Search

Abstract Chemical-assisted waterflooding enhances the ultimate recovery of a conventional waterflooding process through several mechanisms such as reducing interfacial tension between water and oil, formation of in-situ emulsions, treatment of adverse mobility ratio, and wettability modification. Application of chemical-assisted waterflooding for recovery of heavy oil is still an active research topic. A new chemical technology (i.e. IPC Technology as referred to in this paper) has been developed. A proprietary mixture of surfactants is used in several techniques associated with surface extraction as well as in-situ recovery of heavy oil and bitumen. This formulation of solvents and surfactants is reusable, low foaming, non-flammable, not acutely toxic, and non-carcinogenic. The efficacy of using IPC as an additive for waterflooding was presented earlier through a systematic coreflooding study, which showed increased ultimate recovery of different types of oils when compared with commercial surfactant and alkali flooding. In order to investigate the mechanisms behind the enhanced macro-scale oil recovery, a series of pore-scale tests were designed and conducted in this study. Glass micromodel type of porous media was used in the presence of brines with different ion compositions. The pore-scale chemical-assisted waterflooding tests were carried out in four consecutive stages: brine flooding, chemical flooding, soaking period, and extended brine flooding. High quality pore-scale images were captured for qualitative and quantitative analysis of the IPC-assisted waterflooding at the pore-level. IPC intensified water wettability of grain particles in the presence of NaCl; however in the presence of MgCl 2 , use of IPC makes solid surfaces oil-wet. The phenomenon of water-in-oil and oil-in-water emulsification was observed when IPC was used along with different brine compositions. This phenomenon is weakened for lighter oils. When the acid number of the oil was low, extension of soaking period intensified wettability alteration and emulsification mechanisms. Other pore-scale phenomena were also observed during visualization tests such as coalescence of microdroplets during the extended waterflooding stage, snap-off mechanism creating daughter droplets during the extended waterflooding stage, occasional flow of bulk oil films toward the production end, and wettability reversal during various flooding stages. Attempts were also made to conduct statistical analysis of emulsion droplet sizes under different test conditions. Several parameters, including chemical concentration as well as ion concentration in brines, were found to significantly affect the emulsion droplet size distribution. [ABSTRACT FROM AUTHOR]

Abstract Use of chemicals as an additive during steam-based bitumen recovery processes has been an active topic for research and development in the last four decades. In this study, thermo-physical properties of mixtures of bitumen with a newly developed chemical are reported. This new chemical technology (i.e. IPC as referred in this paper) is a proprietary mixture of surfactants that has been used in several techniques associated with surface extraction as well as in-situ recovery of heavy oil and bitumen. This formulation of solvents and surfactants is reusable, low foaming, non-flammable, not acutely toxic and non-carcinogenic. A series of tests were conducted to measure density and viscosity of a bitumen, IPC, and different mixtures of bitumen-IPC at several pressure, temperature and chemical composition conditions. It was observed that solubility of IPC in bitumen was small, and its effects on the oil phase viscosity and density could not be separated from its effects on bulk properties caused by dispersed emulsified droplets of IPC. The impact of IPC on viscosity of mixture was more pronounced than its effect on mixture density. A very complex emulsion was formed upon contact of IPC with bitumen. The results of these tests will be useful in designing a steam-based bitumen recovery process with IPC as the chemical additive. Details of thermal stability analysis of IPC are also presented. Highlights • The effects of IPC formulation on density and viscosity of bitumen-IPC mixtures were studied. • Physical properties and thermal stability of IPC formulation was studied. • IPC formulation had no significant impact on mixture density up to 100 °C. • IPC formulation decreased the mixture viscosity at 100 °C and above. • Complex emulsions were formed upon low temperature mixing of IPC and bitumen. [ABSTRACT FROM AUTHOR]

