSI uses well log and seismic data together in the geostatistical frameworks. In this study, a new approach of geostatistical inversion based on spectral geostatistical simulation is used. This approach is performed in frequency domain and stochastic framework. Distinct from sequential simulation, spectral simulation method is a direct method, which does not require an acceptance/rejection step. Hence, GSI algorithm based on spectral simulation is fast. This approach is performed in a case study of an Iranian gas field in the Persian Gulf basin. The upper-Dalan and Kangan are two main formations of this field. The results of GSI are compared with deterministic inversion and it is concluded that, as opposed to deterministic inversion, GSI can recover low frequency components.

Abstract Petrophysical parameters such as porosity, water and oil saturations, formation resistivity factor, etc. describe the storage capability of the porous media or the capacity of rocks to hold fluids. The modified Archie’s equation
   . / . , also called the saturation equation, is used to determine the water saturation. Archie’s parameters, namely , , and , are sometimes assumed constant to simplify petrophysical measurements. But these parameters are not constant, particularly in heterogeneous reservoirs. Inaccurate estimates of these parameters can cause significant errors in the calculation of water saturation when using Archie’s equation and lead to discrepancies between log interpretation and production test results. There are many factors affecting cementation factor () such as porosity, pore throat size, type of rock grains, type and distribution of clay content, degree of cementation, and overburden pressure. In the present paper, the results of electrical resistivity experiments are used to derive a new cementation factor correlation which can be applied to carbonate parts of Asmari and Sarvak formations located in south-west Iran. In Iran, the cementation factor is traditionally measured by Shell formula or is assumed equal to 2 to avoid difficulty. In the new formula,  increases with increasing porosity; however, in the Shell formula,  decreases with increasing porosity especially in the low porosity ranges, which is in disagreement with the current paper results. In addition, the results demonstrate that it is not possible to introduce constant  values or separate cementation factor correlations versus porosity for different petrofacies and rock types. Petrophysical evaluations are done to quantify hydrocarbon resources in formations under study. Then, the water saturation is calculated with different calculation methods of cementation factor, . The calculated water saturations are compared with the measured water saturations of preserved cores.

Abstract Wettability alteration is an important method for increasing oil recovery from oil-wet carbonate reservoirs. Chemical agents like surfactants are known as wettability modifiers in carbonate systems. Oil can be recovered from initially oil-wet carbonate reservoirs by wettability alteration from oil-wet to water-wet condition with adding dilute surfactant and electrolyte solutions. This paper investigates the effects of brine concentration, surfactant concentration, and the pH of injection water on the wettability alteration of carbonate reservoirs by different class of surfactants. Scanning electron microscopy images verified the formation of surfactant layer surfaces and the adsorption of surfactant molecules on the rock. The results revealed that TX-100, as a nonionic surfactant, and CTAB, as a cationic surfactant, were better wettability modifiers than SDS, as an anionic surfactant, for carbonate rocks. At the concentration of 1 wt.% and higher, the contact angle reduction was approximately unchanged. The results also proved that there was an optimum salinity for the maximum wettability alteration by surfactants. Increasing the pH of aging fluid resulted in better wettability alteration by CTAB, while, in the case of SDS, the wettability alteration was reduced. Acidic conditions had a negligible effect on the wetting behavior of TX-100.

Abstract CO₂ emissions from combustion flue gases have turned into a major factor in global warming. Post-combustion carbon capture (PCC) from industrial utility flue gases by reactive absorption can substantially reduce the emissions of the greenhouse gas CO₂. To test a new solvent (AIT600) for this purpose, a small pilot plant was used. This paper presents the results of studies on chemical methods of absorbing CO₂ from flue gases with the new solvent, and evaluates the effects of operating conditions on CO₂ absorption efficiency. CO₂ removal rate of the AIT600 solvent was higher in comparison to the conventional monoethanolamine (MEA) solvent. The optimized temperature of the absorber column was 60 °C for CO₂ absorption in this pilot plant. The overall absorption rate (Φ) and the volumetric overall mass transfer coefficient (K_Ga_V) were also investigated.  

Abstract The performance of MSU-S and its forms modified with phosphotungstic acid (HPW) and nickel (Ni) for the desulfurization and denitrogenation of model diesel fuel were studied. According to the results of the characteristic tests (N₂ adsorption-desorption, XRD, SEM, and NH₃-TPD), heteropoly acid incorporation causes higher acidity along with a negligible loss of structural aspects, while Ni impregnation leaves a drastic negative effect on mesoporous structure, crystalline phase, and particle shape along with a positive impact on surface acidity. With both modifications (HPW and Ni), the maximum increase of 33.18% and 6.88% was occurred for the adsorption loading of total sulfur and total nitrogen respectively. The adsorption loading and selectivity of all the adsorbents for total nitrogen were slightly more than those for total sulfur (the selective adsorption of nitrogen over sulfur). The pseudo-second order model can best fit the kinetics data and Freundlich model can best describe the equilibrium isotherm for all the species over Ni/HPW-MSU-S.

