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The structural complexities of hydrocarbon reservoirs make it difficult to correlate geological and petrophysical properties. A successful field development depends on accurately mapping the spatial distributions of reservoir key parameters. In this study, we present results on rock type analysis, estimation, and uncertainty evaluation of geological and petrophysical data of 33 wells in one of the south Iranian gas fields. This paper is divided into two parts. In the first part, we used a reservoir rock classification theme based on identifying electrofacies (EFs) and hydraulic flow units by analyzing both log and core data. In the second part of the paper, we performed estimation, uncertainty evaluation, and assessment of the porosity–thickness relationship of the high-quality EFs using geostatistical techniques. We used sequential simulation schemes to map the spatial distributions of porosity and thickness of the high-quality EFs across the field. Using probabilistic approaches, the generated multiple realizations were used to quantify the local and spatial uncertainties. Variogram analysis showed that property distributions had a higher continuity and minimum variance in the NW–SE direction. Based on spatial uncertainty analysis, we found that the indicator-based sequential simulated maps exhibited less spatial uncertainty. Furthermore, the obtained probability maps indicated that the SE part of the study area is more suitable for drilling and production scenarios. [ABSTRACT FROM AUTHOR]

This study presents a novel approach for optimizing well paths in extended reach drilling (ERD) wells. Different trajectories can be used for ERD wells, each with its pros and cons. Previous research overlooked certain objective functions in single-objective optimization and lacked an autonomous method for selecting the best solution from Pareto optimal solutions in multi-objective optimizations. Furthermore, they lacked comparing different profiles in well design. Risk assessment and operational factors, which greatly influence optimization and drilling success, were insufficiently considered. This study utilized the multi-objective genetic algorithm (MOGA) and the technique for order preference by similarity to an ideal solution (TOPSIS) method to select the optimal well path based on torque, wellbore length, risk (e.g., keyseat), and required tools. First, all possible trajectories were determined, and MOGA identified the optimal path with minimal torque and length. The fuzzy decision-making method automatically selected the best solution from the Pareto optimal solution set. The associated risks and required tools are evaluated for each trajectory. Finally, the TOPSIS method selected the optimal trajectory based on torque, length, risks, and required tools. The case study demonstrated that the undersection path was the most advantageous trajectory for ERD wells, with a 60% closeness to the ideal state. The multiple build trajectory achieved 57% closeness, while the build and hold and double build paths had lower closeness values (43 and 28%, respectively). Consequently, it can be inferred that in the context of ERD wells, it is preferable to carry out the deviation process at deeper depths. [ABSTRACT FROM AUTHOR]

Accurately determining rock elastic modulus (EM) and uniaxial compressive strength (UCS) using laboratory methods requires considerable time and cost. Hence, the development of models for estimating the mechanical properties of rock is a very attractive alternative. The current research was conducted to predict the UCS and EM of sandstone rocks using quartz%, feldspar%, fragments%, compressional wave velocity (PW), the Schmidt hardness number (SN), porosity, density, and water absorption via simple regression, multivariate regression (MVR), K-nearest neighbor (KNN), support vector regression (SVR) with a radial basis function, the adaptive neuro-fuzzy inference system (ANFIS) using the Gaussian membership (GM) function, and the back-propagation neural network (BPNN) based on various training algorithms. The samples were categorized as litharenite and feldspathic litharenite. By increasing the feldspar% and quartz% and decreasing the fragments%, the static properties increased. The results of the statistical analysis showed that the SN and porosity have the greatest effect on the UCS and EM, respectively. Among the Levenberg–Marquardt (LM), Bayesian regularization, and Scaled Conjugate Gradient training algorithms using the BPNN method, the LM achieved the best results in forecasting the UCS and EM. The ideal obtained BPNN, using a trial-and-error process, contains four neurons in a hidden layer with eight inputs. All five models attained acceptable accuracy (correlation coefficient greater than 70%) for estimating the static properties. By comparing the methods, the ANFIS showed higher precision than the other methods. The UCS and EM of the samples can be determined with very high accuracy (R2 > 99%). [ABSTRACT FROM AUTHOR]

