Effect of Temperature on Asphaltene Precipitation in Crude Oils from Xinjiang Oilfield
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ABSTRACT:
SUBMITTER: Li M
PROVIDER: S-EPMC9583088 | biostudies-literature | 2022 Oct
REPOSITORIES: biostudies-literature
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Project description:Due to the technical, environmental and economic problems caused by asphaltene precipitation, such as oil production reduction, well shut-ins and the necessity of EOR usage, the prediction of asphaltene precipitation seems to be vital. Considering the larger size of asphaltene molecules compared to the other hydrocarbon, it is reasonable to predict the precipitation using the Flory-Huggins theory. In this study, Flory-Huggins solution theory has been modified regarding the solvent molar volume. The modified model was used to predict the asphaltene precipitation of four oil samples in the absence and presence of the inhibitors. Then, the modeling data given by the Flory-Huggins theory was validated with the experimental data obtained by ASTM D-6560 standard method. The mean error at this modeling was 2-13%, which seems acceptable. The proposed model for the cases where an inhibitor is not involved has higher accuracy. The modified Flory-Huggins theory confirmed that the addition of inhibitors at all concentrations postpones the onset point. The average error of the modified model was found to be 4.5-9.8%, which is in a good range. Also, the model accuracy is less for situations where the asphaltene content of the crude oil is higher. Based on this study, the modification of Flory-Huggins theory, regarding the solvent molar volume leads to a lower error.
| S-EPMC9643540 | biostudies-literature
Project description:In oil fields, the formation of water-in-waxy crude oil emulsion is inevitable. The dissolved/crystallized state wax can interact with asphaltenes and then greatly affect the emulsion stability. However, studies on this aspect are still insufficient. In this work, the effects of the test temperature (30 °C well above the wax appearance temperature (WAT) and 15 °C well below the WAT) and asphaltene concentration (0∼1.5 wt %) on the stability of the water-in-model waxy crude oil emulsions containing 10 wt % wax were systematically investigated. When the model crude oils contain no wax, the flowability of the oils is good and the asphaltene concentration has little influence on the oil rheology. Increasing the asphaltene concentration facilitates the adsorption of asphaltenes to the oil-water interface, thus reducing the interfacial tension and water droplet size while enhancing the interfacial dilatational modulus. The stability of the emulsions improves with the increase in the asphaltene concentration, but the emulsions are still unstable. When the model crude oils contain 10 wt % wax, the WAT slightly decreases from the initial 25 to 24 °C after the addition of asphaltenes. The oil rheology is greatly improved by the addition of 0.05 wt % asphaltenes. With the further increase of the asphaltene concentration, the improved rheological ability of the asphaltenes deteriorates rapidly. At the asphaltene concentration of 1.5 wt %, the oil rheology is dramatically aggravated. The stability of the emulsion containing 10 wt % wax is mainly controlled by two aspects: on the one hand, the dissolved-state wax (30 °C) could facilitate the adsorption of asphaltenes to the interface, further reduce the interfacial tension and the water droplet size, and enhance the interfacial dilatational modulus; on the other hand, the wax crystals precipitated in the oil phase (15 °C) can form a stronger network structure at relatively high asphaltene concentrations (0.5∼1.5 wt %) and then immobilize the water droplets. The above two aspects greatly improve the sedimentation and coalescence stabilities of the emulsions at 15 °C. In addition, we did not find persuasive evidence showing that the wax could crystallize around the water droplets and strengthen the oil-water interfacial films.
| S-EPMC8908777 | biostudies-literature
Project description:The main goal of this study is to monitor the stability of crude oils in terms of both precipitation and deposition magnitude with respect to time. To achieve this goal, two experimental techniques which include a deposit level test and a spot test were integrated and applied simultaneously. The method was implemented using six crude oils, namely A, B, D, E, F, and G, and tests were performed at different times which split them into short duration tests and long duration tests. All crude oils were found to exhibit potential for asphaltene precipitation and subsequent deposition at different rates. Crude oils B, G, and D were observed to have started asphaltene precipitation and subsequent deposition relatively quicker. Similarly, crude oils B, A, and F exhibit a higher potential for producing asphaltene deposits in terms of deposition level. Crude oil E produces relatively fewer deposits at comparatively slower rates. The overall result indicates that crude oil B was found to be the most risky crude oil as it produces a higher quantity of deposits at higher rates, while crude oil E proved to be the least risky. Sensitivity analysis was also performed via the computing relevancy factor to determine the relative importance of two input parameters, namely the specific gravity of crude oil and the time for two-output precipitation intensity and deposition level. Precipitation intensities were found by the implementation of an image-processing tool on spot test results. The relationship between time and precipitation intensity was found to be negligible; however, the correlation between time and deposition level was found to be strongly positive with a relevancy factor value of approximately 0.521. Similarly, the relationship of the specific gravity of oil with precipitation intensity and deposition level was found to be moderately negative and very close to each other, i.e., -0.228 and -0.247, respectively. The integration of the deposit level test with the spot test allows the continuous and simultaneously reliable monitoring of both asphaltene precipitation and deposition at different times without involving cost, complex instrumentation, or interpretation, irrespective of the type of oil. The method enables the successful determination of stability ranking of different crude oils both in terms of precipitation and deposition.
