PETROLEUM RESEARCH
Year:2015 | Volume:24 | Issue:80|Papers Count:17

Knowing the orientation and spatial configuration of fractures in naturally fractured reservoirs is necessary for the prediction of the flow in those reservoirs. Among the fracture network modeling methods, simulated annealing algorithm (SA), due to its capability in solving large problems and finding a global optimum, is well-known. This paper proposes a new adaptive and fast simulated annealing algorithm for modeling naturally fractured reservoirs. This algorithm improves computation per- formance without degrading solution quality by incorporating a method for the esti-mation of the initial value of the temperature like parameter, T0' using an adaptive Markov chain length, NT (inner iterations) and suggesting a new fast and adaptive annealing schedule. Moreover, we discuss some aspects of a special objective function and proof this issue that why the minimum of this objective function occurs when the final configuration is a two orthogonal fracture sets with the same num-ber of fractures in each set. Finally, we extend this objective function and modify it to develop an objective function that could generate conjugate fractures with any arbitrary intersection angle.

In this research, the effects of surface active agents on the hydrodynamic param-eters and mass transfer characteristics in an internal loop airlift bioreactor with packed were investigated. Overall gas holdup, liquid circulation velocity and mixing time as the hydrodynamic parameters and volumetric mass transfer coefficient as the mass transfer characteristics were considered. Twenty five cylindrical packings were horizontally set inside the reactor. The experiments were carried out with two various surface active agent solutions containing cationic and non-ionic surfactants at a concentration of 5 ppm at the aeration velocities of 0.19-0.97 cm/s under am-bient conditions (atmospheric pressure and temperature of 25oC). The packings installation reduced the liquid circulation velocity, gas holdup, and oxygen volumet-ric mass transfer coefficient, while increased the mixing time compared with the unpacked column. Furthermore, bubble diameter was reduced around 30%, while they got the same diameter in the systems containing the surface active agents. It was concluded that the mixing time and gas holdup increased, whereas oxygen mass transfer coefficient and liquid circulation velocity decreased in the presence of surface active agents.

An electrofacies in defined by a similar set of log responses that characterize a spe-cific bed and allow it to be distinguished from other beds. Electrofacies character-ization is a simple and cost-effective approach to obtaining permeability estimates in heterogeneous carbonate reservoirs using commonly available well logs. For-mation permeability is often measured directly from core samples in the laboratory or evaluated from the well test data. The first method is very expensive. Moreover, the well test data or core data are not available in every well in a field; however, the majority of wells are logged. We propose a two-step approach to permeability prediction from well logs that uses non parametric regression in conjunction with multivariate statistical analysis. First, we classify the well-log data into electrofa-cies types. This classification does not require any artificial subdivision of the data population and it follows naturally based on the unique characteristics of well-log measurements reflecting minerals and lithofacieswithin the logged interval. A com-bination of principal components analysis (PCA), model-based cluster analysis (MCA), and discriminant analysis is used to characterize and identify electrofacies types. Second, we apply nonpararnetric regression techniques to predict perme-ability using well logs within each electrofacies. Three nonparametric approaches are examined, namely alternating conditional expectations (ACE), support vector machine (SVM), and artificial neural networks (ANN), and the relative advantages and disadvantages are explored. For permeability predictions, the ACE model ap-pears to outperform the other non parametric approaches. We applied the proposed technique to a highly heterogeneous carbonate reservoir in the southwest of Iran.

Water injection process has inevitably been scaling process associated. One of the important discussions in this field is to evaluate formation damage. In the current paper, the effect of some parameters on permeability reduction is investigated. In this study, the fracture effect on formation damage in reservoir rock is studied using a physical model. In addition, injection rate and pressure effects are considered in the physical model. Rock structure and heterogeneity restrict investigating formation damage phenomena. We selected some core samples in one of the oil fields injecting water in aquifer for the simulation of the physical model in laboratory. We tried to perform different scenarios using injected water sample in core flooding process. Although, permeability reduction is observed in no fractured samples, injection pressure increasing is not concluded in injection process in the fractured sample. On the other hand, fracture creation in samples, especially the sandstone sample with weak cementation, can be cause of particle movement or formation damage transfer through reservoir (far from injection well). This subject create problems later after injection especially in production wells where they depend on more parameters e.g. rock structure, texture, pore and particle size distribution, and reservoir heterogeneity.