• The joint effects of ultrasound and solvation on oil viscosity were investigated. • The analysis of asphaltene structure by using FTIR and microscopy techniques. • The lowest viscosity was found for irradiation-then-dilution-treated crude oil. • Ultrasonic solvation reduced the ratio of aromatic rings to aliphatic chains. Production from heavy oil reservoirs faces challenges, such as accumulating heavy hydrocarbon materials like asphaltenes near the wellbore, resulting in low recovery rates. To enhance recovery and prevent formation damage, methods often focus on reducing oil viscosity. Solvents and ultrasonic waves have proven effective in this regard, though challenges related to asphaltene aggregation and structural changes persist. This study explores the impact of simultaneously applying ultrasonic radiation and solvents on crude oil's viscosity and asphaltene structure. Toluene and n-heptane, representing aromatic and paraffinic solvents, were employed. Viscosity measurements and Fourier transform infrared spectroscopy tests were conducted on sonicated crude oil diluted with solvents and solvent-diluted crude oil subjected to sonication. Results were compared to untreated and separately treated crude oil samples. The study found that the most effective viscosity reduction method involved blending sonicated oil with toluene under optimal radiation time and concentration conditions. Two primary mechanisms for viscosity reduction were identified. Firstly, there was the dissolution and aggregation of asphaltene clusters. Secondly, chemical changes in asphaltene molecular structure were observed, altering the ratio of aromatic rings to aliphatic chains. This research offers potential insights into how ultrasonication and solvation interact to modify crude oil structure. [Display omitted] [ABSTRACT FROM AUTHOR]

Percolation of reactive fluids in carbonate rocks affects the rock microstructure and hence changes the rock macroscopic properties. In Part 1 paper, we examined the voxel-wise evolution of microstructure of the rock in terms of mineral dissolution/detachment, mineral deposition, and unchanged regions. In the present work, we investigate the relationships between changes in two characteristic transport properties, i.e. permeability and electrical conductivity and two critical parameters of the pore phase, i.e. the fraction of the pore space connecting the inlet and outlet faces of the core sample and the critical pore-throat diameter. We calculate the aforementioned properties on the images of the sample, wherein a homogeneous modification of pore structure occurred in order to ensure the representativeness of the calculated transport properties at the core scale. From images, the evolution of pore connectivity and the potential role of micropores on the connectivity are quantified. It is found that the changing permeability and electrical conductivity distributions along the core length are generally in good agreement with the longitudinal evolution of macro-connected macroporosity and the critical pore-throat diameter. We incorporate microporosity into critical length and permeability calculations and show how microporosity locally plays a role in permeability. It is shown that the Katz-Thompson model reasonably predicts the post-alteration permeability in terms of pre-alteration simulated parameters. This suggests that the evolution of permeability and electrical conductivity of the studied complex carbonate core are controlled by the changes in the macro-connected macroporosity as well as the smallest pore-throats between the connected macropores. [ABSTRACT FROM AUTHOR]

• Heavy oil_solvent mixtures can be assumed as a binary mixture in EOR processes. • New correlations were proposed for oil_solvent binary interaction coefficients. • Using correlations, we eliminate the need for time-consuming optimizations. • P_x phase diagrams can be estimated properly by using binary mixture assumption. Conventional production methods in heavy oil reservoirs are not efficient primarily due to the high viscosity of the oil. Several methods such as VAPEX and ES-SAGD have been developed to overcome production challenges from these reservoirs, which mainly rely on oil viscosity reduction. Solvent injection dilutes the oil and produces a complex asymmetric mixture. It is difficult to study the phase behavior of oil due to the diversity of its components, and it gets more complicated with the addition of solvent. One of the assumptions to simplify the problem is considering heavy oil as a single pseudo component and investigating the thermophysical properties of binary mixtures with diluents. This study collected and evaluated more than 1000 experimental data on various types of heavy oil/bitumen and several hydrocarbon and non-hydrocarbon solvents. The data were divided into two groups, below and above the critical temperature of the solvent, according to experimental temperatures. Modeling of mixture phase behavior as a binary mixture was performed using the advanced Peng-Robinson equation of state (APR-EoS). EoS tuning to match the experimental data was performed by optimizing the binary interaction coefficients (k ij). The results showed that the binary mixture assumption could be used as a practical approach to construct pressure-composition phase diagrams. Optimized values of k ij were proposed as two empirical correlations according to the dimensionless ratio T co / T cs (oil critical temperature to solvent critical temperature). The model constructed using these correlations showed an average deviation of about 16% compared to experimental data. It is necessary to note that the vapor-liquid-liquid three-phase regions may occur in a heavy oil/bitumen and solvent mixture. But according to the Gibbs phase rule, with two components and three phases in the system, the degree of freedom equals one. So, investigating the effects of pressure change on three-phase regions is not possible using this model. [ABSTRACT FROM AUTHOR]