| S-EPMC9089351 | biostudies-literature
Project description:high-temperature oilfield Raw sequence reads
| PRJNA749166 | ENA
Project description:Precipitation and deposition of asphaltene are considered as catastrophic issues facing the petroleum industry. Asphaltene deposition mainly occurs at variety places such as formation pore spaces, pumps, pipelines, wellbore, wellhead, tubing, surface facilities and safety valves causing operational problems, production deficiencies and enormous economic losses. This work aims to study the effect of series of synthesized aryl ionic liquids (ILs) containing different alkyl chains, named as R8-IL, R10-IL, R12-IL, and R14-IL, on the onset precipitation point of asphaltene in crude oil. R8-IL, R10-IL, R12-IL, and R14-IL were synthesized with high yields (the yield varied between 82 and 88%) and characterized via different tools of analysis (FTIR, 1H NMR, and Elemental Analysis). Their Thermal Gravimetric Analysis (TGA) was investigated and showed a reasonable degree of stability. It was found that R8-IL (short alkyl chain) has the highest stability, while R14-IL (long alkyl chain) is the lowest one. Quantum chemical calculations were conducted to study the reactivity and geometry of their electronic structures. Moreover, surface and interfacial tension of them were studied. It was found that the efficiency of the surface active parameters increased by increasing the length of the alkyl chain. The ILs were evaluated to delay the onset precipitation point of asphaltene using to different methods; the kinematic viscosity and the refractive index. Results from the two methods showed delaying of onset precipitation after the addition of the prepared ILs. The asphaltene aggregates was dispersed due to the π-π* interactions and hydrogen bonds formation with the ILs.
| S-EPMC10008557 | biostudies-literature
Project description:Indigenous microbial enhanced oil recovery (IMEOR) is a promising alternative way to promote oil recovery. It activates oil recovery microorganisms in the reservoir by adding nutrients to the injected water, utilizing microbial growth and metabolism to enhance recovery. However, few studies have focused on the impact of injected nutrients on reservoir microbial community composition and potential functions. This limits the further strategic development of IMEOR. In this study, we investigated the effects of nutrition on the composition of the reservoir bacterial community and functions in the Qizhong block of Xinjiang Oilfield, China, by constructing a long core microbial flooding simulation device. The results showed that the microbial community structure of the reservoir changed from aerobic state to anaerobic state after nutrient injection. Reducing the nutrient concentration increased the diversity and network stability of the reservoir bacterial community. At the same time, the nitrogen metabolism function also showed the same change response. Overall, these results indicated that nutrition significantly affected the community structure and function of reservoir microorganisms. Injecting low concentrations of nutrients may be more beneficial to improve oil recovery. This study is of great significance for guiding IMEOR technology and saving costs at the field site.
| S-EPMC11322141 | biostudies-literature
Project description:This study aims to evaluate the behavior of Cardanol/SiO2 nanocomposites in the inhibition of the asphaltene damage based on the coreflooding test at reservoir conditions. The nanocomposite design was performed in Part I (https://doi.org/10.1021/acs.energyfuels.0c01114), leading to SiO2 nanoparticles functionalized with different mass fractions of cardanol on the surface of 5 (5CSN), 7 (7CSN), and 9% (9CSN). In this part of the study, the nanocomposite/reservoir fluid interactions were evaluated through interfacial tension measurements and nanocomposite/rock surface interactions using water imbibition and contact angle measurements. Results showed that the designed nanocomposite leads to a reduction of interfacial tension of 82.6, 61.7, and 51.4% for 5CSN, 7CSN, and 9CSN regarding silica support (SN). Whereas, the reduction of the Si-OH functional groups from SiO2 nanoparticles due to the increase of the cardanol content affects the effectiveness of the wettability alteration for 7CSN and 9CSN. Nevertheless, when 5CSN is evaluated, the system is altered from an oil-wet to a mixed-wet state. Coreflooding tests at reservoir conditions were performed to evaluate the oil recovery after asphaltene damage, after damage removal and nanofluid injection, and after induction of a second asphaltene damage to check inhibition. Results show that the selected nanocomposites at a dosage of 300 mg·L-1 enhance the oil recovery in comparison with the baseline conditions via the reduction of the interfacial/surface forces at the pore scale and wettability alteration. It is worth to remark that this improvement remains after the second asphaltene damage induction, which proves the high inhibitory capacity of the designed nanocomposite for the asphaltene precipitation/deposition. Also, the use of the nanocomposites favors the oil recovery more than 50% compared to the asphaltene damage scenario.