[Display omitted] • A comprehensive study on renewable energy resources in North America is conducted. • A detailed evaluation of renewable energy potentials is provided. • Important steps for better use of renewable energy resources are summarized. • Emerging technologies for development and management of renewable energy are addressed. • Theoretical and practical challenges in development of renewable energies are highlighted. Energy is an important drive for the economic development and social growth. The energy demand has remarkably escalated due to the technological developments in various governmental, industrial, and municipal activities. The fast growing rate of the energy demand as well as the fuel prices, along with the necessity to control the greenhouse gas emissions are the leading driving forces for effective exploitation of the renewable energy resources. In fact, satisfying the growing global energy demands and mitigating the climate change are of the utmost importance in the modern days. In this review paper, a detailed overview of the development and evolution of the renewable and sustainable energy sources is provided in terms of their types, characteristics, applications, production processes, advantages and disadvantages. Moreover, we discuss the impacts of the renewable energies on health and environment, along with the relevant policies and regulations. Further, the emerging technologies and theoretical and practical challenges in the development of the renewable energies are analyzed. Particularly, this review provides information on renewable and sustainable energies' status and prospects in North America. Central large-scale technology and distributed configurations of the renewable energies might be improved in the North American countries to effectively utilize the renewable energies for producing electricity, biomass-based fuels, and heating in both local/rural and industrial divisions. In addition to employment opportunities stemmed from manufacturing of the renewable energies, its significant impact on the economic development can be enhanced in the US, Canada, and Mexico through development of the renewable energy sources. [ABSTRACT FROM AUTHOR]

Chemical-assisted waterflooding is injection of specialty chemical(s) along with water to enhance the productivity through a series of mechanisms. There are several mechanisms responsible for increased ultimate recovery of such a process compared to the traditional waterflooding process including in-situ emulsification of oil, conformance control and treatment of adverse mobility ratio, reduction of Interfacial Tension (IFT) between the in-situ oil and the injecting phase, and wettability modification to facilitate recovery of oil by enhanced relative permeability values. Although chemical-assisted waterflooding has been applied since the early 20th century, it has not been until recently that applicability of this process has been tested for recovery of heavy oil using preliminary macro-scale as well as pore-scale studies. A new chemical technology (i.e. IPC Technology as referred in this paper) has been developed. A proprietary mixture of surfactants is used in several techniques associated with surface extraction as well as in-situ recovery of heavy oil and bitumen. This formulation of solvents and surfactants is reusable, low foaming, non-flammable, not acutely toxic and non-carcinogenic. A systematic study, based on a series of coreflood tests, was designed and conducted to assess efficacy of IPC in the ultimate recovery of different types of oils by use of IPC-assisted waterflooding. Effects of IPC on IFT between oil and IPC solutions at different brine salinities/hardnesses and IPC concentrations were determined. Compatibility of IPC with different brine hardnesses and salinities was determined. IPC technology was particularly effective in recovering heavy oil. The performance of IPC as an additive during waterflood at elevated temperature for recovery of heavy oil was also investigated. For this particular purpose, thermal stability tests were conducted to determine the threshold temperature below which the formulation is thermally stable. When production performance of IPC-assisted waterflood was compared with alkali flooding and a commercial surfactant, IPC gave superior ultimate recovery. [ABSTRACT FROM AUTHOR]

[Display omitted] • Two effective predictive tools are introduced to accurately estimate biodiesel cetane number. • ET is more reliable and precise, compared to LSSVM. • Linoleic (18:02) has the highest importance in biodiesel cetane number. • The strongest correlation exists between Oleic (18:01) and Lauric (12:00), among input variables. • The results of sensitivity analysis are in good agreement with the literature. The self-ignition ability of fuels is characterized using a property called cetane number (CN). The main objective of this research work is to develop accurate models using smart algorithms to predict the CNs associated with 149 samples of biofuels collected from the literature. In this study, we use two machine learning (ML) algorithms, namely least squares support vector machine (LSSVM) and extra trees (ET) and an experimental dataset containing a variety of fatty acids methyl esters (FAME). To assess the predictive performance of the developed models, various statistical parameters including average relative deviation in percentage (ARD%), average absolute relative deviation in percentage (AARD%), and coefficient of determination (R2) are calculated. The statistical and graphical analyses presented in this study reveal that the ET model outperforms the LSSVM model in predicting the CN associated with the biodiesel systems from the collected dataset so that the value of AARD% is less than 3% for the ET method. It is also found that Linoleic (18:02) is the most important factor affecting the CN value of the biodiesels. According to the sensitivity analysis, the CN value decreases upon an increase in the concentration of Palmitoleic (16:01), Oleic (18:01), Linoleic (18:02), and Linolenic (18:03); this is in agreement with the experimental studies. The smart modelling techniques used in this study can be utilized as alternative methods to direct measurements for determination of biodiesel CN. [ABSTRACT FROM AUTHOR]