The application of X-ray micro-computed tomography (μ-CT) for quantitatively characterizing reactive-flow induced pore structure evolution including local particle detachment, displacement and deposition in carbonate rocks is investigated. In the studies conducted in this field of research, the experimental procedure has involved alternating steps of imaging and ex-situ core sample alteration. Practically, it is impossible to return the sample, with micron precision, to the same position and orientation. Furthermore, successive images of a sample in pre- and post-alteration states are usually taken at different conditions such as different scales, resolutions and signal-to-noise ratios. These conditions accompanying with subresolution features in the images make voxel-by-voxel comparisons of successive images problematic. In this paper, we first address the respective challenges in voxel-wise interpretation of successive images of carbonate rocks subject to reactive flow. Reactive coreflood in two carbonate cores with different rock types are considered. For the first rock, we used the experimental and imaging results published by Qajar et al. (2013) which showed a quasi-uniform dissolution regime. A similar reactive core flood was conducted in the second rock which resulted in wormhole-like dissolution regime. We particularly examine the major image processing operations such as transformation of images to the same grey-scale, noise filtering and segmentation thresholding and propose quantitative methods to evaluate the effectiveness of these operations in voxel-wise analysis of successive images of a sample. In the second part, we generalize the methodology based on the three-phase segmentation of normalized images, microporosity assignment and 2D histogram of image intensities to estimate grey-scale changes of individual image voxels for a general case where the greyscale images are segmented into arbitrary number of phases. The results show that local (voxel-based) porosity changes can be decomposed into local mineral dissolution and deposition. Moreover, it is found that the microporosity evolutions are differently distributed in the samples after the reactive coreflood experiments. In the last part of the paper, for the case of quasi-uniform dissolution, we combine the tomographic images with numerical calculations of permeability along the core to characterize the relationship between changes in permeability and the fractions of the mineral dissolved and deposited. A consistency is found between the calculated longitudinal permeability changes and the quantified distribution of mineral dissolved and deposited along the sample. [ABSTRACT FROM AUTHOR]

• Effects of chemical dissolution on pore space was explored by μ-CT and MIP methods. • The evolution of pore size was examined by experimental and simulated MIP curves. • Impact of micropores on pore surface area was quantified by combining μ-CT and MIP. • Permeability changes were controlled by macroporosity and critical pore diameter. In this paper, we report on experimental and computational studies investigating the evolution of pore structure and permeability of a microporous carbonate rock during chemical dissolution using information provided from X-ray micro-computed tomography (µ-CT) and mercury intrusion porosimetry (MIP) techniques. We consider a chemical dissolution in a core sample by a nonacidic solution wherein a quasi-uniform modification of pore structure occurred. First, we conduct a comparative analysis on the capabilities and limitations of the µ-CT and MIP methods to quantify the evolution of pore size and pore surface area. In particular, we incorporate micropores into the calculations of the pore size-related parameters to highlight the uncertainties that ignoring microporosity causes. In the second part of the paper, we present predictive results on the fractional changes in the permeability of the rock using the Katz-Thompson (KT) and Kozeny-Carman (KC) models. The predictions are based on two characteristic parameters of the pore phase, i.e., the critical pore diameter and the specific pore surface area, and two characteristic macro-scale properties, i.e., porosity and formation factor, all calculated from both the MIP and µ-CT methods. The predicted changes in permeability are compared with those calculated directly on the images using the lattice-Boltzmann (LB) flow simulation on segmented images. The effect of changes in microporosity is also assessed to investigate its role in permeability evolution. The results showed that the KT model could reasonably predict the fractional changes in permeability in terms of the pore structure and macroscale parameters calculated from the MIP and µ-CT methods. [ABSTRACT FROM AUTHOR]

