Iranian Journal of Oil and Gas Science and Technology

Abstract Excessive water production represents a significant economic and operational burden in the petroleum industry, necessitating sophisticated control measures to mitigate costs associated with water oil separation, scale formation, and equipment corrosion. This investigation characterizes the performance of preformed particle gels (PPG) as a robust chemical water shutoff treatment through comprehensive rheological and swelling kinetics studies. Experimental results demonstrate that PPG viscosity is highly sensitive to concentration; specifically, a twofold increase in concentration (from 2500 to 5500 ppm) results in a tenfold increase in viscosity. The rheological behavior was successfully modeled using the Cross equation, facilitating the derivation of a unified mathematical model that predicts viscosity as a function of concentration and shear rate. Crucially, at a calculated shear rate of 0.14 s⁻¹ based on the assumption that injection velocity is 100 times the reservoir oil movement PPG maintains sufficient viscosity for effective flow diversion. Furthermore, the study explores the influence of agitation and salinity on swelling performance. Stirring was found to accelerate swelling kinetics, shifting the mechanism from Fickian diffusion at zero RPM to a transport dominated mechanism (n ≈ 0.85) due to the simultaneous activation of multiple diffusion pathways. Salinity experiments utilizing KCl and MgCl₂ reveal that divalent cations (Mg²⁺) are significantly more effective at inhibiting swelling than monovalent cations (K⁺) due to charge neutralization of carboxylate groups. Morphological analysis via Scanning Electron Microscopy (SEM) suggests that ions with larger radii obstruct the gel pores, a phenomenon that can be mitigated during synthesis through the introduction of nonionic hydrophilic monomers and pore forming agents such as ethanol or ammonium bicarbonate. Finally, the research identifies diffusion limited aggregation (DLA) as the dominant growth mechanism. Modified DLA models were developed to predict salinity dependent swelling, providing a rigorous framework for optimizing PPG treatments in heterogeneous reservoirs

Abstract Recently, several techniques have been suggested for measuring fluid density, as a highly applicable parameter in industries. Among these, gamma-ray densitometry is highly recommended due to its benefits such as non-destructive, operator dependence and online monitoring. This study evaluates the feasibility of using gamma-ray-based density measurement at the Shahid Ahmadi-Roshan oil storage facility in Kerman Province, Iran. The results of this work are valuable due to the specific condition of pipeline maps and their physical properties at this site, as unique case study. A Monte Carlo simulation was conducted with FLUKA code, modeling two pipelines used for gasoline and gas oil transport, based on the dimensions, geometries, and elemental compositions of each to replicate actual conditions. Cobalt-60 and Cesium-137 isotropic gamma-ray sources were defined to measure photon flux with a simulated detection system. The simulations explored various densities of gasoline and gas oil, recording flux values at each density level. According to the results, both gamma-ray sources could effectively serve as primary components of the proposed densitometer. However, Cesium-137 is preferable due to its significant photon flux variations corresponding to changes in pipeline wall thickness and fluid density. A gamma-ray-based densitometer is recommended for practical use at this site, as it offers a more efficient alternative to the current operator-dependent, offline hydrometric method. Given the proximity of the two pipelines, a single-source dynamic densitometer could be implemented to substantially lower costs.

Abstract Unlike traditional approaches, Support Vector Regression (SVR), Multilayer Perceptron Neural Network (MLPNN), Probabilistic Neural Network (PNN), Random Forest (RF), Decision Tree (DT), and eXtreme Gradient Boosting (XGBoost) are utilized as predictive algorithms to simulate the cementation exponent based on various pore descriptions and total porosity. To optimize the parameters of the MLPNN approach, Levenberg-Marquardt (LM) is coupled with MLPNN, leading to the development of a hybrid approach named MLPNN-LM. This hybrid model efficiently optimizes neural network parameters, significantly improving accuracy and convergence speed. The necessary databank for constructing, validating, and predicting with the proposed models is derived from Ragland's work and classified into test, validation, and train subsets. The results reveal high precision for the hybrid MLPNN-LM and RF techniques, with key statistical measures such as the Average Absolute Percentage Relative Deviations (AAPRD%) (i.e., the percentage of relative error) of 4.3781% for MLPNN-LM and 4.8690% for RF, and determination coefficients (R²) (i.e., the fitness magnitude of estimated and measured values around Y=X line) of 0.8654 for MLPNN-LM and 0.8731 for RF. The highly accurate estimates of the cementation exponent provided by MLPNN-LM and RF surpass those from commonly applied literature correlations. Sensitivity analysis shows the significant impact of interparticle, moldic, and connected vuggy pore types on the modeling output. The trustworthiness of the databank and the accuracy of the proposed MLPNN-LM and RF approaches are verified by Williams’ plot, with approximately 93.75% and 91.96% of the databank within the applicability domain, respectively. Trend analysis demonstrates a good match of predicted cementation exponent with actual data, especially for deep formations (i.e., depth greater than 1200 m) and tight carbonate reservoirs (i.e., total porosities less than 10%), where traditional correlations face challenges due to the noticeable complexity in the behavior of cementation exponent.