One of the most concerning areas for asphaltene deposition is the near-wellbore region, where such deposition may cause formation damage. The reservoir fluid of the Lake Maracaibo region is known to cause operational problems such as production losses due to asphaltene deposition. In this paper, we focus on the systematic evaluation of the asphaltene formation damage using stacked composite core samples and live oil samples from Lake Maracaibo area and study the formation damage due to asphaltene deposition inside the composite core stack. A special coreflood system was designed for an asphaltene formation damage study using reservoir core samples and sour–live reservoir fluid samples. The phenomenon of asphaltene precipitation and deposition in porous media and subsequent permeability impairment was evaluated while the fluid pressure decreased below the asphaltene onset pressure (AOP). Live fluid samples were collected and flooded through the stacked composite core plugs under reservoir conditions. Progressive pressure reductions were performed to induce asphaltene precipitation and deposition in the composite core. Changes in the absolute permeability of the composite core assembly due to asphaltene precipitation and deposition were calculated in the context of the pressure depletion process. Significant permeability impairment occurred from the depressurization of the reservoir fluid below the AOP. The upstream inlet pressure of the composite core stack was maintained just above the AOP while the outlet pressure was regulated approximately 50 psig above the saturation pressure throughout the coreflood experiment so that the onset of asphaltene precipitation occurred along the length of the composite core. Following the coreflood experiment, the core stack was depressurized and the remaining fluid was extracted from individual core plugs. Various analytical techniques such as asphaltene content measurement, simulated distillation and optical density were used to perform detailed post-trial analyses of the residual fluids extracted from each individual core plugs. Analyses of the thin sections extracted from various core plugs were also performed to investigate the microstructure of the residual hydrocarbon as well as the distribution of the flow pathways plugged with asphaltene aggregates in the pore structures. The results associated with these post-trial analyses confirmed that the observed permeability impairment was indeed due to the plugging of the flow pathways of the core plugs by asphaltene aggregates, and that the asphaltene-induced permeability loss was somewhat more extensive in the tighter plugs associated with the stacked core assembly. We present the systematic approach to perform asphaltene formation damage study using composite core and live reservoir fluid samples above the saturation pressure. [ABSTRACT FROM AUTHOR]

Brown algae adsorb a considerable amount of CO 2 and store carbon in their biomass more than many other algae species. Nowadays, depletion of fossil fuel resources, greenhouse gas emissions, climate change, and the future of human food security have encouraged scientists and policymakers to develop safer and more sustainable alternatives of energy sources. Brown algae have attracted most of this attention in North American countries to generate a wide range of products and biomass for biorefinery. In this review paper, various aspects of brown algae cultivation and its biorefinery process are discussed. Main drivers of the sectors, opportunities, challenges, and future prospects of brown algae-based biofuels in North America have been taken into account; the most appropriate processes and pathways are compared to maximize the outputs and environmental benefits, and minimize costs and drawbacks of the industry. Analysis and predictions of renewable energy future in North American countries revealed that biomass-derived fuels, including brown algae biofuels, will play an important role especially in the transportation sector. These biofuels, including bioethanol and biodiesel are accompanied by various co-products and by-products in an optimized biorefinery system to convert every available component of brown algae. However, cultivation of brown algae to produce biomass at a commercial scale with minimum costs and market demands are the main challenges of algal biofuels. Finally, expanding the value chain of the brown algae biorefinery by producing more advanced biofuels such as aviation fuels and value-added co- and by-products would significantly impact North American countries' gross domestic product. • Many studies related to biofuel production from brown algae are reviewed comprehensively. • Brown algae have attracted significant attention in North America. • Costs and markets demands are two main challenges for this algal energy. • Effective strategies for optimal production of biofuel from brown algae are provided. • Current challenges and future prospects for biofuel from brown algae are discussed. [ABSTRACT FROM AUTHOR]