Lubricants and their additives are important due to their properties which allow longer life and are used widely as an in tribology. In recent decades, they have become more important because of environmental affairs. There are a lot of nanoparticles which can decrease this problem, but they are not suitable enough as their solubility and dispersion in lubricants is low. The best way is using organic coating agent to overcome this problem. In this paper, we synthesized coated nickel nanoparticles by using a micro-emulsion method, sodium dodecylsulfate as a surface active agent in water and ethanol as solvents. Some effective parameters were considered such as the type and quantity of coating agent. The physical properties such as particle size and specific surface area were determined by analytical instruments (TEM, BET, and XRD). The synthesized nickel nanoparticle has a spherical morphology. The particle size is between 7-13 nm and its special surface area is 30 m2/gr. Antiwear properties of nickel nanoparticles in base and multigrade oil were also determined via four ball and Falex tests.

Based on the geochemical and petrophysical data, an exact depth of possible source rocks of Pabdeh and Kazhdumi formations in the Aghajari and Pazanan oilfields was separated and the formation spread (thickness) and organic material variations for each well was examined. Pabdeh formation can be divided into three units based on TOC amount, namely the upper and the lower units A and C with less than 1% TOC and the middle unit with higher than 1% TOC (unit). A and C units are mainly lime stony and the shale is more spread in B unit. Zone B is the main source rock zone and A and C are identified as sub-zones. Observing the rich unit (B) in Pabdeh formation and according to its quality having more than 2% organic matter, it is identified as a rich zone. The thickness of B is more than the two other units in all the wells. The average of organic matter in Pabdeh formation is 1 to 3 percent. Some of these wells are located on Paleo height, in which geothermal gradient increases the transition of organic matter to oil and decreases an average amount of organic matter. This phenomenon is impressed by adjacent fault zones or Paleo height boundaries. Pz#23 has high organic matte richness due to the location out of the Paleo height limit, but in Pz#17, due to location in the high thermal portion of Paleo height, high thermal conditions have caused a decrease in organic matter content immediately and low organic matter remained; but, it still has rich zones. For an accurate and comprehensive examination of organic matter enrichment in Pabdeh and Kazhdumi formations in these wells, an exact position of sampling and amount of organic matter are characterized with software and their adaptation rate with enriched zone is determined by using Rock Eval pyrolysis.

Gas viscosity is one of the most important parameters in petroleum engineering affecting fluid flow in porous media, well, and pipelines. Therefore, it is important to use an accurate value in any ranges of operational pressure and temperature. Gas viscosity is measurable in laboratories but it is costly and time consuming. Also, in Iran, there is no apparatus to measure gas viscosity accurately in laboratories; thus engineers rely on empirical correlations to estimate gas viscosity. In this study, a novel method is used to predict hydrocarbon gas viscosity. This new gas viscosity correlation is developed using artificial neural network, statistical techniques, and a non-linear optimization. Moreover, the validation of this correlation has been approved. The results show that this model has more accuracy compared to other ones for a massive data set.

Environmental restrictions on emission due to fossil fuel combustion have pushed refiners to decrease the sulfur content of products like gasoil and gasoline. The simple concept of ODS method has drawn the attention of many research groups in last few years. Some advantages of this method comparing to other new ones include its simplicity, mild operation condition, low investment cost, and no hydrogen consumption. Many aspects of this process have been investigated; therefore, some different reaction systems are developed. The basis of ODS is oxidizing the organo-sulfur compounds to their sulfones and then removing sulfones from hydrocarbon media. The combination of new technical facilities and traditional chemical processes tend to improve the chemical reaction systems. In this study, by using the ultrasonic waves, the sulfur content of a gasoil sample is decreased to an acceptable limit by Euro environmental laws. Optimum parameters for maximum desulfurization are determined by the analysis of experimental design results. Applying the ultrasonic waves and using optimized parameters, more than 90 percent desulfurization and less than 5 percent hydrocarbon losses are achieved.

