PETROLEUM RESEARCH
Year:2011 | Volume:21 | Issue:65|Papers Count:11

Regarding molecular diffusion drive simultaneously with the pressure gradient drive in the porous media is usually referred to as multi-mechanistic flow in the reservoir. Molecular diffusion occurs in the reservoir simultaneously with the pressure gradient drive. Since the pressure gradient drive is usually the dominant drive mechanism, molecular diffusion is usually ignored in the simulation. However, in some cases, ignoring molecular diffusion effect in the simulation results in a prediction that is drastically different from the real reservoir behavior. Gas condensate fractured reservoirs are one of the situations in which molecular diffusion plays an important role in the production mechanism. This paper is the first to investigate the molecular diffusion in gas injection for a gas condensate fractured reservoir. Single block approach is used in this work. This single block is firstly saturated with methane followed by methane and ethane and lastly, methane and n-pentane. Pressure at the left side of this matrix block is kept constant by injection while production is done at the constant pressure at the right side. Fully implicit Newton-Raphson technique is applied to solve highly non-linear equations in this simulation model. In order to speed up the simulation technique, Broyden updating approach is used to update Jacobian matrix. At the end, it was concluded that in gas injection in naturally fractured gas condensate reservoirs, diffusion phenomenon is considerable in matrix blocks with the permeability of lower than 0.01 md in the case of single phase flow at the reservoir condition, while this permeability increases to 0.1 md when two phase flow occurs at the reservoir conditions.

In this paper, heat treated Nickel Aluminium Bronze (C95520) was used as received and exposed to sea water for 75 days. Metallographic investigations were carried out on exposed specimens prepared under as received and heat treated conditions in order to study their microstructures using optical microscopy (OM) and scanning electron microscopy (SEM) equipped with energy dispersive x-ray analysis (EDAX). To determine the resistance of the passive layer on specimen surfaces, an advanced and novel electrochemical noise technique via zeo resistance ammeter (ZRA) together with linear polarization resistance (LPR) and electrochemical impedance spectroscopy (EIS) were utilized. With respect to the passivation potentials extracted from polarization diagrams and polarization resistance (Rp) determined from Nyquist diagrams for all specimens, it was found out that the target sample was under concentration polarization effect. The target sample, coded as sample 14, was heat treated at 675 oC for 45 minutes and normalized in air. The lower starting passivation potential for the target sample indicated a better condition from passivation point of view. Data analysis of electrochemical noise measurements using an evaluation of the last measured 40 potentials and current data of the specimens exposed to sea water for 75 days showed that the corrosion current for as received specimen was found to be twice that of the target specimen. According to the metallographic micrograph, the pearlitic zones in target specimens were attacked much less than similar sites in as received specimen. It was further observed that the corrosion attack on passive layer occurred on selective phases leading to pitting corrosion.

The effect of derivatives of fullerene soot on hydrocarbon fuels was examined. Fullerene was prepared from commercial soot containing a mixture of fullerene (a>7%) with high solubility in petroleum derivatives. The derivatives of fullerenes were reacted with fatty amines such as hexadecylamine in the presence and absence of a solvent. The gas phase, solvent free reaction was carried out at reduced pressure and high temperature conditions. Vacuum distillation was used to remove unreacted amines from the products formed. Thus, an excess of hexadecylamine was used to maximize the number of lipophilic substituents in the mixture of fullerenes and soot. In the second step, the effects of derivatives of fullerene soot as gasoline additives on octane number, fuel consumption and emission of exhaust pollutants were evaluated using standard tests in Peugeot 405, Samand, and Pride engines. The derivatives did not appreciably change octane number and fuel consumption, but somehow affected the exhaust pollutants including CO, HC and NOx in comparison with ordinary gasoline.Furthermore, the effect of formulated gasoline using hexadecylamine fullerene package on exhaust pollutants was evaluated in a 150 hour cycle and no precipitate was observed.