In water- and wastewater-treatment processes, knowledge of sludge settlement behavior is a key requirement for proper design of a continuous clarifier or thickener. One of the most robust and practical tests to acquire information about rate of sedimentation is through execution of batch settling tests. In lieu of conducting a series of settling tests for various initial concentrations, it is promising and advantageous to develop simple predictive models to estimate the sludge settlement behavior for a wide range of operating conditions. These predictive mathematical model(s) also enhance the accuracy of outputs by eliminating measurement errors originated from graphical methods and visual observations. In the present study, two empirical models were proposed based on Vandermonde matrix (VM) characteristics as well as a Levenberg–Marquardt (LM) algorithm to predict temporal height of the supernatant–sludge interface. The novelty of our modeling approach is twofold: the proposed models in this study are more robust and simpler compared to other models in the literature, and the initial sludge concentration was considered as a key independent variable in addition to the more-customarily used settling time. The prediction performance of the VM-based model was better than the LM-based model considering the statistical parameters associated with the fitting of the experimental data including coefficient of determination (R2), root mean square error (RMSE), and mean absolute percentage error (MAPE). The values of R2, RMSE, and MAPE for the VM- and LM-based models were obtained at 0.997, 0.132, and 5.413% as well as 0.969, 0.107, and 6.433%, respectively. The proposed predictive models will be useful for determination of the sedimentation behavior at pilot- or industrial-scale applications of water treatment, when the experimental methods are not feasible, time is limited, or adequate laboratory infrastructure is not available. [ABSTRACT FROM AUTHOR]

[Display omitted] • Vital parameters affecting control and utilization of co-culture systems are evaluated. • Utilization of microalgal microbial fuel cells in wastewater treatment is reviewed. • Microalgal co-cultivation systems for biomass/biofuel production are analyzed. • Techniques for biomass and lipid content measurement are comprehensively discussed. • Current challenges and future prospects in microalgal co-cultures progress are addressed. The adverse impacts of fossil fuels on the environment, specifically climate change, have intensified the need for finding a sustainable alternative source of energy. Numerous studies have postulated that biotechnology development, focusing on biofuel production processes, could be a suitable solution for sustainable energy production. The utilization of microorganisms, such as microalgae, is one of the basic strategies to produce biodiesel, pharmaceuticals, and nutraceuticals. Co-cultivation has overtaken mono-cultivation to improve the production of microalgae due to its endurance, foreseeability, and stability. However, further development of the co-cultivation process requires elaborate efforts to make it safe, practical, and optimal. Some dominant factors affecting the co-culture system control are the diversity of the cell groups, mass transfer, scale-up, population ratio, and time. In this review article, we will discuss some critical topics related to the co-cultivation process, such as data collection, modelling, cultivation methods, and interaction varieties. An overview of the quantification techniques for biomass concentration and lipid content is also provided. Moreover, the utilization of microalgal co-cultures will be analyzed, depicting the difficulties associated with their efficient control. As knowledge of the reactions and their entailing kinetics is elemental for analyzing the microalgal systems, which are used to synthesize intermediate products and chemicals, some studies focusing on the kinetics of microalgal biomass conversion into biofuels are presented. Since the microbial fuel cells (MFCs), as a new bioelectrochemical process, are utilized in the mixed-culture systems to treat wastewater and produce biofuels and other valuable by-products, a summary of the microalgal MFCs is also provided. Finally, arguments about the challenges and advantages of the co-cultivation systems are presented. [ABSTRACT FROM AUTHOR]

