Iranian Journal of Oil & Gas Science and Technology
Volume:2 Issue: 1, Winter 2013

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.

The gas-assisted gravity drainage (GAGD) process is designed and practiced based on gravity drainage idea and uses the advantage of density difference between injected CO2 and reservoir oil. In this work, one of Iran western oilfields was selected as a case study and a sector model was simulated based on its rock and fluid properties. The pressure of CO2 gas injection was close to the MMP of the oil, which was measured 1740 psia. Both homogeneous and heterogeneous types of fractures were simulated by creating maps of permeability and porosity. The results showed that homogeneous fractures had the highest value of efficiency, namely 40%; however, in heterogeneous fractures, the efficiency depended on the value of fracture density and the maximum efficiency was around 37%. Also, the effect of injection rate on two different intensities of fracture was studied and the results demonstrated that the model having higher fracture intensity had lesslimitation in increasing the CO2 injection rate; furthermore, its BHP did not increase intensively at higher injection rates either. In addition, three different types of water influxes were inspected on GAGD performance to simulate active, partial, and weak aquifer. The results showed that strong aquifer had a reverse effect on the influence of GAGD and almost completely disabled the gravity drainage mechanism. Finally, we inventively used a method to weaken the aquifer strength, and thus the gravity drainage revived and efficiency started to increase as if there was no aquifer.

Least squares method (LSM) is an accurate and rapid method for solving some analytical and numerical problems. This method can be used to estimate the average reservoir pressure in well test analysis. In fact, it may be employed to estimate parameters such as permeability (k) and pore volume (Vp). Regarding this point, buildup, drawdown, late transient test data, modified Muskat method, interference test, and other methods are equivalent to a separable least squares problem. The main advantage of LSM in the well testing problems is that the results would be confident and no trial and error is required. Furthermore, the given method requires a short time. The fast rate of convergence and high accuracy of the LSM are demonstrated through two examples. The current study concerns a modified Muskat method. The results of LSM combined with the modified Muskat method are compared with the other iterative and qualitative methods. The preliminary numerical results with both simulated and field data suggest that the method be capable of producing smooth interpretable estimates of reservoir parameters from data.

The late detection of the kick (the entrance of underground fluids into oil wells) leads to oil well blowouts. It causes human life loss and imposes a great deal of expenses on the petroleum industry. This paper presents the application of adaptive neuro-fuzzy inference system designed for an earlier kick detection using measurable drilling parameters. In order to generate the initial fuzzy inference system, subtractive clustering is utilized. The training set contains 50 data samples and there are 362 data samples for testing the proposed method. Also, ANFIS structure is examined at different radii (the parameter of subtractive clustering). Different conformations are tested to get the earliest detection and the lowest false alarms while facing kick. Eventually, ANFIS verifies the danger exposure depth of about 28.6 meters before the depth that the kick was sensed by crew. Such an assessment gives the rig crew enough time to prepare for the danger and stop the operation before being exposed to high pressure zones.

Fractured reservoirs contain about 85 and 90 percent of oil and gas resources respectively in Iran. A comprehensive study and investigation of fractures as the main factor affecting fluid flow or perhaps barrier seems necessary for reservoir development studies. High degrees of heterogeneity and sparseness of data have incapacitated conventional deterministic methods in fracture network modeling. Recently, simulated annealing (SA) has been applied to generate stochastic realizations of spatially correlated fracture networks by assuming that the elastic energy of fractures follows
Boltzmann distribution. Although SA honors local variability, the objective function of geometrical fracture modeling is defined for homogeneous conditions. In this study, after the introduction of SA and the derivation of the energy function, a novel technique is presented to adjust the model with highly heterogeneous data for a fractured field from the southwest of Iran. To this end, the regular object-based model is combined with a grid-based technique to cover the heterogeneity of reservoir properties. The original SA algorithm is also modified by being constrained in different directions and weighting the energy function to make it appropriate for heterogeneous conditions. The simulation results of the presented approach are in good agreement with the observed field data.

The aim of this work is to synthesize and investigate the performance of yttria-doped zirconia solgel coatings in the chemical corrosion prevention of zircaloy-4 (zirconium alloy) in a 1 N H2SO4 environment. The influence of four different molar ratios of water to alkoxide, namely , , 12, and 20, on the coating quality and its corrosion prevention performance was investigated. Differential thermal analysis and thermogravimetric analysis (DTA-TG) revealed the coating formation process. Surface morphology was examined using scanning electron microscopy (SEM). Microscopic features were obtained by employing energy dispersive spectroscopy (EDX) and X-ray diffraction (XRD). Wet corrosion performance was evaluated by using potentiodynamic polarization and electrochemical impedance spectroscopy (EIS) techniques. The EDX results approved that the amount of the yttria doped in zirconia was about 8 wt.%. The XRD results showed that the crystallization of zirconia started near 400 °C. The SEM results showed that denser cracks were formed at a water/alkoxide molar ratio of 4. The electrochemical tests revealed that, as the molar ratio of water to alkoxide was increased beyond 4, the coating quality was damaged and the best protection performance was achieved at a water/alkoxide molar ratio of 4.