Iranian Journal of Oil & Gas Science and Technology
Volume:10 Issue: 1, Winter 2021

Flaring of gas often having high heating value results in considerable economic and energy losses in addition to significant environmental impacts. Power generation through combined gas and steam turbine cycles may be considered as a suitable flare gas recovery process. Thermal sea-water desalination is a process that requires a considerable amount of heat; hence it may be used in downstream of power generation cycles. Energy is the largest section of the water generation cost of all desalination processes. The energy cost of thermal distillation sea-water plants is close to 50-60% of water generation costs. In the current study, the generation of power and desalinated water through the gas turbine cycle, steam cycle, and multistage flash (MSF) method using flare gas of cheshmeh khosh are investigated. The economic parameters related to the different scenarios considered for the production of power and water are evaluated in the current research. According to the economic evaluation carried out, the most economically profitable scenarios for the investigated co-generation plant is generating as much as possible power in the steam turbine and using the remaining heat in the low-pressure outlet steam in the MSF desalination process. The results show that by increasing steam turbine outlet pressure from 3 bar to 78 bar, power and water generation is changed from 697 to 581 MW and 1557 to 2109 m3/h, respectively. Also, by increasing the outlet pressure of the steam turbine from 3 to 78 bar, the total capital cost is changed from 1177 to 1192 MUSD, and the operating cost is changed from 117.85 to 117 MUSD/year. Finally, operating profit will decrease from 300 to 50 MUSD/year, and payback time will change from 3.92 to 4.75 years.

The conjugation of two or more Artificial Intelligent (AI) models used to design a single model that has increased in popularity over the recent years for exploration of hydrocarbon reservoirs. In this research, we have successfully predicted shear wave velocity (Vs) with higher accuracy through the integration of statistical and AI models using petrophysical data in a mixed carbonate-siliciclastic heterogeneous reservoir. In the designed code for multi-model, first Multivariate Linear Regression (MLR) is used to select the more relevant input variables from petrophysical data using weight coefficients of a suggested function. The most influential petrophysical data (Vp, NPHI, RHOB) are passed to Ant colony optimization (ACOR) for training and establishing initial connection weights and biases of back propagation (BP) algorithm. Afterward, BP training algorithm is applied for final weights and acceptable prediction of shear wave velocity. This novel methodology is illustrated by using a case study from the mixed carbonate-siliciclastic reservoir from one of the Iranian oilfields. Results show that the proposed integrated modeling can sufficiently improve the performance of Vs estimation, and is a method applicable to mixed heterogeneous intervals with complicated diagenetic overprints. Furthermore, predicted Vs from this model is well correlated with lithology, facies and diagenesis variations in the formation. Meanwhile, the developed AI multi-model can serve as an effective approach for estimation of rock elastic properties. More accurate prediction of rock elastic properties in several wells could reduce uncertainty of exploration and save plenty of time and cost for oil industries.

In Iran, power plants use liquid fuels such as heavy fuel oil (HFO) or mazut to prevent disruption in power generation. The high percentage of sulfur compounds in HFO and the lack of efforts to remove it, causing significant damage to the environment. The purpose of this research is performing a techno-economic analysis on the Hydrodesulfurization (HDS) process of HFO. The results showed that for removing 85% of sulfur compounds from HFO with a volume flow rate of 250 m3/h that includes 3.5% wt sulfur compounds, the total capital investment and the net production cost are 308.9 million US$ and 114.5 million US$/year, respectively. Besides, the sensitivity analysis indicates that with a 100% increase in the catalyst loading, the mass percentage of sulfur compounds in the HFO will be decreased by 15% more. Also, 6.4% and 32% will add to the total capital investment and net production cost, respectively. With a 100% increase in the gas to oil ratio, the mass percentage of sulfur compounds in the HFO will be decreased by 15.3% more. Also, 43.8% and 6% will be added to the total capital investment and net production cost, respectively. With a 100% increase in the pressure of the HDS process, the mass percentage of sulfur compounds in the HFO will be reduced by 20.75% more. Also, 43% and 6.75% will be added to the total capital investment and net production cost, respectively. Ultimately, with a 100% increase in the inlet temperature of beds, the mass percentage of sulfur compounds in the HFO will be reduced by 5% more. Among the effective operational parameters, hydrogen consumption has the greatest impact on net production cost and payback period, and the pressure of the Hydrodesulfurization process has the greatest impact on increasing the total capital investment of the process.

