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Showing papers in "Journal of Energy Resources Technology-transactions of The Asme in 2019"


Journal ArticleDOI
TL;DR: A comprehensive review of different thermal and non-thermal EOR methods is presented and discussed in this paper, which is considered the dominant technique among all different methods of EOR.
Abstract: The oil production from any well passes through three stages. The first stage is the natural extraction of oil under the well pressure, the second stage starts when the well pressure decreases. This second stage includes flooding the well with water via pumping sea or brackish water to increase the well pressure and push the oil up enhancing the oil recovery. After the first and secondary stages of oil production from the well, 20–30% of the well reserve is extracted. The well is said to be depleted while more than 70% of the oil are left over. At this stage, the third stage starts and it is called the enhanced oil recovery (EOR) or tertiary recovery. Enhanced oil recovery is a technology deployed to recover most of our finite crude oil deposit. With constant increase in energy demands, EOR will go a long way in extracting crude oil reserve while achieving huge economic benefits. EOR involves thermal and/or nonthermal means of changing the properties of crude oil in reservoirs, such as density and viscosity that ensures improved oil displacement in the reservoir and consequently better recovery. Thermal EOR, which is the focus of this paper, is considered the dominant technique among all different methods of EOR. In this paper, we present a brief overview of EOR classification in terms of thermal and nonthermal methods. Furthermore, a comprehensive review of different thermal EOR methods is presented and discussed.

95 citations


Journal ArticleDOI
TL;DR: In this paper, the characteristics of oil distribution in porous media systems during a high water-cut stage, sandstones with different permeability scales of 53.63 × 10-3 μm 2 and 108.11 ×10-3 µm 2 were imaged under a resolution of 4.12 μm during a water flooding process using X-ray tomography.
Abstract: To investigate the characteristics of oil distribution in porous media systems during a high water-cut stage, sandstones with different permeability scales of 53.63 ×10-3 μm 2 and 108.11 ×10-3 μm 2 were imaged under a resolution of 4.12 μm during a water flooding process using X-ray tomography. Based on the cluster-size distribution of oil segmented from the tomography images, and through classification using the shape factor and Euler number, the transformation of the oil distribution pattern in different injection stages was studied for samples with different pore structures. In general, the distribution patterns of an oil cluster continuously change during water injection. Large connected oil clusters break off into smaller segments. For sandstones with higher permeability, which show the largest change in distribution pattern, and the remaining oil is trapped in the pores with a radius of approximately 7-12 μm. Meanwhile, some disconnected clusters merge and lead to a re-connection during the high water cut period. Whereas the pore structure becomes compact and complex, the residual non-wetting phase becomes static and is difficult to move, and thus all distribution patterns coexist during the entire displacement process, and are mainly distributed in pores with a radius of 8-12 μm. For the pore-scale entrapment characteristics of the oil phase during a high water cut period, different enhance oil recovery (EOR) methods should be considered in sandstones correspondent to each permeability scale.

73 citations


Journal ArticleDOI
TL;DR: In this article, a power-to-synthetic natural gas (SNG) plant design and a techno-economic analysis of its performance for producing SNG by reacting renewably generated hydrogen from low-temperature electrolysis with captured carbon dioxide.
Abstract: Power-to-gas to energy systems are of increasing interest for low carbon fuels production and as a low-cost grid-balancing solution for renewables penetration. However, such gas generation systems are typically focused on hydrogen production, which has compatibility issues with the existing natural gas pipeline infrastructures. This study presents a power-to-synthetic natural gas (SNG) plant design and a techno-economic analysis of its performance for producing SNG by reacting renewably generated hydrogen from low-temperature electrolysis with captured carbon dioxide. The study presents a “bulk” methanation process that is unique due to the high concentration of carbon oxides and hydrogen. Carbon dioxide, as the only carbon feedstock, has much different reaction characteristics than carbon monoxide. Thermodynamic and kinetic considerations of the methanation reaction are explored to design a system of multistaged reactors for the conversion of hydrogen and carbon dioxide to SNG. Heat recuperation from the methanation reaction is accomplished using organic Rankine cycle (ORC) units to generate electricity. The product SNG has a Wobbe index of 47.5 MJ/m3 and the overall plant efficiency (H2/CO2 to SNG) is shown to be 78.1% LHV (83.2% HHV). The nominal production cost for SNG is estimated at 132 $/MWh (38.8 $/MMBTU) with 3 $/kg hydrogen and a 65% capacity factor. At U.S. DOE target hydrogen production costs (2.2 $/kg), SNG cost is estimated to be as low as 97.6 $/MWh (28.6 $/MMBtu or 1.46 $/kgSNG).