Differential pipe sticking is one of the usual and hazardous problems during drilling operation that leads to increasing the total cost. Nowadays minimizing the risk of stuck occurrence is one of the priorities and main goals in petroleum industry. In the past, statistical methods were applied to investigate differential pipe sticking, but these methods cannot remarkably predict the non-linear behaviors. Artificial neural network is a novel method for solving engineering problems. This method is capable of considering the effective parameters at the same time and has the ability of direct generalization and learning from the field data (due to the errors and uncertainties). In this paper, the data from 63 wells of the offshore Persian Gulf oil fields were applied and by using a probabilistic neural network, a predictive model has been developed. High accuracy of this model in predicting differential pipe sticking allows it to be applied in well planning as well as real time drilling operations.Analyzing the result of neural network, associated with engineering viewpoint leads to preventing differential pipe sticking by optimizing the effective parameters.

Nowadays, biopolymers are one of the most important parts of drilling fluids. Xanthan, a biopolysaccharide with high molecular weight, is produced from Xanthomonas campestris through fermentation processes. In this research, xanthan was produced from three strains of Xanthomonas campestris, b82, 1706DSMZ, SAM3301 and its application potential as a part of drilling fluid was evaluated. In a simultaneous study for decreasing the cost of final product, xanthan production was evaluated by one of these strains using sugar cane molasses. To study the efficiency in drilling fluids, these products were separately dissolved in fresh water, seawater (NaCl 40 g/L), saturated water (NaCl 400 g/L) and KCl 35 % (KCl 350g/L) in 0.5, 1 and 2 lbb concentrations and assessed before and after roll at 121oC. The best result was generally obtained using 2 ppb concentrations of biopolymers. Biopolymer produced by the strains b82 and SAM3301 showed the best efficiency according to high apparent viscosity (AV), Plastic viscosity (PV), Yield point (YP) and also increasing these parameters after role plus producing higher YP/PV ratio. The latter showed greater applicability because of its increased thermal stability and lower foaming. Xanthan sample produced using molasses had the best efficiency in sea water (higher YP/PV ratio), but it’s showed weaker properties than commercial xanthan (XC).

Bibi Hakimeh oil field is one of the biggest oil fields located in the Dezful Embayment. In this study, Kazhdumi and Gadvan Formations and tongue of Kazhdumi in Daryian Formation in Bibi Hakimeh 120 well are investigated.Gamma log, Rock Eval and thermal modeling methods are used in this regard. In this study, properties of source rock zones are separated by using gamma log. Then, quantity and quality of source rocks is studied by using Rock Eval Analysis and thermal modeling. This study reveals that Gamma Ray Log can be used as a good tool in identification of source rock intervals. In this investigation, burial history, hydrogen index, transformation ratio and residual hydrocarbon profiles are obtained. Source rocks are in the early stage of oil generation, but oil expulsion has not taken place yet.

Hydrates are known to occur in a variety of natural-gas handling facilities and processing equipment in oil fields, refineries, and chemical plants where natural gas and water coexist at elevated pressures and reduced temperatures. Prevention of hydrate formation requires prediction of hydrate formation temperature or pressure.In this paper, two data-driven models, i.e. artificial neural network (ANN) and neuro-fuzzy system (ANFIS model) have been applied to predict hydrate formation pressure by available experimental data in this field as alternative tools. For this purpose, optimum structure of data-driven models was determined by statistical parameters. Optimum neural network and ANFIS models were compared with well-known empirical correlation and thermodynamic model of Heriot-Watt University. The results obtained in this work indicate that ANFIS model is more accurate in prediction of hydrate formation pressure than ANN. Furthermore, comparison shows that ANFIS matches better with experimental data compared with empirical correlation and HWHYD model in terms of statistical values.

This article describes a new common-midpoint stacking method for seismic data, called “smart stacking,” which has been tested using experimental and reported data. This method is based solely on optimizing seismic amplitudes of the stacked signal by excluding harmful samples from the stack and applying more weight to the central part of the sample population. This stacking technique can have many advantages over the commonly used straight mean stacking. In addition to minimizing the effect of noise bursts, smart stacking enhances the amplitude of stacked reflections and removes frequency distortions caused by poor static correction, insufficient stretch muting, and imperfections in velocity analysis. This consequently results in a stack with higher temporal resolution and more spatial coherency than traditionally stacked seismic sections.