[Display omitted] • Two integrated configurations for H 2 production from solid oxide fuel cell waste heat are compared. • PEM electrolyzer and Cu-Cl electro-thermochemical are considered in two different scenarios. • Water scrubbing-based biogas upgrading system is used to supply input feed to a solid oxide fuel cell. • Opting for Cu-Cl cycle over PEM/CO 2 power cycle enhances economic and thermodynamic conditions. • Exergy, economic, optimization and uncertainty analyses are used to determine optimal conditions. The efficient and cost-effective design of an integrated structure relying on a biogas-based fuel cell for hydrogen (H 2) production can represent a key step to attain the goal of net-zero carbon emissions. In this paper, waste heat and generated power of the hybrid configuration based on the biogas purification cycle and solid oxide fuel cell are utilized to produce H 2. In the first H 2 production scenario, the waste heat and power are used in a copper-chlorine (Cu-Cl) thermochemical plant and a polymer electrolyte membrane (PEM) electrolysis unit. In the second H 2 production scenario, the power and waste heat are employed in a carbon dioxide power process and a PEM electrolyzer. Using an energy analysis, the thermal efficiency of the Cu-Cl/PEM-based system is 25.19% greater than that of the PEM-based system. The exergy efficiency of the Cu-Cl/PEM- and PEM-based systems are calculated at 48.10% and 40.12%, respectively. The prime cost of H 2 for the Cu-Cl/PEM-based system is 27.64% smaller compared to that of the PEM-based system. From the thermodynamic and economic perspectives, the first H 2 production scenario seems superior compared to the second one. Sensitivity analysis, machine learning, and multi-objective optimization approaches are used to extract the optimum conditions on the Pareto front. Biogas flow rate, cupric chloride change ratio, and inlet air to fuel cell as the inlet parameters and H 2 flow rate, net annual profit, and irreversibility as the output parameters in the machine learning analysis are considered. The parameters used in the machine learning analysis are obtained from the sensitivity analysis of the first scenario. Various decision criteria are employed to select the optimum operating conditions in the Pareto front. Using particle swarm optimization, the TOPSIS technique determines the operating conditions that have the highest H 2 production (i.e., 171.3 kg/h) and net annual profit (i.e., 3.407 MMUSD/yr). The fuzzy Bellman-Zadeh method introduces the conditions that have the lowest irreversibility for the first scenario. The uncertainty levels of the objective functions are examined using a Monte Carlo-based uncertainty quantification. [ABSTRACT FROM AUTHOR]

• Nanoemulsion flooding in porous systems is experimentally investigated. • Taguchi experimental design approach is employed to obtain proper variable levels. • An appreciable recovery factor is attained under optimal concentration of nano-particles. • Parametric sensitivity analysis is conducted to make better design and operation decisions. • IFT reduction, viscosity reduction, and wettability modification are the main recovery mechanisms. Utilization of nanoparticles in oil and gas industry has attracted considerable attention of engineers and researchers. In this article, the feasibility of nanoemulsion flooding is investigated as a method for Enhanced Oil Recovery (EOR) through coreflooding experiments, using a packed bed and real reservoir fluids. Nine different mixtures of the solvent, surfactant, and nanoparticles in the form of a nanoemulsion phase are generated and used to recover the oil in the context of an EOR process. Various tests are conducted to determine the properties of porous medium and fluids. To study the production performance of this EOR technique, pressure drop across the packed bed are measured, along with the volumetric measurements of the produced fluids. A baseline injection scheme using seawater is also performed. All the nanoemulsion fluids are synthesized using the same base seawater. The Taguchi experimental design approach is employed in this research to design the experiments. The effects of nanoparticles concentration, along with those of surfactant and solvent components of the injection fluid on the oil recovery at the laboratory scale are investigated using the Analysis of Variance (ANOVA) method. Comparing the performance of waterflooding (WF) and nanoemulsion flooding, enhancement in the Recovery Factor (RF) by using emulsions is between 40–107%. Both the pressure and pressure fluctuations are surprisingly higher in the case of WF in comparison to the emulsion flooding. It is also found that under optimal concentration conditions (0.01 g of nanoparticles, 0.015 mL of surfactant, and 1 mL of solvent per one liter of brine), a recovery factor of up to 60% is achieved. [ABSTRACT FROM AUTHOR]

