Iranian Journal of Oil & Gas Science and Technology
Volume:2 Issue: 4, Autumn 2013

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.

Flow unit characterization plays an important role in heterogeneity analysis and reservoir simulation studies. Usually, a correct description of the lateral variations of reservoir is associated with uncertainties. From this point of view, the well data alone does not cover reservoir properties. Because of large well distances, it is difficult to build the model of a heterogenic reservoir, but 3D seismic data provides regular sampling that can improve reservoir spatial description.
In this study, seismic attribute analysis was used to predict flow zone indicator (FZI) values of a carbonate reservoir by using seismic and well log data. First, a 3D acoustic impedance volume was created as an external attribute for seismic data analysis. To improve the ability of FZI prediction, the maximum number of attributes from multiattribute analysis was computed by using a step-wise regression technique. To verify the results of multiattribute technique, the cross plot analysis of multiattribute method was performed. It was found that the R2 value of the correlation between the predicted and actual FZI is as high as 0.859 with an average error value of 2.34 µm. The analysis of the results of multiattribute technique showed that it was an effective technique for FZI prediction in hydrocarbon reservoirs. Such accuracy in building a 3D distribution of FZI provides a good insight into reservoir production zones. The results clearly indicate that the methodology proposed herein can successfully be used to specify the locations of new wells for the purpose of future production or injection plans.

Control of well drilling operations poses a challenging issue to be tackled. The loss of well control could lead to the occurrence of blowout as a severe threat, involving the risk of human lives and environmental and economic consequences. Conventional proportional-integral (PI) controller is a common practice in the well control operation. The small existing margin between pore pressure and fracture gradients jeopardizes the efficiency of this conventional method to exercise an accurate and precise pressure control. There is a significant incentive to develop more efficient control methodologies to precisely control the annular pressure profile throughout the well bore to ascertain the down-hole pressure environment limits. Adaptive control presents an attractive candidate approach to achieving these demanding goals through adjusting itself to the changes during well drilling operations. The current paper presents a set of adaptive control paradigms in the form of self-tuning control (STC). The developed STC’s are comparatively evaluated on a simulated well drilling benchmark case study for both regulatory and servo-tracking control objectives. The different sets of test scenarios are conducted to represent the superior performance of the developed STC methods compared to the conventional PI control approach.

Cementation factor is a critical parameter, which affects water saturation calculation. In carbonate rocks, due to the sensitivity of this parameter to pore type, water saturation estimation has associated with high inaccuracy. Hence developing a reliable mathematical strategy to determine these properties accurately is of crucial importance. To this end, genetic algorithm pattern search is employed to find accurate cementation factor by using formation resistivity factor and the porosity obtained from laboratory core analyses with considering the assumption that tortuosity factor is not unity. Subsequently, particle swarm optimization (PSO) fuzzy inference system (FIS) was used for the classification of cementation factor according to the predominated rock pore type by using the input variables such as cementation factor, porosity, and permeability to classify the core samples in three groups, namely fractured, interparticle, and vuggy pore system. Then, the experimental data which was collected from Sarvak formation located in one of the Iran southwestern oil fields was applied to the proposed model. Next, for each class, a cementation factor-porosity correlation was created and the results were used to calculate cementation factor and water saturation profile for the studied well. The results showed that the constructed model could predict cementation factor with high accuracy. The comparison between the model presented herein and the conventional method demonstrated that the proposed model provided a more accurate result with a mean square error (MSE) of around 0.024 and led to an R2 value of 0.603 in calculating the water saturation.

Copper trimesate (Cu-BTC) MOF has been pointed out as a promising adsorbent for separating carbon dioxide from methane. However, MOF’s need to be shaped prior to their use in packed bed adsorbers in order to reduce pressure drop; on the other hand, the production of mechanically resistant shaped bodies reduces their adsorption performance. In this work, Cu-BTC tablets provided by BASF are evaluated to perform CO2/CH4 separation through adsorption. The adsorption capacity of pure carbon dioxide from methane was measured in a magnetic suspension balance between temperatures of 308 and 373 K up to a pressure of 700 kPa. The evaluated material presents higher adsorption capacity than previously studied shaped samples with a carbon dioxide and methane adsorption capacity up to 3.07 and 0.63 mol/kg at 100 kPa and 308 K respectively. Moreover, the experimental data were fitted with the Langmuir model. Isosteric heats of adsorption were obtained to be 22.8 and 15.1 kJ/mol for CO2 and CH4 on Cu-BTC tablets respectively, which indicates a strong adsorption of carbon dioxide on these adsorbents. Also, single and binary breakthrough curves were measured in the same temperature range and atmospheric pressure by using Cu-BTC tablets as the adsorbent. The preferential adsorption capacity of CO2 on nanoporous copper trimesate (Cu-BTC) indicates that this material can be used for methane purification from natural gas.

MSU-S mesoporous catalyst with [SiO2]/[Al2O3] ratio of 55 was synthesized using tetrapropylammonium hydroxide (TPAOH) as a structure directing agent and hexadecyltrimethylammonium bromide (CTAB) as a surfactant. The catalytic activity of the calcined sample was evaluated for the dehydration of methanol to dimethyl ether (DME) in a vertical fixed bed microreactor at a weight hurly space velocity (WHSV) of 5 hr-1 .Temperature ranged from 230 °C to 380 °C and pressure was kept constant at 1 bar. The catalyst was characterized by XRD; consequently, the mesoporous structure of MSU-S catalyst was verified. The activity, selectivity, and stability of MSU-S catalyst were investigated in a vertical fixed bed reactor. An increase in methanol conversion was observed by increasing temperature. The equilibrium conversion of methanol was almost reached at 380 °C and selectivity decreased from 100% to 97% as temperature rose from 200 °C to 380 °C. The stability of MSU-S (Michigan State University) catalyst was investigated for 12 hr at 380 °C and a stable methanol conversion was observed during the mentioned time.