Abstract The prediction of lithology is necessary in all areas of petroleum engineering. This means that to design a project in any branch of petroleum engineering, the lithology must be well known. Support vector machines (SVM’s) use an analytical approach to classification based on statistical learning theory, the principles of structural risk minimization, and empirical risk minimization. In this research, SVM classification method is used for lithology prediction from petrophysical well logs based on petrographic studies of core lithology in a heterogeneous carbonate reservoir in southwestern Iran. Data preparation including normalization and attribute selection was performed on the data. Well by well data separation technique was used for data partitioning so that the instances of each well were predicted against training the SVM with the other wells. The effect of different kernel functions on the SVM performance was deliberated. The results showed that the SVM performance in the lithology prediction of wells by applying well by well data partitioning technique is good, and that in two data separation cases, radial basis function (RBF) kernel gives a higher lithology misclassification rate compared with polynomial and normalized polynomial kernels. Moreover, the lithology misclassification rate associated with RBF kernel increases with an increasing training set size.

Abstract In this paper, a very efficient method, called single matrix block analyzer (SMBA), has been developed to determine relative permeability and capillary pressure curves from spontaneous imbibition (SI) data. SMBA mimics realistically the SI tests by appropriate boundary conditions modeling. In the proposed method, a cuboid with an identical core plug height is considered. The equal dimensions of the cuboid in x and y directions are set such that the cylindrical core plug and the cuboid have the same shape factor. Thus, by avoiding the difficulties of the cylindrical coordinates, a representative model for the core plug is established. Appropriate grid numbers in x-y and z directions are specified to the model. Furthermore, the rock and fluid properties of SI test are set in the SMBA. By supposing forms of the oil-water capillary pressure and relative permeability and comparing the oil recovery curves of SMBA and SI data, capillary pressure and relative permeability can be determined. The SMBA is demonstrated using three experimental data with different aging times. Suitable equations are employed to represent the capillary pressure and relative permeability curves. The genetic algorithm is used as the optimization tool. The obtained results, especially for capillary pressure, are in good agreement with the experimental data. Moreover, the Bayesian credible interval (P10 and P90) evaluated by the Neighborhood Bayes Algorithm (NAB) is quite satisfactory.  

Abstract Seismic waves are non-stationary due to its propagation through the earth. Time-frequency transforms are suitable tools for analyzing non-stationary seismic signals. Spectral decomposition can reveal the non-stationary characteristics which cannot be easily observed in the time or frequency representation alone. Various types of spectral decomposition methods have been introduced by some researchers. Conventional spectral decompositions have some restrictions such as Heisenberg uncertainty principle and cross-terms which limit their applications in signal analysis. In this paper, synchrosqueezingbased transforms were used to overcome the mentioned restrictions; also, as an application of this new high resolution time-frequency analysis method, it was applied to random noise removal and the detection of low-frequency shadows in seismic data. The efficiency of this method is evaluated by applying it to both synthetic and real seismic data. The results show that the mentioned transform is a proper tool for seismic data processing and interpretation.

Abstract In the present study, lightweight expanded clay aggregate (LECA) coated with iron oxide was investigated as a low cost sorbent to remove  from wastewater. Iron oxide coated LECA (IOCL) as a new sorbent was tested for its efficiency as  sorbent using operational parameters such as contact time, the initial pH of the solutions, and sorbent dosage concentration in batch systems. The adsorption characteristics of the natural LECA and IOCL were investigated through scanning electron microscopy (SEM), X-ray fluorescence spectroscopy (XRF), and X-ray diffraction (XRD) analysis. The maximum sorption efficiency was found to be 96% for IOCL at an initial pH of 6.0 and a sorbent dosage of 5 . The results revealed that the  sorption kinetic data were well fitted to a pseudo second–order kinetic model. The experimental data showed that  sorption was considerably high on IOCL and the new sorbent is an economical method for Ni (II) removal from effluents and aqueous media.

Abstract The petrophysical analysis of the early Eocene Sui Main Limestone (SML) has been conducted in Kharnhak-1 well for the prospect of the hydrocarbon exploration of the Khairpur-Jacobabad High, Middle Indus Basin, Pakistan. The petrophysical analysis of SML is carried out on the basis of well logs including gamma ray, spontaneous potential, resistivity, neutron, and density logs. These analyses lead to interpreting the vertical distribution of porosity and permeability in order to measure the reservoir potential of the SML. The Archie equation was used to assess the petrophysical characteristics. The SML has good porosity and poor permeability with positive correlation coefficient between the two parameters. The average volume of shale is 18%. The log signature of SML shows dominance of carbonates (limestone). The reservoir quality of the SML in Kharnhak-1 well is such that it is 77% water saturated. The porosity (x) varies inversely with formation resistivity factor (F) and compressional wave velocity (Vp). However, F and Vp are directly related with each other. Thus, the electric and elastic properties of the carbonate rocks can be influenced by postdepositional alterations, which include porosity enhancement and reduction processes respectively.

