Iranian Journal of Oil and Gas Science and Technology

Abstract The complicated nature of oil and gas projects demands the deployment of integrated and effective project management methodologies to achieve the project objectives, including the scope, cost, and timing of the project. However, the availability of alternative methods such as PMI/PMBOK, IPMA, and PRINCE2; high project failure rate; and limited resources can make decision-making challenging for project managers. Identification and ranking of the most critical factors in project management could be made through different methods, i.e., MCDM, regression analysis, or structural equation modeling, depending on the nature of the data and the purpose of the research. The primary purpose of this research is to provide insight into the effects of PMBOK’s 10 knowledge areas, including integration management, scope management, time management, cost management, quality management, human resources management, communication management, risk management, procurement management, and stakeholder management on critical success factors in Iran’s oil and gas industry. PMBOK knowledge areas were measured through the project management planning quality (PMPQ) survey, and the dependent variables, which were critical success factors, were operationalized through the project implementation profile (PIP) questionnaire. A total of 100 questionnaires were distributed among project managers, senior managers, and project experts in oil and gas organizations in Iran, and 72 acceptable responses were received and analyzed through structural equation modeling (SEM). The model was statistically significant and accounted for 33.7 % of the variation of CSFs. The standardized root mean square residual (SRMR) value of the modified model was 0.098, so the model fitting was appropriate. The overall positive relationship between the variables was also observed. The results of SEM analysis indicated that scope management was the most practical knowledge area with a weight equal to 0.855, followed by communication management and risk management with weights equal to 0.818 and 0.756, respectively.  

Abstract Separating two immiscible liquids from gas is essential to produce light liquid, heavy liquid, and vapor phases. Water separation from hydrocarbons is a practical example in the oil industry. For such separation in industry, a three-phase separator is used. In this study, different parameters and the weight of the three-phase separator were optimized with the genetic algorithm (GA). Finally, the total cost of manufacturing the separator was decreased. Different types of three-phase separators are vertical, horizontal, and spherical. The separator worked in operating conditions of 172 kPa and 445 K, and the actual weight of the separator was 8131 kg. For the optimization target, the flow of vapor, light liquid, and heavy liquid was considered constant during the optimization process. The objective function (OF) was obtained from the weight of the separator and three multiparameter equations. Also, seven parameters, including the separator aspect ratio (L/D), the height of heavy liquid (H_HL), the height of light liquid (H_LL), the hold-up time (T_H), the surge time (T_S), the low liquid level (H_LLL), and the vapor level (H_v), were used in GA as constraints. The weight of the optimized separator was calculated at approximately 6001 kg. Hence, with this method, the total weight of the separator decreased by about 26.2 % as compared to the actual weight of the separator. On the other hand, the maximum difference between the answers was 3.3%, which was acceptable. Further, the error analysis of the predicted results was calculated by mean absolute percentage error (MAPE) for seven design parameters of the three-phase separator and separator weight, which were in an acceptable level of accuracy. The presented approach could have potential application for developing low-cost manufacturing of three-phase separators in the petroleum industry.

Abstract An essential transport characteristic that links a substance's molar (mass) flux to its concentration gradient is the molecular diffusion coefficient. For modeling and performance forecasting of solvent-aided recovery processes of heavy oils such as VAPEX and SAGD; a reliable and accurate estimation of the molecular diffusion coefficient is a crucial input. Despite the importance of this parameter, there is no approved way to measure it, especially in systems with heavy oil and gaseous solvents that have limited solubility. This can be as a result of the intricacy of experimental measures and the challenge of analyzing experimental data. There are two direct and indirect methods for measuring the diffusion coefficient, the direct method has not been addressed because it is expensive and time-consuming. Indirect methods include Constant-Volume Methods (Pressure Decay), Constant-Pressure, Refractive Index, Nuclear Magnetic Resonance (NMR), X-ray Computer-Assisted Tomography (CAT), Pendent drop and Microfluidics. The advantage and disadvantages of these experimental methods established for diffusivity measurements of the gaseous solvent in heavy oil systems are discussed in this article. According to the investigations carried out in this study, the Constant-Volume Methods (Pressure Decay) with the least error percentage (1.05%) was chosen as the best method for measuring the diffusion coefficient. The diffusion coefficient of light and heavy oil was compared, and light oil has a higher diffusion coefficient.