Considering the development of refining industries, the ability of the treatment of heavy crude oil with high sulfur, salt, heavy metals, and other undesirable conditions, and the severity of environmental standards, the treatment of refinery waste-water and the disposal of remaining sludge is more difficult than before. With the development of wastewater treatment processes, nowadays more attention are paid to advanced oxidation processes (AOPs). In this work, ozonation as an advanced oxidation process is used for the reduction of biological sludge of Bandar Abbas refinery wastewater. Samples of returned sludge to oxidation basin were ozonated for 20-120 minutes with an amount of 0.0516 to 0.6192 mgO3/mgTSS and in each case COD and remained sludge were defined. The results show that ozone can reduce the amount of sludge and COD with an improvement in the settling conditions. The best conditions were in case of ozone injection for 80 minutes at 0.4128 mgO3/mgTSS. This case can reduce the final sludge up to 36.67% and in this condition COD was reduced from 15570mg/l to 8920mg/l with a 42.71 % reduction. Considering the monthly production of 40-50 tons of excess sludge in Bandar Abbas refinery, using this procedure can reduce the final sludge up to 18 tons/month with reducing environmental hazards with the minimization of the waste management costs.

In this work, the MMFH model and Solid model performance in predicting sour gas injection effects on the asphaltene formation and precipitation in crude oils is investigated. The asphaltene is the heaviest and the most polar parts of the crude oil. The changes in pressure, temperature, and/or composition can cause instability of the asphaltene in petroleum system and finally lead to asphaltene precipitation and deposition. Herein, two models, i.e. MMFH and Solid models, are investigated to predict asphaltene instability in three real oil samples. The stability of the models and their compatibility with the experimental and field observation are assumed as the model application comparison basis. First, the model parameters are tuned via the experimental data and then the adjusted models are used for predicting the sour gas injection and pressure effects on the asphaltene precipitation. As it can be seen, the MMFH models is better than the solid model (this model is used in the commercial software for reservoir simulation) in both comparison criteria, namely the model stability and compatibility with the other results.

The determination of relative permeability model used in reservoir simulation soft-ware is the corner stone of reservoir studies. Nowadays, in order to estimate relative permeability, several models are presented, having their own features. Corey model is one of the most well-known models, because it has simple calculation. However, it behaves inappropriately in facing heterogenic carbonate rock. Also, insufficient studies on comparing different models on carbonate rock are undeniable. Therefore, the assessment of different models and determining the appropriate model to result in a better estimation in carbonate rock is the aim of this study. In this work, after conducting unsteady-state relative permeability experiment under reservoir conditions from three reservoirs, namely A, B, and C, the relative permeability was calculated by using JBN method. Then, all the models could be compared. According to the results, it can be concluded that the LET model in heterogenic carbonate rock (various rock type) leads to a better result compared with the other models and it causes a significant decrease in standard error value for the relative permeability of oil and water to 0.00488 and 0.00119. Furthermore, it is found that this model can predict the S-shape behavior of relative permeability, seeing in Iranian carbonate reservoirs, perfectly.

The presence of many types of noises such as random noise in the seismic data cause some problems; so, they must be attenuated in the processing steps. Singular value decomposition (SVO) is a coherency and linear algebra based filter, which can detect horizontal events in the first eigenimages. For random noise attenuation, after geometry assigning, in common depth point (COP) gather, after velocity analysis and dynamic corrections and before stacking data, SVO is applied to data. The aligned reflectors are detected at first eigenimages, then they are reconstructed; hence another eigenimage, which contains random noise, is zeroed and the random noise will be attenuated. Because the SVO can detect the horizontal event, if static and dynamic corrections are not applied to data correctly and in the common depth point gather, the reflectors have fluctuations and SVO cannot separate between reflectors and random noise viable. In this paper, these steps are applied to a synthetic common depth point gather with various ratios of signal to noise and to a real common depth point gather from one of the Iranian land hydrocarbon field. According to the results, singular value decomposition can attenuate the random noise and preserves the reflectors considrably. Furthermore, this subject is shown in the synthetic data with high noise level (SNR=1).

