Iranian Journal of Oil and Gas Science and Technology

Abstract Electric Submersible Pumps (ESPs) are widely used in oil and gas production, yet their reliability is challenged by diverse failure modes and inconsistent monitoring practices across manufacturers. This study develops a vendor-agnostic Key Performance Indicator (KPI) framework to enable objective comparison of ESP performance across different brands.
A representative dataset comprising 330 ESP runs across three major ESP brands was analyzed using standardized failure classification and statistical techniques, including Weibull reliability modeling. Failure modes were categorized into mechanical, electrical, hydraulic/gas-related, material, and operational classes, and correlated with vendor-independent KPIs derived from thermal, electrical, hydraulic, and operational measurements.
The results reveal distinct brand-specific failure patterns. Brand A is dominated by electrical failures associated with reduced thermal margin, Brand B exhibits longer characteristic life with wear-out-dominated behavior, and Brand C shows higher susceptibility to hydraulic instability driven by gas interference. Several KPIs, including Motor Temperature Margin (MTM), Current Imbalance (CI), and Gas Interference Index (GII), consistently provide early-warning indicators of failure.
The proposed framework enables cross-brand benchmarking, improves interpretability of ESP health monitoring, and supports the development of predictive maintenance strategies independent of proprietary vendor systems.

Abstract Gas lift is a principal technique used for artificial lifting and Enhanced Oil Recovery (EOR) method, facilitates oil flow in mature fields those in the latter half of their productive life by injecting high-pressure gas into the wellbore to reduce column density. However, the thermodynamics of gas injection in wells requiring high differential pressures introduce severe flow assurance challenges. The intense Joule-Thomson cooling effect across injection chokes is the primary driver of gas hydrate formation. In the studied field (Aghajari), the current hardware-based mitigation strategy employs Thermal Chokes, which utilize the enthalpy of live crude oil to heat the injection gas. Despite this, operational evidence indicates that during cold seasons and for wells with high pressure drops, this system proves inefficient, leading to freezing in injection lines and flow interruption. In the absence of inhibitor injection systems, operators are compelled to resort to reactive measures such as flaring injection gas to induce pressure shocks and clear blockages. This vicious cycle not only results in capital loss but also leads to production deferment and excessive workload for human resources. This research aims to propose a proactive process-based solution by synergizing data mining and computational intelligence. Through the analysis of 5,960 operational records from 101 wells (extracted from the WIMS system), an Artificial Neural Network (ANN) model was developed to serve as a virtual sensor, predicting gas thermodynamic behavior and post-choke temperature with 98.5% accuracy. The core novelty of this study lies in the simulation and validation of a dual-stage pressure reduction strategy. Results demonstrate that splitting the pressure drop profile reduces cooling intensity by up to 60%, maintaining the fluid outside the hydrate stability zone throughout the expansion path. This approach enhances safety and production stability while eliminating the need for costly physical interventions.

Abstract Nowadays, use of visco-elastic surfactants as the main component of gel diverters is becoming more and more common among well completion engineers, as well as stimulation service companies. Gel diverter, as other kinds of diverters, is used in multi-layered carbonated reservoirs to diver acid into less permeable sublayer. As use of these materials becomes more common, modeling and simulating the gel-acid injection process becomes more required. In this study, a mathematical model is generated to simulate gel-acid injection process, and experimental data is compared with data predicted by the model. The purpose of this study is to investigate the field possibility of injection gel-acid and to generate a model for simulating this process, in order to smart permeability enhancement in Ahwaz oilfield, one of Iranian Southwest oilfields. The solutions predicted by model are in an acceptable correlation with experimental data. The generated model can be used for other multi-layered carbonated oilfields.