Abstract Tedious calculations and simulations are needed to obtain an efficient production scenario and/or
proper field development strategy. Capacitance-resistance model (CRM) is proved to be a fast
reservoir simulation tool using just the field-available data of production and injection rates. This
approach sets a time-constant and a weighting factor (or well-pair connectivity parameter) between
each pair of injection and production wells according to their histories. In this study, we investigated
the behavior of the CRM parameters in synthetic reservoir models with different porosity and
permeability maps. Four reservoirs are considered with different porosities and permeabilities to study
their effects on CRM response. We defined a new parameter, named error to mean production ratio
(EMPR), to analyze the CRM performance. Some fluctuations are exerted on the production data to
evaluate the capability of CRM against variable production records. Porosity showed a stronger effect
on CRM parameters than the permeability based on the calculated EMPR. Unstable production
history would result in large error which can be corrected with some smoothing techniques on
variable production data. Also, a linear trend of EMPR was obtained with the change of porosity and
permeability or a combination of the two parameters within the reservoir.

Abstract Core flooding experiments were conducted with the objective of evaluating near miscible surfactant alternating CO₂ injection and the effect of surfactant concentrations on gas-oil and water displacements in porous media. The core samples were provided from a low permeability mixed wet oil reservoir at 156 °F and 1900 psia. In addition, very few studies of surfactant adsorption on carbonate minerals have been conducted. Hence, the surfactant adsorption on carbonate rock was determined by core flooding and crushed tests. It was found that for the crushed rock, the required equilibrium time is approximately five hours, while it is more than four days for the flow-through tests. Hysteresis effects demonstrated that the irreducible water saturations were 5 to 10% higher than the initial connate water saturation after drainage cycles during 5000 ppm surfactant solution. Furthermore, near-miscible surfactant alternating CO₂ injection process led to a 4-17% increase in the recovery factor in comparison to water alternating gas process.

Abstract The chemical surfactant flooding can mobilize the trapped oil by lowering the interfacial tension between oil and brine and in some cases altering the reservoir rock wettability. In this work, the effect of surfactants on oil/brine interfacial tension was experimentally investigated. First, the effect of surfactants concentration was surveyed. Afterwards, the effect of salinity on surfactant behavior was studied. The experiments were carried out at ambient and reservoir temperatures (all at reservoir pressure) to clarify that we cannot generalize the ambient experimental results to reservoir ones and the experiments must be done in reservoir conditions to attain more certainty. Sodium dodecyl sulfonate, cetyl trimethyl ammonium bromide and Triton X-100 were used as the surfactants. The oil and brine samples of the Iranian Asmari reservoir were used. Pendant drop method was used to measure oil/brine interfacial tension. Based on the results, it is concluded that the anionic surfactant (SDS) has a better performance at reservoir and ambient temperatures. The superiority of SDS is more emphatic at reservoir temperature than ambient temperature. At reservoir temperature, the SDS solution lowers the interfacial tension significantly (0.4 mN/m) even when a very low concentration of SDS (0.04 wt.%) is added to brine.

Abstract Oil spill is one of major marine environmental challenges. The main impacts of this phenomenon are preventing light transmission into the deep water and oxygen absorption, which can disturb the photosynthesis process of water plants. In this research, we utilize SpecTIR airborne sensor data to extract and classify oils spill for the Gulf of Mexico Deepwater Horizon (DWH) happened in 2010. For this purpose, by using FLAASH algorithm atmospheric correction is first performed. Then, total 360 spectral bands from 183 to 198 and from 255 to 279 have been excluded by applying the atmospheric correction algorithm due to low signal to noise ratio (SNR). After that, bands 1 to 119 have been eliminated for their irrelevancy to extracting oil spill spectral endmembers. In the next step, by using MATLAB hyperspectral toolbox, six spectral endmembers according to the ratio of oil to water have been extracted. Finally, by using extracted endmembers and SAM classification algorithm, the image has been classified into 6 classes. The classes are 100% oil, 80% oil and 20% water, 60% oil and 40% water, 40% oil and 60% water, 20% oil and 80% water, and 100% water. 

Abstract The aim of seismic inversion is mapping all of the subsurface structures from seismic data. Due to the band-limited nature of the seismic data, it is difficult to find a unique solution for seismic inversion. Deterministic methods of seismic inversion are based on try and error techniques and provide a smooth map of elastic properties, while stochastic methods produce high-resolution maps of elastic properties with the same probability. The current paper studies a stochastic method of seismic inversion which was applied to one of the Persian Gulf oilfields. Joint posterior distribution of elastic properties was calculated using Bayesian principle; then a sequential Gaussian simulation technique was performed to decompose the global probability function of elastic properties into some local probability functions at each trace location. The sampling of the local probability functions was performed, and two hundred realizations of the elastic properties were generated. The results of the stochastic inversion were found to be capable of modeling heterogeneities of the reservoir. The generated realizations provided the possibility to uncertainties assessment by calculating the variance of the elastic properties. It was found out that the uncertainty increased in locations far away from the well. Moreover, stochastic inversion, unlike deterministic one, was found to be capable of detecting thin beds (3.5 to 5.7 m) embedded within the reservoir.