Abstract The mechanisms of Low-Salinity Water (LSW) flooding in carbonate reservoirs remain less well understood than in sandstones. This study investigates the role of rock composition through a comparative experimental analysis of genuine limestone from the Shadegan oil field and pure synthetic calcite. Core flooding tests, contact angle measurements, zeta potential analysis, and pH monitoring were conducted under reservoir conditions (70°C, 100 bar). Results show that tertiary LSW injection recovered 14.5% of the initial oil in place in limestone, compared to only 3.4% in pure calcite. This significant difference is attributed to a more pronounced wettability shift towards water-wet conditions (42° contact angle reduction vs. 16° in calcite), driven by a stronger negative zeta potential shift (-7.7 mV vs. -4.1 mV) in the genuine rock. XRF analysis revealed the presence of silica, sulfate, and phosphate impurities in the limestone, which amplified the surface charge alteration. The study concludes that trace non-clay minerals significantly enhance LSW efficacy in carbonates, providing new insights for optimizing EOR in complex carbonate formations.

Abstract Matrix acidizing is one of the effective methods for carbonate reservoirs, aiming to reduce formation damage, enhance well production, and improve hydrocarbon recovery. Although numerous studies have examined acid fluid types and their interaction with reservoir rock, few have combined technical matrix acidizing with economic evaluation for Iranian reservoirs. This study addresses that gap by integrating a simulation-based technical and economic comparison of two acid types — 15% hydrochloric acid (HCL) and emulsified acid (SXE 15%) — in a carbonate reservoir well in Khuzestan province, Iran. The outcomes of these two scenarios, in terms of production rate, acid penetration, and wormhole creation, were modeled using WellBook software under identical conditions. Technical results indicated that emulsified acid achieved deeper wormhole penetration (approximately 5 ft versus 2.5 ft for HCL), greater skin factor reduction (from +7 to –2.85 versus +0.31 for HCL), and higher production increase (from 0.44 to 1.13 bbl/min versus 0.75 bbl/min). Subsequently, the scenarios were evaluated economically based on two procurement methods, i.e., domestic supply in Iranian Rials and import supply in US Dollars. The economic analysis was conducted using key financial indicators such as NPV, IRR, MIRR, and PI. The technical and economic analyses demonstrated that emulsified acid outperforms HCL 15% acid in terms of production rate, wormhole penetration, and overall economic performance.

Abstract This study presents an advanced petrophysical evaluation of the Sarvak Formation in one of the major supergiant oil fields in Southwest Iran, achieved by integrating Nuclear Magnetic Resonance (NMR) log data with conventional well logs. NMR measurements from Well-A were analysed to extract critical reservoir properties—including total and effective porosity, and volumes of bound and free water—which significantly enhanced the accuracy of the petrophysical model. A multi-resolution graph-based clustering (MRGC) algorithm was developed to estimate NMR-derived parameters from conventional logs for the adjacent Well-B, where NMR data were unavailable. The MRGC model utilised gamma-ray, acoustic, density, neutron, and photoelectric logs to predict total and effective porosity, clay-bound water, irreducible water saturation, and other NMR-related parameters. The model was calibrated using data from Well-A and subsequently applied to Well-B, enabling NMR-informed petrophysical characterisation in the absence of direct measurements. The optimised petrophysical model demonstrated consistent reservoir characteristics across both wells. Average total porosity was 10.7% in Well-A and 12.2% in Well-B; effective porosity averaged 10.2% and 11.8%, respectively; clay volume was approximately 3.2% in Well-A and 3.6% in Well-B; and water saturation was 85% and 84%, respectively. Based on cutoff thresholds of 5% porosity, 15% clay volume, and 50% water saturation, net pay intervals were delineated, yielding approximately 31 m of productive zone out of 411 m in Well-A, and 30 m out of 380 m in Well-B. The NMR-augmented analysis provided more precise differentiation of hydrocarbon-bearing zones and proved more cost-effective than traditional log-based methods. This refined petrophysical workflow significantly improves reservoir characterisation, enhances the accuracy of hydrocarbon volume estimation, and supports more informed field development planning.