Water-based drilling muds, a more environment-friendly candidate than oil-based drilling muds, are wildly used for drilling oil and gas wells. When water-based drilling mud is used for drilling formations with shale containing active clay constituents, it is challenging to preserve stability of the borehole due to clay swelling unless proper inhibition mechanisms are foreseen. In the current study, the feasibility of using Korean red Ginseng root extract was assessed as a clay swelling inhibitor. This root extract is rich in non-ionic surfactants such as Ginsenosides Rg3, Rg5, and RK1, and is referred to as "biosurfactant" throughout this manuscript. After preparation of mud systems containing problematic clay particles, the clay-swelling inhibition performance of the biosurfactant was systematically investigated through a series of tests, including mud formation, filtration, immersion, sedimentation assisted with optical microscopy, wettability by sessile drop technique, use of thermal gravimetric analysis (TGA), scanning electron microscopy (SEM) and Fourier-transform infrared spectroscopy (FTIR), and shale cuttings recovery. The clay-swelling inhibition performance of the biosurfactant was then compared against two clay swelling inhibitors namely CTAB (Cetrimonium bromide, a known cationic surfactant) and potassium chloride. There are some properties associated with the mud systems prepared with biosurfactant solution which makes this product unique. These properties include: remarkable loading capacity of sodium montmorillonite (Mt) which in turn resulted in low rheological profile, poor fluid loss control, creation of stable Mt pellets, creation of larger size and aggregated Mt particles with less hydrophilicity, creation of fully unstable dispersed Mt particles that resulted in good sedimentation over time, less mass loss, and higher shale cuttings recovery, all compared to the baseline fluid made without the presence of biosurfactant. The results of this study indicate that the biosurfactant provides excellent clay swelling inhibition properties, comparable to known inhibitors. The biosurfactant's compatibility with other drilling mud components was also checked, and it was found that the fluid properties are independent of the biosurfactant. The wettability and FTIR analyses were also performed to investigate the mechanisms involved in clay swelling inhibition of the biosurfactant, which are believed to be as a result of coating the clay active surfaces with a hydrophobic layer, hence repelling the water phase. This hydrophobic layer is probably formed by interactions of the hydrophilic group of the Ginsenosides and the oxygen atoms available on the Mt surfaces, when the hydrophobic tail is oriented toward the aqueous phase. Image 1 • The feasibility of using a biosurfactant was assessed as a clay swelling inhibitor. • The biosurfactant exhibited an acceptable performance. • Wettability alteration is the more probable inhibition mechanism. • The biosurfactant was compatible with the drilling fluid componnts. • The biosurfactant is biodegradable, environmentally friendly, and relatively inexpensive. [ABSTRACT FROM AUTHOR]

Highlights • This work highlights capability of LSSVM-CSA to determine vital thermodynamic properties. • This research introduces an effective computational tool to obtain solubility of hydrocarbons and non-hydrocarbons in aqueous solutions. • Parametric sensitivity analysis is performed to assess the model capability in capturing physical trends. • The developed approach offers higher reliability/precision within wide ranges of thermodynamic conditions, compared to previous works. Abstract Determining solubility of hydrocarbon and non-hydrocarbon components of natural gas is crucial for theoretical studies and engineering design. In this study, new solubility prediction models were developed for both hydrocarbon gases (methane, ethane, propane, and butane) and non-hydrocarbon gases (CO 2 and N 2) in aqueous solutions of strong electrolytes using a hybrid modeling strategy, which links the Coupled Simulated Annealing (CSA) to the Least-Squares Support Vector Machine (LSSVM) technique. Comparing the models' predictions with experimentally determined solubility values, a very good agreement was noticed, leading to the overall correlation coefficients of 0.9880 and 0.9907 for the hydrocarbon and non-hydrocarbon gases, respectively. These models were also found to succeed in capturing the physical trends among experimental datasets through performing sensitivity analysis between the dependent and independent parameters. Developed models can be utilized to predict the solubility of pure and/or a mixture of hydrocarbon and non-hydrocarbon gases in aqueous electrolyte solutions, covering wide ranges of ionic strength, pressures, and temperatures up to supercritical conditions. Such a reliable predictive tool helps researchers and engineers to successfully obtain the key thermodynamic properties (e.g., solubility, vapor pressure, and compressibility factor), which are central to properly design and operate the corresponding units in a variety of chemical plants such as petrochemical plants, natural gas processing plants, and refineries. [ABSTRACT FROM AUTHOR]