Instability in shale layers is accounted as one of the biggest problems in drilling industry and area of gas and oil craft. Yearly, industrialists spend a great deal of money to solve this problem. Connection between drilling fluid water base and shale formation causes the swelling development and an increase of pore pressure in the walls of wells; the continuation of this process during time span will be one of the most important factors for the stability of well walls. The potential difference developed/created between drilling fluid and shale formation will cause changes in pore pressure, swelling pressure, water absorption percentage by the shale and the coefficient of membrane. By using the mathematical methods and numerical modeling of finite difference methods, the physical and chemical reactions developed between drilling fluid of water base and shale formation were studied in this work. The results obtained from the numerical modeling express this fact that using fluids in the studied field, to prevent the instability of well resulted from swellings of shells, creates the necessary efficiency and the potassium chloride fluid shows better performance among them. Therefore, the least swelling pressure and pore pressure have been developed by using it.

Petrographic studies on samples of C-4 to F members of Qum Formation shows that dolomitization is one of the most important diagenetic processes affecting carbonate members. Despite this fact that the dolomitization process is one of main reasons for developing porosity and reservoir properties, in section under study, reservoir properties are totally poor and matrix porosity is low. The distribution of dolomicrite and dolomicrosparite has mainly outspreaded the matrix porosity in a limited distance; much of the dolomite in this section is partial dolomitization. The development of cement (mainly dolomitic cement) in deep burial depth as filling the pore, the high percentage of dolomitization formed intertwined mosaics, compaction, stylolitization, and illitization closing the pore throat and reducing porosity and permeability caused reservoir property to become poor. Microscopic studies revealed the presence of 9 types of dolomite, four models of dolomitization in Qum Formation in this section, including Sabkha model, the leakage model, deep burial model, and Do-Rag model. Upper Red Formation on the Qum Formation and the presence of clay and marl in Qum Formation as a combination of clay are the main sources of Mg supply for the Qum Formation dolomites.

In recent years, micromodels have been used to investigate and understand the mechanisms of oil recovery. Micromodels provide the opportunity to observe fluid flow and investigate displacement efficiency on the pore scale. In this work, the ability of Pseudomonas aeruginosa HATH to grow and produce rhamnolipid biosur-factant on sunflower as a carbon source is shown. The produced rhamnolipid can reduce the surface tension from 70 mNm/ to 28 mN/m and interfacial tension from 36 mN/m to 4 mN/m at the CMC concentration. These characteristics show that the produced rhamnolipid has a great potential for the oil recovery, especially in microbial enhanced oil recovery. Furthermore, the effect of produced rhamnolipid on enhanced oil recovery has been studied using a micromodel. The results of the experiments show that after rhamnolipid flooding at the CMC concentration (120 mg/l), about 5% of crude oil is recovered from a micromodel.

Shale volume is one of the main parameters in petrophysical and reservoir studies. Using core to petrophysical parameter determination has some problems and limitations such as coring costs too much and normally it cannot be completely recovered (especially in fractured reservoirs). Image logs dominantly have been used for fracture analysis in Iran, while they have been used to a lesser extent in other fields such as shale volume calculation, porosity, sedimentary environment recognition, etc. In this study, the shale volume of Dalan formation was estimated by applying Binarization method to the FMI image log in one of carbonate reservoirs of the South Western oil fields of Iran. For the validation of suggesting approach, shale volume has also been estimated from GR log Index (CGR) and was compared with FMI shale volume. Shale volume resulted from FMI and CGR logs are compatible and shale volume determination using FMI has some errors caused by locating open fractures next to the shale interlayers.