Abstract Recently, nanoparticles have been used to improve oil and gas production volume and enhance oil recovery (EOR). Based on our recent research, using nanoparticles such as silica and calcium oxide has a good potential for changing mechanisms in the porous media, such as interfacial tension and wettability. Low permeability carbonate plugs were selected to determine the application of nanoparticles in the porous media. Two main steps were used: 1) Using CaO and SiO₂ nanoparticles for wettability alteration, interfacial tension reduction, and improving fluid flow through porous media, and 2) Surveying the application of nanoparticles to the water alternating gas (WAG) (nanoparticles (NCs)-assisted WAG) test. The zeta potential values were stable at –56.4 ± 2 mV and –44.0 ± 3 mV for calcium oxide and silica nanoparticles, respectively, at an optimum nanoparticle concentration of 15 ppm. Calcium oxide and silica nanoparticles effectively altered the wettability from oil-wet to water-wet by surveying the intersection of two-phase relative permeability. Moreover, CaO nanoparticles performed better in low permeability carbonate porous media than SiO₂ nanoparticles regarding wettability alteration to water wetness. Based on the results and a better grade of CaO, it was selected for performing NCs-assisted WAG tests at WAG ratios of 1:1, 40 ℃, and 15 ppm. The recovery factor increased from 42.9% to 73% in the presence of CaO during NC-assisted WAG tests, and residual oil saturation decreased from 40.9% to 19.4%.

Abstract Rock-Eval pyrolysis is a thermal method petroleum geologists use to evaluate source rock characteristics and obtain geochemistry parameters. However, there are misconceptions and misuses in exceptional cases that could lead to erroneous conclusions after using the Rock-Eval pyrolysis data to evaluate the properties of organic matter. However, a cross-plot of petroleum potential (S₂) versus total organic carbon (TOC) is a useful tool for solving issues and checking the accuracy of the geochemistry parameters. The graph provides the correction criteria for the S₂, hydrogen index (HI), and kerogen types. As well as the graph measures the adsorption of hydrocarbon by the mineral matrix. In addition, this article demonstrates a manner based on the data plot of S₂ versus TOC to detect bitumen or hydrocarbon contaminations. Based on our knowledge about the Garau formation as a possible source rock in the petroleum geology of Iran, a geochemistry study by Rock-Eval VI pyrolysis and LECO carbon analyzer has been conducted on many rock samples collected from different outcrops in the Lurestan province, Aligudarz region, from southwest of Iran, High Zagros. Plotting the data on a cross plot of S₂ versus TOC, drawing the regression line, and finding the regression equation are the best methods for determining the actual values of S₂ and HI parameters and bitumen/hydrocarbon contamination. Contamination creates a y-intercept in the graph of S₂ versus TOC, making geochemistry data unreliable in two study locations. The S₂ and HI data unrealistically increase, while the T_max values decline and reduce the thermal maturity of the organic matter from its actual status. The y-intercept of the graphs is removed, and the corresponding values are subtracted from the HI and S₂ to skip the effect of contamination and obtain the actual geochemistry parameters. The cause of contamination in the Garau formation is the adhesion of heavy bitumen to organic facies due to the covalent bonds between carbon and hydrogen ions.

Abstract Column final tests face new challenges, and in addition to casing burst/collapse limitations, buckling occurrence creates serious problems. In case of a slight gap between mud and slurry densities, buckling initiation is inevitable. Casing elongation, bending, and buckling are detailed to define column behavior while testing. Buckling influences on slurry are mentioned and compared to the column without test. A new cement quality indicator is also proposed, tested, and validated via logging of wells drilled in different regions. The results are generalized to cover other situations rather than heavy sections. Further, gas migration regions, depleted reservoirs, and weak zones are all examined. Registrations confirm the appearance of buckling either while pumping slurry or pressure testing. A new modified casing selection method conjointly with an updated numerical technique is proposed to prevent buckling. Moreover, the experimental and simulation findings confirm the reliability of the proposed technique.

Abstract This research aims to investigate the effect of microwaves on the physical and chemical properties of heavy crude oil in the presence of different minerals. In this regard, the physical and chemical changes of the oil and rock powder (sand and carbonate) mixture are investigated by microwave radiation. Viscosity and temperature changes of two samples are measured. IP143 and elemental analysis (carbon, hydrogen, nitrogen, and sulfur) are used to extract and identify the composition changes of asphaltene. The viscosity and temperature changes show that for both samples at the beginning of microwave radiation, there is a decrease in viscosity due to heavy hydrocarbon particle cracking, such as asphaltene, and converting them into lighter ones. Light compounds evaporate by continuing the radiation and temperature increase; finally, the viscosity increases. The evaporation process in the carbonate powder sample starts earlier than in the sand powder. From elemental analysis, it is concluded that the sulfur and nitrogen in asphaltene decrease almost the same for both samples, and this decrease is more evident for sulfur; thus, the rock powder combined with oil does not have a significant effect on the reduction of these elements. The increase in IFT is also observed due to the evaporation of light oil compounds, and IFT increases further due to the higher temperature of the sample containing carbonate rock powder.