Production from heavy asphaltenic oil reservoirs poses several challenges that require new and innovative techniques for improved production and recovery. The main objective of this study is to experimentally investigate the influences of ultrasonic waves and solvent on oil viscosity, asphaltene precipitation behavior, and recovery of a heavy asphaltenic crude oil. This study is divided into two main parts. In the first part, crude oil samples were subjected to ultrasonic radiation with a frequency of 20 kHz and varying output powers (30, 60, and 100 W) for various durations. The viscosity of each oil sample was measured immediately after stopping ultrasonic radiation and also after 24 h of irradiation. An optimum time for ultrasound radiation was determined when the cooled-down radiated oil reached a minimum viscosity. We then measured the viscosity of the ultrasonically treated oil samples blended with a solvent (i.e., n-heptane) to assess the synergetic effect of ultrasonic radiation and solvation on the oil viscosity. In the second part, the application of ultrasonic radiation on the asphaltene aggregates and oil recovery was examined using solvent flooding in a transparent porous medium. Four sets of experiments were undertaken where the solvent was injected into the micromodel saturated with the untreated and ultrasonically treated oil free from or blended with the solvent. The results showed that ultrasonic treatment decreased the size of asphaltene aggregates and consequently reduced the viscosity of the crude oil. As a result, the suspension of asphaltene in the ultrasonically treated oil increased and reduced its tendency to precipitate at the optimum radiation time. Furthermore, the results indicated that the combined use of ultrasound and solvent had the greatest reduction in the oil viscosity compared to the untreated crude oil with ultrasonic waves or solvent. • The joint effect of ultrasonic radiation and solvent on viscosity and asphaltene aggregation of crude oil was investigated. • A synergy in viscosity reduction was found when the solvated crude oil was subjected to ultrasonic radiation. • The flooding tests showed that ultrasonic radiation locally decreased the size and precipitation of asphaltene aggregates. • The ultrasonicated oil was displaced more efficiently on the local pore space. • Considerably lower asphaltene precipitation was found when the radiated oil was displaced by the solvent. [ABSTRACT FROM AUTHOR]

• Simultaneous Effects of ultrasonic irradiation and α-Fe 2 O 3 nanoparticles (NPs) on crude oil properties were investigated. • The viscosity of irradiated oil with NPs was found to be less than that of irradiated oil without NPs. • The post-pyrolysis mass loss of the irradiated NP-added oil was greater than that of non-irradiated oil with/without NPs. • Regarding the thermogravimetric tests, the addition of NPs and the ultrasonic irradiation work in the opposite direction. In this work, the effects of ultrasonic irradiation assisted by α-Fe 2 O 3 nanoparticles (NPs) on the evolution of viscosity and thermal properties of crude oil are evaluated. A viscous crude oil with a high amount of asphaltene (∼20% by mass) was used for ultrasonication over different exposure times and nanoparticle concentrations. The viscosity of the oil before and after ultrasonic irradiation was measured with and without nanoparticles. Experimental results indicated that the viscosity of irradiated oil containing nanoparticles at optimum conditions was lower than the viscosity of nanoparticle-free irradiated oil. The thermal behavior of the irradiated crude oil mixed with nanoparticles at optimum conditions was examined using the TGA/DTA methods. The results showed a non-complementary effect of ultrasonic irradiation and nanoparticles on the weight loss and the amount of residual oil at both the end of the pyrolysis and oxidation stages, representing that addition of the α-Fe 2 O 3 NPs to the crude oil and the ultrasonication of the crude oil work in the opposite direction. Based on the TG/DTA data, the kinetic parameters of the pyrolysis and oxidation reactions were estimated. It was found that the simultaneous use of ultrasonic irradiation and nanoparticles sharply decreased the activation energy of the oxidation reactions, but had almost no effect on the activation energy of the pyrolysis reactions. The results of this paper provide an insight into the effectiveness of in-situ combustion enhanced oil recovery, which depends on viscosity reduction and the rate at which heat is generated. [ABSTRACT FROM AUTHOR]

The selective catalytic reduction (SCR) of nitric oxide with excess ammonia in the presence of oxygen on silica-supported vanadium oxide catalyst was studied in a packed-bed reactor, and a mathematical model was proposed for the processes occurring in the reactor. Experimental data were presented for evaluation of the accuracy of the proposed model. Good agreement was observed between the measured and calculated values of the conversion in the outlet of the reactor. Once the validity of the proposed model was verified, it was used to examine the effects of different parameters such as feed temperature, inlet feed composition, and gas hourly space velocity (GHSV) on the conversion of NO over V2O5/SiO2 catalyst for practical application. The results for the employed catalyst showed that high NO conversion occurred at temperatures of 280°-300°C, GHSV less than 2000 h-1 (STP), and O2 concentration greater than 10% v/v. These results clearly demonstrate the high potential for this catalyst to be applied commercially for the control of NOx emissions from flue gases of different sources. [ABSTRACT FROM AUTHOR]