| S-EPMC7643095 | biostudies-literature
Project description:Deasphalting bitumen using paraffinic solvent injection is a commonly used technique to reduce both its viscosity and density and ease its flow through pipelines. Common modeling approaches for asphaltene precipitation prediction such as population balance model (PBM) contains complex mathematical relation and require conducting precise experiments to define initial and boundary conditions. Machine learning (ML) approach is considered as a robust, fast, and reliable alternative modeling approach. The main objective of this research work was to model the effect of paraffinic solvent injection on the amount of asphaltene precipitation using ML and PBM approaches. Five hundred and ninety (590) experimental data were collected from the literature for model development. The gathered data was processed using box plot, data scaling, and data splitting. Data pre-processing led to the use of 517 data points for modeling. Then, multilayer perceptron, random forest, decision tree, support vector machine, committee machine intelligent system optimized by annealing, and random search techniques were used for modeling. Precipitant molecular weight, injection rate, API gravity, pressure, C5 asphaltene content, and temperature were determined as the most relevant features for the process. Although the results of the PBM model are precise, the AI/ML model (CMIS) is the preferred model due to its robustness, reliability, and relative accuracy. The committee machine intelligent system is the superior model among the developed smart models with an RMSE of 1.7% for the testing dataset and prediction of asphaltene precipitation during bitumen recovery.
| S-EPMC9494634 | biostudies-literature
Project description:Crude oil extracted from oilfield reservoirs brings together hypersaline produced water. Failure in pipelines transporting this mixture causes contamination of the soil with oil and hypersaline water. Soil salinization is harmful to biological populations, impairing the biodegradation of contaminants. We simulated the contamination of a soil from an oilfield with produced water containing different concentrations of NaCl and crude oil, in order to evaluate the effect of salinity and hydrocarbon concentration on prokaryote community structure and biodegradation activity. Microcosms were incubated in CO2-measuring respirometer. After the incubation, residual aliphatic hydrocarbons were quantified and were performed 16S rRNA gene sequencing. An increase in CO2 emission and hydrocarbon biodegradation was observed with increasing oil concentration up to 100 g kg-1. Alpha diversity decreased in oil-contaminated soils with an increase in the relative abundance of Actinobacteria and reduction of Bacteroidetes with increasing oil concentration. In the NaCl-contaminated soils, alpha diversity, CO2 emission, and hydrocarbon biodegradation decreased with increasing NaCl concentration. There was an increase in the relative abundance of Firmicutes and Proteobacteria and a reduction of Actinobacteria with increasing salt concentration. Our results highlight the need to adopt specific bioremediation strategies in soils impacted by mixtures of crude oil and hypersaline produced water.
| S-EPMC8105486 | biostudies-literature
Project description:In recent years, researchers have attempted to find some practical approaches for asphaltene adsorption and the prevention or postponement of asphaltene precipitation. Among different techniques, nanotechnology has attracted the researchers' attention to overcome the formation damage resulting from the deposition of asphaltenes. In this study, the application of two types of carboxylate-alumoxane nanoparticles (functionalized boehmite by methoxyacetic acid (BMA) and functionalized pseudo-boehmite by methoxyacetic acid (PBMA)) for asphaltene adsorption and precipitation was investigated. First, the synthesis of two functionalized nanoparticles was performed via the sol-gel method. For the assessment of the adsorption efficiency and adsorption capacity of these nanoparticles toward asphaltene adsorption, the batch adsorption experiments applying ultraviolet-visible (UV-Vis) spectroscopy were performed. The Langmuir and Freundlich isotherms were studied to describe the interaction between asphaltene molecules and carboxylate-alumoxane nanoparticles. For determining the "onset" point of asphaltene precipitation, the indirect method, which was based on the difference in the optical property of various solutions containing different concentrations of asphaltene, was utilized by applying UV-Vis spectroscopy. The isotherm models indicate that the adsorption of asphaltene on the surface of nanoparticles is better fitted to the Freundlich isotherm model compared with the Langmuir model. In the presence of PBMA (0.1 wt %), the onset point was delayed around 26, 20, and 17% in the asphaltene concentrations of 1000, 3000, and 5000 ppm, respectively, in comparison with their reference synthetic oils. On the other hand, these postponements for BMA nanoparticles (0.1 wt %) were 17%, 9%, and insignificant for the asphaltene concentrations of 1000, 3000, and 5000 ppm, respectively. The results reveal that two functionalized nanoparticles tend to adsorb asphaltene molecules and have a positive impact on the postponement of asphaltene precipitation due to molecular interactions between the surface of carboxylate-alumoxane nanoparticles and asphaltene molecules. However, PBMA nanoparticles exhibited better performance on the asphaltene adsorption and postponement of asphaltene precipitation, which is related to its smaller size, as well as higher surface area, compared with BMA nanoparticles.
| S-EPMC7346270 | biostudies-literature