Abstract Knowing the characteristics of suitable environments for the precipitation of oil-prone source rocks facilitates oil explorations and leads to the development of oil fields. The current study investigates the properties of organic matter and sedimentary environment conditions of the Garau formation in various outcrop sections in Lurestan province from southwest of Iran (High Zagros) using elemental analysis, visual kerogen analysis, and Rock–Eval pyrolysis data. The geochemistry parameters indicate that the Garau formation is an excellent oil-prone source rock composed of kerogen types I and II. The oxygen index (OI) is minimal, revealing that organic matter is deposited in an anoxic sedimentary environment, suitable for preserving organic matter and hydrocarbon generation. The visual analysis of isolated kerogens from source rock samples indicates the abundance of dark amorphous organic matter (AOM) with low amounts of phytoclasts and pyrite without any palynomorph. Sedimentation appears to have occurred in deep and reduced parts of a carbonate basin during a rapid transgression. In addition, due to the effect of thermal maturation, the color of amorphous organic matter has darkened. The elemental analysis and van Krevelen diagram are employed to show the type of organic matter and reveal that the thermal maturity is related to the oil window. Elemental analysis reveals the high content of organic sulfur in the structure of kerogen. Moreover, the content of pyritic sulfur (Sp) and organic sulfur (So) is calculated.

Abstract Oil-well cementing is a multi-purpose operation in which cement slurries are prepared by mixing water, cement, and various additives and pumped into the well to isolate productive zones, protect the casing pipe, perform remedial operations, control drilling fluid lost, or abandon the well. Various additives are used to improve the mechanical properties of the slurry, like cement retarders and accelerators, which increase and decrease the thickening time of the cement slurry, respectively. Weight-enhancing additives are materials with a specific gravity higher than cement, which can weigh up the slurry to overcome the hydrostatic pressure of mud and perform an excellent cementing job. Improving the mechanical properties of these cement slurries has always been an essential issue in the discussion of oil well cementing. In this study, the effects of nanozeolite on heavy-weight oil-well cement slurry are investigated in the laboratory to improve the rheological and mechanical properties of the cement. In the designed experiments, nano-zeolite is added to the slurry with 1, 2, and 3% by weight of cement (BWOC). The results show that nanozeolite is an additive to reduce the thickening time, increase the plastic viscosity, and reduce the slurry’s yield point. Thus, it should be noted that the pumping time of the cement slurry can be adjusted using other additives based on the required cementing job timing schedule. The experiments also show that adding nano-zeolite to the cement slurry from 1 to 3% BWOC increases the free fluid of the cement slurry but does not show any effect on controlling the fluid loss. Finally, by adding 2% BWOC of nanozeolite, the compressive strength of the cement stone increases, and the initial setting time of the cement slurry decreases.

Abstract The increasing demand for hydrocarbons has prompted new recovery strategies by applying nanoparticle–surfactant flooding in chemical-enhanced oil recovery (CEOR). Some mechanisms that improve oil mobility are rock wettability alteration and reduced interfacial tension between the oil and water. In this work, silica (SiO₂) nanoparticles (NPs) were synthesized and characterized, and their effect on wettability alteration and interfacial tension (IFT) between the oil and SiO₂ nanoparticles (NPs) dispersed in sodium dodecyl sulfate (SDS) solutions was determined. Experiments on oil displacement by flooding with brine and NPs dispersed in an SDS solution were investigated in a micro glass model. X-ray diffraction (XRD) pattern and scanning electron microscopy (SEM) confirmed the mineral structure and platy polycrystalline morphologies that gave an estimated particle size of 88 nm using Scherrer’s formula. Fourier transform infrared spectroscopy (FTIR) showed characteristic symmetric and asymmetric stretching vibrations. The measured wettability alteration and IFT showed changes in wettability from water-wet toward a more water-wet condition and decreased IFT, respectively, as the SDS concentration increased. The optimum oil recovery of 67.45% was obtained at 2.08 mM SDS when SDS concentrations were varied (2.08, 6.25, 8.33, 10.42, and 14.58 mM) at a constant concentration of SiO₂ NPs (0.1 wt %). Having obtained the optimum oil volume from OOIP at 2.08 mM SDS, SiO₂ NPs concentration varied (0.05, 0.1, 0.15, 0.2, and 0.25 wt %) at a constant SDS concentration (2.08 mM). This optimized approach gave an excellent total oil recovery of 78.36% at 0.2 wt % SiO₂ NPs. Therefore, 0.2 wt % SiO2 NPs with 2.08 mM SDS should be applied in oil recovery.