Graphical abstract Highlights • This study introduces an experimental and modeling approach to obtain asphaltene precipitation. • The new technique is more accurate for light to heavy oils, compared to previous models. • The new approach considers vital oil and process characteristics in asphaltene precipitation. • A sensitivity analysis is conducted to make better operating and policy decisions while dealing with asphaltene precipitation. • The most influencing parameters in asphaltene precipitation are pressure and dilution ratio. Abstract Asphaltenes are heavy fractions of petroleum mixtures, which precipitate out of homogenous bulk fluid phase due to changes in pressure, temperature, and composition. Asphaltene precipitation and subsequent deposition in porous media can adversely affect Enhanced Oil Recovery (EOR) processes as well as impede surface transportation of crude oil. It is therefore beneficial to develop accurate techniques for determination of asphaltene precipitation as well as reliable predictive modeling approaches to remedy potential production impairments. In this study, a laboratory work is performed using three different oil samples (light, medium-viscosity, and heavy crude oil) to measure the mass of precipitated asphaltenes in a series of titration experiments. The effects of various parameters such as precipitant type, pressure, dilution ratio, API gravity of oil, and resin-to-asphaltene ratio of crude oil on the amount of precipitated asphaltenes are studied. A deterministic tool, so-called Response Surface Methodology (RSM), is then proposed to estimate the mass of asphaltenes precipitated from these three oil types in a titration process as a function of input parameters selected through a systematic parametric sensitivity analysis. The Analysis of Variance (ANOVA) technique is also employed to assess the validity of the proposed predictive methodology. Among all the contributing parameters, pressure and dilution ratio are found to be the most influencing factors when predicting the mass of precipitated asphaltenes. The developed simple predictive tool appears to be an effective methodology to forecast the mass of precipitated asphaltenes over a wide range of input parameters for various oil types. [ABSTRACT FROM AUTHOR]

Capillary pressure is one of the most important parameters affecting fluids distribution in a reservoir rock and is an essential input parameter for reservoir simulation. Measurement of capillary pressure data, in the context of special core analysis (SCAL) is a time and cost consuming process that does not often lead to accurate and reliable results. Routine core analysis (RCAL) data, on the other hand, can be obtained by simple, accurate, and cost-effective procedures. In this paper, the idea of using RCAL measurements to predict SCAL data (more specifically capillary pressure data) using Artificial Neural Network (ANN) approach is presented. An ANN with Multi-Linear Perceptron structure and feed-forward propagation was used to predict capillary pressure curves for a target reservoir under study. The ANN model was then optimized by Cuckoo optimization algorithm (COA). The ANN-COA model was used for 30 measurements, composed of both drainage and imbibition data points obtained from 15 core samples using centrifugation method. Out of this databank, 16 measurements were used for training and the remaining 14 measurements were used as the testing dataset. It was obtained that the optimized model shows a profound predicting performance based on the excellent value of coefficient of determination for predicted versus measured capillary pressure data. [ABSTRACT FROM AUTHOR]

Wellbore instability is one of the most critical challenges that continuously appear in drilling and production operations. Borehole breakout, as the enlargement and elongation of a borehole in a preferential direction, is an important phenomenon which should be addressed when stability of the wellbore is analyzed. Breakout pressure is an important parameter in wellbore stability analysis. In this paper, a geomechanical model was constructed using several petrophysical, field and lab data for one formation of interest to evaluate in-situ and induced stresses. Three shear failure criteria, namely Mohr-Coulomb, Mogi-Coulomb and Hoek-Brown were used to predict the breakout pressure profile and the outcomes were validated with 4-arm caliper log data of the well. The effect of azimuth and inclination of the deviated wells on the breakout pressure was investigated using stress transformation equations. It was found that the Hoek-Brown failure criterion with optimized constants resulted in the best prediction of the breakout pressure for this particular case under study. As for the deviated wells, inclination had an increasing effect on the breakout pressure whereas azimuth relative to the maximum horizontal stress could counteract it. [ABSTRACT FROM AUTHOR]