Abstract This paper investigates the role of the adequate thickness of the Asmari reservoir formation zones on oil production in one of the Iranian carbonate oil fields. Adequate thickness is a term that includes the total gross thickness of rocks by lithofacies for a selected wellbore. The lithology of the Asmari formation in the studied area consists of dolomite, sandstone, lime, dolomitic-lime, sandstone-shale, and shale limestone dolomites. Based on the existing well-logs, the average shale volume, the effective arithmetic means of porosity in the gross intervals, and average water saturation or hydrocarbon-bearing increments of the studied field are calculated using well-logs. In wellbore #A, a depth interval of 2214 to 2296 m shows 9.6% average shale volume, 27.2% average water saturation, and 20.9% average porosity. A depth interval of 2213 to 2280 m, in wellbore #B, shows 6% average shale volume, 21.25% average water saturation, and 28.5% average porosity. Based on our petrophysical assessments, we divide the Asmari reservoir in the studied field into eight zones. Zone 1 is made of carbonate (calcareous and dolomitic), and zones 2–5 are mainly sandstone; zones 7 and 8 are calcareous and shale, and zone 6 is a mixture of all the rocks mentioned above. Among these eight zones, there are two primary hydrocarbon productive zones. The numerical calculation of in situ oil volume showed that zone 2 contains 65% of oil volume in this reservoir. With more than 80% sand, this zone has the highest net hydrocarbon column.

Abstract 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.

Abstract In the current study, the kinetics of asphaltene particle flocculation is investigated under a shear flow through numerical simulation. The discrete element method (DEM) is coupled with computational fluid dynamics (CFD) to model the agglomeration and fragmentation processes. In addition, a coalescence model is proposed to consider the attachment of colliding particles. The changes in mean asphaltene floc size, the particle size distribution (PSD) of asphaltene flocs over simulation time, and the average fractal dimension are presented. Moreover, the effect of fluid velocity on the kinetics of asphaltene flocculation is examined. The mean asphaltene floc size increases exponentially at first, and then the growth slows; finally, it ceases due to the establishment of a dynamic equilibrium between the agglomeration and fragmentation processes. As expected, asphaltene PSD’s move from fine to coarse sizes during the simulation. Log-normal distribution matches the PSDs best, which is in agreement with the nature of asphaltene. As fluid velocity increases, the dynamic equilibrium is attained more rapidly at a smaller mean floc size and higher average fractal dimension; furthermore, PSDs shift to smaller asphaltene floc sizes. The obtained average fractal dimensions of the asphaltene flocs are in the range of 1.65 to 1.74, which is compatible with the values reported in the literature. Eventually, a semi-analytical model is utilized to fit the simulation results. It is found out that the semi-theoretical model is capable of predicting the evolution of asphaltene particle size appropriately.

Abstract In matrix acidizing operations, the main goal is increasing permeability. For production engineers, it is desirable that acid could be injected into whole [M.N.1] [amehri.gh2] pay zone. Sometimes, this pay zone has a long height and various sub-layers which have different permeability values. To prevent acid from going completely into the most permeable sub-layer, one of the useful techniques is using diverters, and one of the major groups of diverters is gel diverters. Diverter viscosity changes by temperature and pH, and an increase in viscosity leads to a decrease in its permeability; thus, acid can permeate further through less permeable sub-layers. In this study, two kinds of different viscoelastic surfactants (VES) provided by two different companies were used to produce gel to divert acid into a core plug sample having lower permeability in a dual parallel acid injection set-up. The core plug samples were taken from the pay zone of Ahwaz oilfield, one of Iran southwest oilfields. Before performing the injection test, some viscosity measurement tests were carried out. Unfortunately, one of these two VES’s did not have an acceptable quality and failed to pass the injection tests. However, the other one passed all the tests successfully and diverted the injection fluid. The water permeability values of the low-perm and high-perm core plug samples were 0.91 md and 6.4 md respectively, whereas, after injection, they rose to 1.5 and 18.5 md respectively.

Abstract In this paper, the potentials of using particles, especially nanoparticles, in enhanced oil recovery is investigated. The effect of different nanoparticles on wettability alteration, which is an important method to increase oil recovery from oil-wet reservoirs, is reviewed. The effect of different kinds of particles, namely solid inorganic particles, hydrophilic or hydrophobic nanoparticles, and amphiphilic nanohybrids on emulsion formation (which is cited as a contributing factor in crude oil recovery) and emulsion stability is described. The potential of nanohybrids for simultaneously acting as emulsion stabilizers and transporters for catalytic species of in situ reactions in reservoirs is also reviewed. Finally, the application of nanoparticles in core flooding experiments is classified based on the dominant mechanism which causes an increase in oil recovery from cores. However, the preparation of homogeneous suspensions of nanoparticles is a technical challenge when using nanoparticles in enhanced oil recovery (EOR). Future researches need to focus on finding out the proper functionalities of nanoparticles to improve their stability under harsh conditions of reservoirs.