Abstract One of the most important methods for enhancing oil recovery in reservoirs is chemical flooding. The performance and efficiency of these processes in increasing oil recovery depend on several factors, including the rock and fluid properties of the reservoir. Therefore, a critical step in evaluating the effectiveness of these methods is conducting laboratory studies and calculating the potential of chemical agents to recover oil. Optimal design, using new approaches such as novel chemical agents or comprehensive studies of chemical flooding at the core scale, is essential to make chemical flooding more cost-effective.
For this purpose, a laboratory study combined with integrated simulation was performed to identify the effective mechanisms in low-salinity water–polymer injection and to determine the necessary and dominant conditions for improving recovery in Iranian carbonate reservoirs. Initially, four injection scenarios were tested in the laboratory: water injection–polymer injection–low-salinity water injection, water injection–low-salinity water injection–polymer injection, water injection–low-salinity water–polymer injection, and low-salinity water injection–low-salinity water–polymer injection. Subsequently, low-salinity water–polymer flooding was simulated using the Eclipse 100 simulator to evaluate the effect of polymer injection on oil recovery and oil trapping in the reservoir rock. Finally, simulation results were validated against laboratory data.
The results demonstrated that low-salinity water injection followed by low-salinity water–polymer injection showed the best performance, improving secondary oil recovery by 63.45%, with wettability alteration identified as a key mechanism for enhanced oil recovery. The study also showed that under optimal conditions, despite mechanical degradation of the polymer, recovery of initial oil in place could reach up to 85% through controlled adsorption of polymer on the rock surface. Furthermore, initial polymer injection was found to help reduce the amount of polymer required to achieve residual oil saturation.

Abstract Sarvestan and Saadatabad oilfields produce more than 140 bbl/day of wastewater due to oil processing. Due to environmental issues, the produced water is injected into a disposal well through a pipeline with a diameter of 8 inch and a length of 5 km. Formation of inorganic scale may accelerate the need for frequent reservoir acid stimulation, restrict flow path, and generally add unpredicted costs for water injection operations. This study predicts scaling tendency and examines scale precipitation at different pressures, temperature, and mixing ratios of injection wastewater with formation water in Sarvestan and Saadatabad oilfields. The experimentally measured chemical analysis of the injection water and formation water was used to estimate the amount, type, and composition of scale due to mixing and changes in thermodynamic conditions. Scaling tendency values for eight types of scale, namely CaCO₃ (calcite), CaSO₄ (anhydrite), CaSO₄.2H₂O (gypsum), FeCO₃ (siderite), Fe(OH)₂ (amorphous), NaCl (halite), Mg(OH)₂ (pyrochroite), and KCl (sylvite), were investigated by commercial software packages OLI ScaleChem and StimCADE. The results show that the significant scales are CaCO₃ and FeCO₃ formed in Sarvestan and Saadatabad oilfields. The formation of these scales can lead to severe problems, such as disrupting equipment and decreasing production; thus, it is necessary to predict all types of scales before forming. It allows design and planning for chemical inhibitor treatment and prediction of injectivity problems and acid stimulation.

Abstract This study investigated the application of iron oxide nanoparticles in the presence of an external magnetic field to control the rheology of drilling fluids. Drilling fluid rheology is one of the most critical factors in determining the optimal fluid. Drilling fluid must have good rheological properties to carry the drilled cuttings. On the other hand, polymers in the water-based drilling fluid control fluid loss. In low-density oil-based fluids, where the water content is low, rheological control is generally difficult since there is a limitation in selecting additives. In this study, the ferromagnetic fluid has been generated by adding nanoparticles of Fe₃O₄ to silicon oil. By adding ferromagnetic fluid to the oil-based mud under the influence of the external magnetic field, we examined the rheological behavior of the oil-based drilling mud. The external magnetic field can be applied in actual conditions in the middle of a magnetic drilling string. The results showed that the magnetic nanoparticles improved the drilling mud rheological properties. Moreover, the viscosity of the oil-based fluid without nanoparticles was measured 2 cP and increased to 33 cP by adding 4 wt % of iron oxide nanoparticles under an external magnetic field of 0.321 T. The magnetic field was also used for water-based mud (WBM), and the results showed that in water-based fluids containing polyanionic cellulose (PAC) polymer, the magnetic field did not have much effect on the rheological properties of the drilling mud compared to oil-based mud (OBM). Since water is the main component of the water-based fluid, increasing the magnetic field reduces the viscosity of the water-based fluid. The magnetic field increased fluid’s rheology by adding iron oxide nanoparticles to the polymer-based fluid. The viscosity of the water-based fluid containing nanoparticles increased to 850 cP under the magnetic field.