[Display omitted] • Self-aggregation of Quinolin-65 is simulated using MD and DFT approaches. • vdW interactions between aromatic rings in Quinolin-65 molecules affect self-aggregation. • The aggregation process is strongly influenced by the medium solubility parameter. • An increase in temperature increases the molecule stability. • The molecular behaviors and interaction forces are well explored by MD and DFT. Asphaltene is the heaviest and most polar component of the crude oil. Asphaltene precipitation and deposition results in some adverse processes in both upstream and downstream petroleum industry such as formation of water-in-oil emulsions, wettability alteration of the reservoir rock, pore blockage leading to permeability impairment, blockage of transportation pipeline, and catalyst poisoning in refineries. Asphaltene self-aggregation plays a major role in all these operational difficulties. Although several studies have been carried out on asphaltene aggregation, there is limited scientific understanding of asphaltene self-aggregation at the microscopic level. In this study, Quinolin-65 molecule is considered as a model asphaltene structure. The effect of various factors contributing to self-aggregation of Quinolin-65 molecules including intermolecular interactions, temperature, pressure, solvent, and molecular structure are investigated using quantum mechanics analysis and molecular dynamics (MD) simulations. Results of reduced density gradient (RDG) analysis demonstrated that the strong van der Waals interaction between aromatic rings in two Quinolin-65 molecules is a critical factor in their dimerization and self-aggregation. Radial distribution function, potential of mean force, and mean square displacement are calculated using MD simulation. The Quinolin-65 aggregation tendency in the toluene medium is significantly decreased compared to that in the water and heptane media, due to the interactions between the Quinolin-65 molecules and toluene. According to the MD simulation results, the solubility parameter of the medium can affect the Quinolin-65 aggregation process. The stability of Quinolin-65 molecule in the medium is increased by increasing the temperature. Upon a change in the Quinolin-65 aggregation behavior, the free energy variation range with pressure and temperature is from −4.01 to −0.23 kj mol and −3.49 to −0.56 kj mol , respectively. This study provides new insights/findings to better understand the interaction force(s) between the Quinolin-65 molecules as well as the effect of different thermodynamic conditions on Quinolin-65 molecules self-aggregation at the molecular level. Moreover, this research work assesses the synergistic effects of influential parameters (e.g., thermodynamic conditions, solvent, and structure) on the Quinolin-65 self-aggregation behavior, which can help predict some serious flow assurance issues associated with the precipitation/deposition of asphaltene particles. [ABSTRACT FROM AUTHOR]

• A hybrid smart model is employed for optimization of gas injection. • A novel objective function is introduced for optimal gas injection scenario. • A systematic sensitivity analysis is conducted to identify vital factors. • Maximizing cumulative oil production is not the best decision. • There is a good match between the ANN predictions and simulation/real data. A considerable volume of oil remains in the reservoir after terminating the primary and secondary oil recovery stages. It is the target of enhanced oil recovery (EOR) processes to increase the overall oil displacement efficiency. Gas injection process is the most commonly used technique in EOR. There has always been a demand for optimizing the gas injection process through modifying the determining factors such as injection/production well placement, injection rate, composition of the injected gas phase, to name a few. In this study, a combination of artificial neural networks (ANN) and genetic algorithm (GA) was used to discover and then optimize the connections between different properties and variables of a reservoir which is undergoing a gas injection process. A commercial reservoir simulator was used to simulate the production performance of the target reservoir. A new objective function was also developed to optimize the gas injection process based on the final profits gained. According to the results, production maximization was not the best decision since it was not the most profitable alternative. However, a profit-based optimization considering the costs of gas injection and the oil price was proved to be a better solution to the optimization problem. For a five-year production period, employing the profit-based optimization for well productivity index calculation resulted in an earned profit of 5.7 × 109 USD, achieved through injection of 203,600 MMSCFD of gas. On the other hand, production maximization approach led to a lesser earned profit of 5.39 × 109 USD due to injection of much greater volume of gas (310,000 MMSCFD). The results of the ANN modelling demonstrated the ability of the hybrid smart model in predicting production performance of the target reservoir under gas injection process. In addition, the ANN model was capable of accurately predicting noise-containing data which makes it a highly reliable candidate to apply on real field data. [ABSTRACT FROM AUTHOR]