This study aims to present a simple method to calculate the permeability of porous materials using μ-CT images and an approximation based on the solution of Laplace's equation for pressure. For this purpose, an in-house computer program was developed based on finite difference method to determine the distribution of pressure in voxelated pore space. Afterwards, approximate permeability was obtained using Euclidean distance map of the pore space and a simple upscaling scheme for a range of porous media including idealized channels of elementary cross sections, Boolean models of spherical grains, bundles of capillary tubes and digital rocks obtained from μ-CT imaging. Next, a comparison was made between the Laplace permeability approximation and the analytical solutions of idealized microstructure and digitally-computed permeability of a number of rock samples using the Stokes solver and the lattice-Boltzmann method. It has been revealed that the estimated permeability values are in good agreement over the investigated range of porosity. The developed Laplace permeability solver was also well matched with the results of experimental measurement on a real rock sample. As an illustration of the applicability of the proposed method, the anisotropy of permeability at pore scale and the cross-correlation between permeability and connected macro-porosity was analyzed for the experimentally investigated rock sample. In conclusion, the results of this paper suggest that the proposed permeability solver is suitable for rough estimation of permeability and hence rough evaluation of heterogeneity/anisotropy from μ-CT images of rocks, particularly for large datasets with high number of pore voxels. • A simple method for estimating permeability of rocks using 3D µ-CT images. • The method is based on a finite-difference solution of Laplace's equation for pressure. • An upscaling scheme is used to estimate permeability using the pressure and Euclidean distance maps of the fluid phase. • Highlights The method is compared with analytical solutions of idealized media and Stokes and LBM calculations of digital rocks. [ABSTRACT FROM AUTHOR]

Miscible gas injection in tight/shale oil reservoirs presents a complex problem due to various factors, including the presence of a large number of nanopores in the rock structure and asphaltene and heavy components in crude oil. This method performs best when the gas injection pressure exceeds the minimum miscibility pressure (MMP). Accordingly, accurate calculation of the MMP is of special importance. A critical issue that needs to be considered is that the phase behavior of the fluid in confined nanopores is substantially different from that of conventional reservoirs. The confinement effect may significantly affect fluid properties, flow, and transport phenomena characteristics in pore space, e.g., considerably changing the critical properties and enhancing fluid adsorption on the pore wall. In this study, we have investigated the MMP between an asphaltenic crude oil and enriched natural gas using Peng-Robinson (PR) and cubic-plus-association (CPA) equations of state (EoSs) by considering the effect of confinement, adsorption, the shift of critical properties, and the presence of asphaltene. According to the best of our knowledge, this is the first time a model has been developed considering all these factors for use in porous media. We used the vanishing interfacial tension (VIT) method and slim tube test data to calculate the MMP and examined the effects of pore radius, type/composition of injected gas, and asphaltene type on the computed MMP. The results showed that the MMP increased with an increasing radius of up to 100 nm and then remained almost constant. This is while the gas enrichment reduced the MMP. Asphaltene presence changed the trend of IFT reduction and delayed the miscibility achievement so that it was about 61% different from the model without the asphaltene precipitation effect. However, the type of asphaltene had little impact on the MMP, and the controlling factor was the amount of asphaltene in the oil. Moreover, although cubic EoSs are particularly popular for their simplicity and accuracy in predicting the behavior of hydrocarbon fluids, the CPA EoS is more accurate for asphaltenic oils, especially when the operating pressure is within the asphaltene precipitation range. [ABSTRACT FROM AUTHOR]

Highlights In this study, the influence of ultrasonic waves on the viscosity and thermal behaviour of a crude oil with high asphaltene content at different irradiation times and powers/frequencies was investigated. It was found that the ultrasonic radiation significantly reduced the oil viscosity before the oil cooled down. The viscosity was then remeasured after the irradiated oil cooled down to the ambient temperature to evaluate the reversibility in viscosity at various time intervals. For each ultrasonic frequency, an optimum irradiation time was found at which the cooled-down irradiated oil reached a minimum viscosity. For the ultrasonic radiation with a frequency of 46 kHz and an output power of 50 W, it was found that the permanent viscosity loss of the cooled-down oil irradiated for an optimum time of 8 min was 10 %. The effects of ultrasonic irradiation on thermal behaviour of the oil were analysed using thermogravimetric and differential thermal (TGA/DTA) methods to evaluate the relation between changes in viscosity and thermal properties of the oil. It was found that the weight loss of the irradiated-oil was more than that of the non-irradiated oil at the end of both the pyrolysis and oxidation stages. [ABSTRACT FROM AUTHOR]