Abstract Formation damage is reported during the secondary and tertiary stages of reservoir lifespan. One of the unpleasant sequences of formation damage caused by fine particles is permeability reduction due to pore plugging and bridging. The fine particles might exist initially in a porous medium or be introduced by external sources. In addition, there is a variety of particle types and sizes. The current research focuses on the effects of non-swelling clay minerals motions, such as the laminar ones found in Iranian sandstone reservoirs, on permeability. For this purpose, sand packs in various glass bead sizes and containing aluminum oxide as fine particles were designed to scrutinize the motion of fine particles under various pressure differences, flow rates, and concentrations. It was concluded that for each of the three sand packs regarded as the porous media in this study and composed of fine glass beads with different sizes, there is a critical flow rate as a function of glass bead size. For the flow rates lower than the critical flow rate, bridges form stably and lead to the most severe formation damage. After reaching the critical flow rate, the bridges weaken and break, and relative permeability will be independent of the flow rate. It was deduced that permeability reduction and formation damage are directly proportional to particle concentration and inversely proportional to glass bead size.

Abstract Shale formations are essential for different disciplines, including wellbore stability studies in petroleum engineering. In shale stability studies, the prediction of transport parameters of water and ions is a significant issue (Farrokhrouz and Asef, 2013). A unique and novel method to address this subject is the Revil model (Revil et al., 2011), which, unlike previous models, considers physiochemical mechanisms in the pore space and needs a few easily measurable shale properties (Revil et al., 2004). In this paper, for the first time to our knowledge, the Revil model has been extended for salts of multivalent ions. The extended model for water and ion transport through shale has been evaluated against a range of experimental data sets in the literature. The extended Revil model only needs a few shale properties such as cation exchange capacity (CEC), porosity, and grain density, which can be readily measured in the laboratory. Further, in the present work, three parameters ( ) have been considered calibration parameters. In addition to extending the Revil model for multivalent salts, we derived a simplified equation to estimate ion selectivity (IS) and a proof for the conjecture that IS correlates with membrane efficiency (ME). Focusing on the data set of Albazali (2005), a complete matching could be obtained by adjusting calibration parameters for each test data. In the case of adjusting all experiments with only three standard calibration parameters, the prediction was not satisfactory. However, the “intact-anion method” results were more accurate than the “Donnan method”. When multiple sets of ME data in a broader concentration range, including low concentrations, were plotted along with high-concentration data, correlativity was significant (R² > 0.9). Further, a sensitivity analysis of the model parameters was performed. Our findings pave the way for the appropriate mechanistic approach to investigating and handling practical engineering challenges associated with shale.

Abstract Using nanoparticles for adsorbing asphaltene is an efficient method for upgrading actual oil samples compared to other expensive mechanical treatments or even solvents, such as n-pentane and n-heptane, and surfactants. This study uses nickel–zeolite oxide nanoparticles for asphaltene adsorption and solving asphaltene precipitation problems. Although nickel–zeolite oxide nanoparticles have been used in previous studies as an asphaltene adsorbent, observing the relationship between asphaltene adsorption on their surface and asphaltene precipitation in the presence of nanoparticles during the actual process is not covered. For addressing this relation, we performed a series of experiments included Fourier-transform infrared spectroscopy (FTIR), CO₂–oil interfacial tension tests, Langmuir and Freundlich isotherm models, and natural depletion tests in the presence of nickel–zeolite oxide nanoparticles. The Langmuir model better fitted the adsorption data than the Freundlich model, which shows that the adsorption occurs on a homogeneous surface with monolayer coverage. Based on the CO₂–oil interfacial tension results, there are two different slope forms in interfacial tension readings as pressure increases from 150 to 1650 psi. Due to asphaltene aggregation, the second slope (900–1650 psi) is slower than the first one (150–900 psi). Three pressures of 1350, 1500, and 1650 psi and nickel–zeolite oxide nanoparticles at a concentration of 30 ppm were selected for the natural depletion tests, and the basis of selection was high-efficiency adsorption at these points. As pressure decreased from 1650 to 1350 psi, asphaltene precipitation changed from 8.25 to 10.52 wt % in the base case, and it varied from 5.17 to 7.54 wt % in the presence of nickel–zeolite oxide at a concentration of 30 ppm. Accordingly, nickel–zeolite oxide nanoparticles adsorbed asphaltene on their surface correctly, and the amount of asphaltene precipitation decreased in the presence of nickel–zeolite oxide nanoparticles.