Rapid development of technologies, their increasing complexity and variety, together with limited organizational resources and efforts for survival in industrial competitions have made the task of appropriate technology selection a major challenge. The present research is aimed at the formulation of technology strategy related to oil production in one of the west Karoon oil fields in Iran. At the first, the processes and challenges of production in the studied oil field are recognized by the experts’ survey. Then, the priority of the challenges is evaluated and four key challenges of the considered field are recognized by using a paired comparison questionnaire and Chang Fuzzy AHP. In the next step, the existing and new technologies of oil production in the four recognized key challenges are determined. For each of the recognized technologies, the attractiveness assessment and capability assessment questionnaire are designed based on Jolly indexes and distribute in a sample composed of production engineering experts. Sampling is done by the non-random and purposive-judgmental method. Based on the results of the questionnaires, the attractiveness-capability matrix is designed by Morin’s model, and then based on the obtained technology portfolio, the strategies of each of the four areas are formulated and discussed.

Gasoline obtained from the fractionation of indigenous natural gas condensate has low octane number (78) and is therefore of limited uses. Lead-based octane boosting and catalytic reforming are not the viable methods for many fractionation plants. This study was therefore aimed to develop an inexpensive conceptual alternative method for boosting the octane number of gasoline. Natural gas concentrated in methane having high octane number (more than 100) was absorbed in the gasoline to boost the octane number partially (86). Selective additives i.e. ethanol, tert-butyl alcohol, methylcyclopentane, toluene, iso-octane and xylene were blended first with the gasoline to aid the absorption of natural gas molecules. The loss of absorbed gas molecules from gasoline with the increase in temperature was also observed. It is therefore required to try for avoiding any increase in temperature in the finished gasoline. The developed conceptual method is promising. The findings of this simulation study would be useful for more studies towards the development of an affordable alternative method for fractionation plants for boosting the octane number of gasoline derived from natural gas condensate.

In recent years, the use of natural surfactants as surface active agents in chemical methods of oil recovery over chemical surfactants has been under consideration due to the absence of environmental problems. In this study, a new plant, Albizia julibressin (Albizia), was introduced as a natural surfactant. Our novelty resides in a unified approach that deals with the introduction of Albizia julibressin (Albizia) as a new natural surfactant, interpretation of the chemical EOR objectives, interface reactions, and the induced optimization to improve oil recovery. For this purpose, the plant was extracted using Soxhlet extraction method, aqueous base solutions and interfacial tension between natural surfactant aqueous solutions and kerosene as an oil phase were measured by pendant drop method. The critical micelle concentration structures formed by this material has been determined by interfacial tension tests and confirmed by electrical conductivity tests. The results show that Albizia extract at 3.5 wt% begins to form micelles structures, which is the critical concentration of Albizia plant micelles. At this concentration, the interfacial tension between the deionized water and the oil phase is reduced from 34 mN /m to 10 mN/m, which indicates a significant decrease in interfacial tension by this plant. Carbonate rock was employed to core flooding experiments in order to investigate the effect of Albizia extract (AE) on oil recovery. Also based on results, by using AE, wettability of oil-wet carbonate rocks, was altered from about 165.02◦ to 86.59◦. Finally, AE enhanced ultimate oil recovery about 11.6% of original oil in place in tertiary recovery for a carbonate rock.

< p>One of the most important factors through the miscible gas injection process is to determine the Minimum Miscibility Pressure. According to the definition, the minimum miscibility pressure is the minimum pressure at which, at a constant temperature, the oil and gas injected can dissolve together to form a single phase. This pressure is typically abbreviated as MMP. Among the available methods for determining the minimum miscibility pressure, laboratory methods including slim tube test and ascending bubble apparatus test are more widely utilized. Although the mentioned tests have high measurement accuracy, they are very time consuming and expensive. Therefore, the determination of the minimum miscibility pressure is usually done using computational and simulation approaches that also have high accuracy. Conducting PVT tests and determining their MMP using slim tube method was previously performed. In this study, the minimum miscibility pressure of reservoirs was determined by applying three methods of simulation with PVTi software, simulation with Eclipse 300 software and using Empirical Correlations. By comparing the obtained results and the laboratory results, it was revealed that the simulation by Eclipse 300 is regarded as the fastest and most accurate approach.