The elastic modulus is one of the important parameters for analyzing the stability of engineering projects, especially dam sites. In the current study, the effect of physical properties, quartz, fragment, and feldspar percentages, and dynamic Young’s modulus (DYM) on the static Young’s modulus (SYM) of the various types of sandstones was assessed. These investigations were conducted through simple and multivariate regression, support vector regression, adaptive neuro-fuzzy inference system, and backpropagation multilayer perceptron. The XRD and thin section results showed that the studied samples were classified as arenite, litharenite, and feldspathic litharenite. The low resistance of the arenite type is mainly due to the presence of sulfate cement, clay minerals, high porosity, and carbonate fragments in this type. Examining the fracture patterns of these sandstones in different resistance ranges showed that at low values of resistance, the fracture pattern is mainly of simple shear type, which changes to multiple extension types with increasing compressive strength. Among the influencing factors, the percentage of quartz has the greatest effect on SYM. A comparison of the methods' performance based on CPM and error values in estimating SYM revealed that SVR (R2 = 0.98, RMSE = 0.11GPa, CPM =  + 1.84) outperformed other methods in terms of accuracy. The average difference between predicted SYM using intelligent methods and measured SYM value was less than 0.05% which indicates the efficiency of the used methods in estimating SYM. [ABSTRACT FROM AUTHOR]

Digital rock physics is at the forefront of characterizing porous media, leveraging advanced tomographic imaging and numerical simulations to extract key rock properties like permeability. However, fully capturing the heterogeneity of natural rocks necessitates imaging increasingly larger sample volumes, presenting a significant challenge. Direct numerical simulations at these scales become either prohibitively expensive or computationally unfeasible due to limitations in resolution and field of view (FOV). This issue is particularly pronounced in carbonate rocks, known for their complex, multiscale pore structures, which exacerbate the resolution-FOV tradeoff. To address this, we introduce a machine learning strategy that merges multiscale imaging data from various resolutions with a 3D convolutional neural network (CNN) model. This approach is innovative in its ability to identify cross-scale correlations, thereby enabling the estimation of transport properties in larger volumes—properties that are difficult to simulate directly—using trainable proxies. The integration of multiscale imaging with deep learning allows for accurate permeability predictions at scales beyond those feasible with traditional direct simulation methods. By employing transfer learning across different scales during the training phase, our multiscale machine learning model achieves robust performance, with an R² exceeding 0.96 when evaluated on diverse lower-resolution domains with larger FOVs. Notably, this method significantly enhances computational efficiency, reducing the computational time by orders of magnitude. Originally developed for the intricate pore structures of carbonate rocks, our approach shows promise for application to a wide range of multiscale porous media, offering a viable solution to the longstanding tradeoff between imaging resolution and FOV in digital rock physics. [ABSTRACT FROM AUTHOR]

In this work, the effects of four different chemical inhibitors, namely a polymeric surfactant, synthesized γ-Al2O3/NiO nanoparticles, epoxy resin, and canola oil to inhibit asphaltene precipitation in three different crude oils collected from various oil fields located in southern Iran. A high-pressure solid detection apparatus was employed to measure the onset point of asphaltene precipitation in crude oils with API ranging between 35 and 38 and various characteristics in the presence of the inhibitors in a wide range of concentrations ranging 0–20 wt. % at a high pressure of 2,000 psi and ambient temperature. The elemental composition of resin and asphaltene fractions in the crude oils was identified using a LEC elemental analyzer. The results showed that all fractions of precipitated asphaltenes were composed of low ratios of H (hydrogen)/C (carbon), which were an indication of large instability. Moreover, the screening experiments showed that the polymeric surfactant inhibitor with a base-nature was more efficacious with most oil samples due to the presence of high content (73%) of resin in this type of inhibitor. Besides, they can be used as a well-candidate for other oils not assessed in this work due to their high polarity and also compatibility with the structure of studied asphaltenes. It was found that the polymeric surfactant γ-Al2O3/NiO nanoparticles had the highest inhibition performance in comparison with the epoxy resin and canola oil. [ABSTRACT FROM AUTHOR]