Abstract One of the critical issues in the oil industry is related to asphaltene precipitation during different stages, and using nanoparticles is known as a standard method for solving this problem. Although nickel oxide and zeolite have been addressed in previous research to solve the asphaltene precipitation problem, using NiO/Na-ZSm-5 (the primary goal of this study) has not been developed to solve relevant asphaltene precipitation problems. The crystalline structure and morphology of the synthesized nanoparticles were analyzed with the help of X-ray diffraction spectrometry (XRD), scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FTIR), and energy-dispersive X-ray spectroscopy (EDXS). The results show that the nanoparticles were well synthesized and preserved their crystalline structure with a diameter of 13.6 nm after synthesis. The EDXS analyses also proved that the sorbent adsorbed an amount of asphaltene. In the next step, asphaltene adsorption experiments were carried out at various concentrations of asphaltene and temperatures, and the effect of different variables, including the initial concentration of asphaltene, temperature, and the ratio of heptane to toluene, on the asphaltene adsorption rate was evaluated. The results indicate that with an increase in the initial asphaltene concentration from 25 to 2000 ppm, the asphaltene adsorption rate in zeolite increases. At concentrations less than 500 ppm, a rise in the temperature reduces the asphaltene adsorption, while at concentrations higher than 500 ppm, raising the temperature from 25 to 55 °C increases asphaltene adsorption capacity on zeolite. Further, more significant adsorption is observed at a heptane-to-toluene ratio of 0.4 with q = 25.17 mg/g. Evaluating the effects of kinetic adsorption molecules of asphaltene on these nanoparticles shows that the adsorption process reaches equilibrium in less than 2 h. The experimental data were adapted according to Lagrangian pseudo-first-order and pseudo-second-order models to determine the kinetic mechanism of this process. The Langmuir and Freundlich adsorption isotherms were evaluated, and the isotherms resulting from the Langmuir isotherm model were of good conformity, indicating that adsorption at the homogenous level occurred with a single-layered coating. In the final step, after evaluating the thermodynamic conditions, the spontaneity of the asphaltene adsorption process was proved.

Abstract Although experimental studies confirmed the effectiveness of nanoparticles in enhanced oil recovery applications, no comprehensive investigation has been carried out to reveal the effect of different subsurface factors on this improvement. Proper application of nanoparticles mainly depends on their ability to travel long distances within a reservoir without agglomeration, retention, and blocking the pore throats. This study strengthens our understanding of the effect of the main subsurface factors on the nanofluid-assisted enhanced oil recovery. To this end, a transport approach utilizing the kinetic Langmuir model is developed and validated using experimental data. After that, the effects of reservoir rock type and its properties (clay content and grain size), the salinity of injected fluid, and the reservoir temperature on the transport and retention of nanoparticles in porous media concerning enhanced oil recovery methods are investigated. Since the concentration of nanoparticles in the injected fluid and on the rock surface (as deposited) control the mobility and wettability alteration, the effect of subsurface factors and salinity of injected fluid on this deposition is also analyzed. The results showed that the rock type and its properties significantly affect the transport and retention of nanoparticles in porous media. Brine salinity also has the most significant impact on the amount of nanoparticles deposited on the rock surface. The surface covered by nanoparticles increased from 10% to 82% after changing salinity from 3 wt % NaCl to the API brine. 

Abstract Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (S_w) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.



 