Abstract The formation of heat-stable salts (HSS), such as acetate, formate, oxalate, and thiosulfate, in gas-sweetening units creates various issues, including corrosion, high foaming, and reduced unit efficiency. This research aims to investigate eliminating heat-stable salts using an anion-exchange resin. The findings indicated that removing approximately 85% of acetate anion salt from an amine solution at a solution-to-resin ratio of 30 was feasible. Two adsorption models, Langmuir and Freundlich, were employed to analyze the equilibrium adsorption of acetate anion salt. The results indicated that the Langmuir adsorption isotherm aligned more closely with the data obtained from the acetate anion ion exchange process with the resin. Furthermore, it was determined that the maximum adsorption capacity for acetate onto the resin was 15 mg/g at a temperature of 25 °C. The impact of contact time during adsorption was examined using quasi-first-order and quasi-second-order kinetic models and an intra-particle model. The results indicated that the quasi-first-order kinetic model provided the best fit to the data, and equilibrium adsorption was achieved after approximately 70 min. Thermodynamic parameters were also investigated, revealing a ΔH value of –12.7370 kJ/mol, indicating an exothermic adsorption process. Based on the studies, utilizing the selected resin appears to be a suitable option for removing heat-stable salts.

Abstract Pipelines are considered the most practical way to transport oil and gas. However, some factors, such as corrosion and third-party damage, can lead to severe incidents. Appropriate risk assessment can help reduce the risk of pipeline systems. Prioritizing repairs, scheduling physical integrity assessments, and developing emergency plans cannot be adequately done without implementing an appropriate risk assessment method. Risk consists of the probability of failure (PoF) and consequence of failure (CoF) and, in many cases, is obtained from the failure statistics published by the pipeline operators. In an endeavor to apply more engineering concepts to the highly statistics-dominated idea of risk assessment, the PoF can be calculated using finite element and Monte Carlo methods. This paper is specifically concerned with finding the PoF caused by excavations neighboring a buried pipeline, a form of failure rarely considered as most studies about third-party damages are concerned with the direct hit as a failure cause. Hence, a Python script was written that modeled the excavations using Abaqus. The soil was modeled using the Mohr-Coulomb plasticity approach, while the pipe was modeled as a shell. The excavation adjacent to the pipe would cause the pipe to deflect due to gravity. The stress caused by this deflection was compared to the yield stress to determine whether or not it would fail. To determine the probability of failure, this iterative process was carried out for excavations of different sizes using a Monte Carlo method. Additionally, a methodology was implemented to address the issue of computationally expensive models. The method proposed in this paper was compared and weighted against other standard procedures to determine whether the advantages of risk assessment based on finite element analysis (FEA) could justify its complexity.

Abstract The importance of studying Quaternary deposits has increased to such an extent that it now occupies a significant part of research in different parts of the world. In oil-rich countries, including Iran, pollution caused by oil industry activities such as drilling and exploitation has seriously threatened the sediments and soils around these areas. The Abteymour oilfield is one of the big fields in southwestern Iran, located in the area of agricultural lands. As a result, it is essential to evaluate its environmental effects. In this research, 33 surface soil samples were collected, and in addition to measuring the concentration of heavy metals, some physical and chemical characteristics of the soil were measured. Statistical analyses such as correlation coefficient, principal component analysis, and cluster analysis were used to identify the source of pollutants. Environmental geological indices such as geoaccumulation index (Igeo), enrichment factor (EF), contamination factor (Cf), and Nemro integrated pollution index (NIP) were used to determine the level of heavy metal pollution. The cluster analysis results stated that the studied elements were clustered in two groups. Also, the factor analysis results showed that 89% of the variation of the studied parameters was affected by two factors. The results of the statistical analysis demonstrated that the pollution in the region was of anthropogenic origin, and the activities related to the extraction and exploitation of the Abteymour oilfield, agricultural activities, and wastewater impacted the soil quality in the area. Investigation of the pollution level of the samples based on the Igeo, EF, Cf, and NIP indices indicated that the samples were unpolluted for most of the studied elements. Some samples had low pollution levels for elements Na, Mg, Cr, Ni, Sr, Cu, Li, and Pb. Sulfur (S) also included all pollution levels although most of the samples were at the medium level. Based on the modified contamination degree index (mCd) and ecological risk of the sum of elements (RI) indices, 100% of the samples had very low levels and low risk, respectively. Due to the continuation of agricultural activities and oil industries in the studied area, there is a possibility of increasing the level of pollution.