Modelling involves the use of statistical techniques or analogy data to infill the inter-well volume producing images of the subsurface. Integration of available data sets from “KO” field were used to identify hydrocarbon prospects and by means of interpolation, populate the facies and petrophysical distribution across the field to define the reservoir properties for regions with missing logging data[KO1] . 3D seismic data, check-shot data, and a series of well logs of four wells were analyzed, and the analysis of the well logs was performed using the well data. The synthetic seismogram produced from the well ties [M.N.2] [KO3] was used to map horizon slices across the reservoir regions. Four horizons and fifteen faults, including one growth fault, four major faults, and other minor faults, all in the time domain were mapped. Attribute analyses were carried out, and a 3D static model comprised of the data from the isochore maps, faults, horizons, seismic attributes, and the various logs generated was built. A stochastic method was also employed in populating the facies and petrophysical models. Two hydrocarbon-bearing sands (reservoirs S1 and S2) with depth values ranging from –1729 to 1929 m were mapped. The petrophysical analysis gave porosity values ranging from 0.18 to 0.24 across the reservoirs, and the permeability values ranged from 2790 to 5651 mD. The water saturation (S_w) of the reservoirs had an average value of 50% in reservoir S1 and 47% in reservoir S2. The depth structure maps generated showed an anticlinal structure in the center of the surfaces, and the mapped faults with the four wells were located in the anticlinal structure. The reserve estimate for the stock tank oil initially in place (STOIIP) of the reservoirs was about 70 mmbbl, and the gas initially in place (GIIP) of the reservoirs ranged from 26714 to 63294 mmcf. The result of the petrophysical analysis revealed the presence of hydrocarbon at favorable quantities in the wells, while the model showed the distribution of these petrophysical parameters across the reservoirs.



 [KO1]Sentence has been rephrased.




 [M.N.2]This verb does not make sense in this context and has made the sentence unclear.




 [KO3]Sentence has been rephrased



 

Abstract < p>The determination of rock types for petrophysical studies has a wide range of applications. It is widely used in drilling, production, and especially in the study and characterization of reservoirs. Zoning of flow units and permeability estimation is one of the challenging tasks of reservoir studies, which uses the integration of data from well logs and analysis of the core. In this study, a Bayesian theory-based statistical modeling method is proposed to identify hydraulic flow units in coreless wells using the concept of hydraulic flow unit and then permeability estimation. In the flow zone indicator (FZI) method, the formation is divided into five hydraulic flow units. In the Winland R35 ethod, however, it is divided into four hydraulic flow units. The Bayesian statistical model divides the existing complex carbonate reservoir rock data into three hydraulic flow units with the most probability of similarity. The second and third hydraulic flow units have closer properties compared to the first hydraulic unit. The Bayesian method-based permeability estimation modeling has acceptable precision, and validation of its results with core data indicates a precision factor of 0.96.
The findings of this study can help in better understanding of the concept of flow units and more effective estimation of the permeability of the rocks of the heterogeneous carbonate reservoir.

Abstract Ultrasonic irradiation is a new, economic, and environmentally friendly technique for treating asphaltene aggregation in petroleum industry. In this study, the effect of ultrasonic radiation on asphaltene formation is investigated using conventional optical microscopy, viscosity measurement, and Fourier-transform infrared spectroscopy (FTIR). To this end, five crude oil samples, collected from different reservoirs, are used, and the effect of ultrasonic radiation on the structure of the crude oils is investigated at various exposure times. The results show that, at an optimum radiation time, the ultrasonic waves can break the asphaltene clusters and shift the size distribution of the asphaltene aggregate to a smaller size. In addition, the FTIR analysis reveals structural changes in the composition of the crude oil after the ultrasonic irradiation. By increasing the ultrasound exposure time, the viscosity of the asphaltenic oil first decreases to a minimum before rising again. Moreover, the measurement of asphaltene and resin content of the crude oils indicates that at exposure times longer than the one leading to the minimum viscosity, resin molecules are broken upon exposure to ultrasound. This can be the main reason for the existence of an optimum time in the application of ultrasonic radiation, after which the percentage of asphaltene particles and the viscosity of the crude oils increase.

Abstract Enhanced oil recovery (EOR) is a vital part of the process of oil production from sandstone and carbonate reservoirs. Maintaining and increasing oil production from many fields require proper selection, design, and implementation of EOR methods. The selection of EOR methods for specific reservoir conditions is one of the most difficult tasks for oil and gas companies. Screening of different EOR techniques considering previous experiences from the methods applied in other fields is a first step in the recommendation of any costly EOR operations. In this paper, EORgui software was utilized to screen eight enhanced oil recovery methods in one of Iran’s offshore sandstone oil fields. The reservoir is composed of two sections with different fluid properties, namely API, viscosity, and oil composition, but relatively homogeneous rock properties and high permeability (1500 mD). The results show that polymer flooding is technically the most suitable enhanced oil recovery method in the upper zone of the reservoir with a high percentage matching score of 90%, and immiscible gas injection with a matching score of 83% is ranked second. For the lower part of the reservoir containing a fluid with much higher viscosity, immiscible gas injection (83% matching) can be recommended. Furthermore, polymer flooding predictive module (PFPM) was utilized to investigate the impact of polymer concentration on oil recovery performance of the upper part with an ultimate recovery of about 40% at the optimum concentration.