58 citations


Journal ArticleDOI
TL;DR: The Artificial neural network technique was combined with the self-adaptive differential evolution algorithm (SaDe) to develop an optimum ANN model for each rheological property using 1029 data points, and the SaDe helped to optimize the best combination of parameters for the ANN models.
Abstract: The rheological properties of the drilling fluid play a key role in controlling the drilling operation. Knowledge of drilling fluid rheological properties is very crucial for drilling hydraulic calculations required for hole cleaning optimization. Measuring the rheological properties during drilling sometimes is a time-consuming process. Wrong estimation of these properties may lead to many problems, such as pipe sticking, loss of circulation, and/or well control issues. The aforementioned problems increase the non-productive time and the overall cost of the drilling operations. In this paper, the frequent drilling fluid measurements (mud density, Marsh funnel viscosity (MFV), and solid percent) are used to estimate the rheological properties of bentonite spud mud. Artificial neural network (ANN) technique was combined with the self-adaptive differential evolution algorithm (SaDe) to develop an optimum ANN model for each rheological property using 1029 data points. The SaDe helped to optimize the best combination of parameters for the ANN models. For the first time, based on the developed ANN models, empirical equations are extracted for each rheological parameter. The ANN models predicted the rheological properties from the mud density, MFV, and solid percent with high accuracy (average absolute percentage error (AAPE) less than 5% and correlation coefficient higher than 95%). The developed apparent viscosity model was compared with the available models in the literature using the unseen dataset. The SaDe-ANN model outperformed the other models which overestimated the apparent viscosity of the spud drilling fluid. The developed models will help drilling engineers to predict the rheological properties every 15–20 min. This will help to optimize hole cleaning and avoid pipe sticking and loss of circulation where bentonite spud mud is used. No additional equipment or special software is required for applying the new method.

57 citations


Journal ArticleDOI
TL;DR: The potential applications of NH3 in conventional ICEs and advanced homogenous charge compression ignition (HCCI) engines are analyzed in this article, providing a theoretical basis for evaluating NH3 combustion in ICEs.
Abstract: Ammonia (NH3) is an excellent hydrogen (H2) carrier that is easy to bulk manufacture, handle, transport, and use. NH3 is itself combustible and could potentially become a clean transport fuel for direct use in internal combustion engines (ICEs). This technical review examines the current state of knowledge of NH3 as a fuel in ICEs on its own or in mixtures with other fuels. A particular case of interest is to partially dissociate NH3 in situ to produce an NH3/H2 mixture before injection into the engine cylinders. A key element of the present innovation, the presence of H2 is expected to allow easy control and enhanced performance of NH3 combustion. The key thermochemical properties of NH3 are collected and compared to those of conventional and alternative fuels. The basic combustion characteristics and properties of NH3 and its mixtures with H2 are summarized, providing a theoretical basis for evaluating NH3 combustion in ICEs. The combustion chemistry and kinetics of NH3 combustion and mechanisms of NOx formation and destruction are also discussed. The potential applications of NH3 in conventional ICEs and advanced homogenous charge compression ignition (HCCI) engines are analyzed.

51 citations


Journal ArticleDOI
TL;DR: In this paper, a new robust model was introduced to predict the rate of penetration (ROP) using both drilling parameters (WOB, Q, ROP, torque (T), standpipe pressure (SPP), uniaxial compressive strength (UCS), and mud properties (density and viscosity) using 7000 real-time data measurements.
Abstract: During the drilling operations, optimizing the rate of penetration (ROP) is very crucial, because it can significantly reduce the overall cost of the drilling process. ROP is defined as the speed at which the drill bit breaks the rock to deepen the hole, and it is measured in units of feet per hour or meters per hour. ROP prediction is very challenging before drilling, because it depends on many parameters that should be optimized. Several models have been developed in the literature to predict ROP. Most of the developed models used drilling parameters such as weight on bit (WOB), pumping rate (Q), and string revolutions per minute (RPM). Few researchers considered the effect of mud properties on ROP by including a small number of actual field measurements. This paper introduces a new robust model to predict the ROP using both drilling parameters (WOB, Q, ROP, torque (T), standpipe pressure (SPP), uniaxial compressive strength (UCS), and mud properties (density and viscosity) using 7000 real-time data measurements. In addition, the relative importance of drilling fluid properties, rock strength, and drilling parameters to ROP is determined. The obtained results showed that the ROP is highly affected by WOB, RPM, T, and horsepower (HP), where the coefficient of determination (T2) was 0.71, 0.87, 0.70, and 0.92 for WOB, RPM, T, and HP, respectively. ROP also showed a strong function of mud fluid properties, where R2 was 0.70 and 0.70 for plastic viscosity (PV) and mud density, respectively. No clear relationship was observed between ROP and yield point (YP) for more than 500 field data points. The new model predicts the ROP with average absolute percentage error (AAPE) of 5% and correlation coefficient (R) of 0.93. In addition, the new model outperformed three existing ROP models. The novelty in this paper is the application of the clustering technique in which the formations are clustered based on their compressive strength range to predict the ROP. Clustering yielded accurate ROP prediction compared to the field ROP.

50 citations


Journal ArticleDOI
TL;DR: By combining meaningful metrics of accuracy and precision, a new metric for determining the best-in-class method was defined.
Abstract: Mathematical methods such as empirical correlations, analytical models, numerical simulations, and data-intensive computing (data-driven models) are the key to the modeling of energy science and engineering. Accrediting of different models and deciding on the best method, however, is a serious challenge even for experts, as the application of models is not limited only to estimations, but to predictions and derivative properties. In this note, by combining meaningful metrics of accuracy and precision, a new metric for determining the best-in-class method was defined.

50 citations


Journal ArticleDOI
TL;DR: In this paper, the pore-throat size is a key parameter for the assessment of reservoirs and the existing pore characterization techniques were used jointly with scanning electron microscopy (SEM), low-temperature nitrogen adsorption (LTNA), high pressure mercury intrusion (HPMI), and rate-controlled mercury intrusion(RCMI) technologies to highlight features of throat sizes and distribution of pores in tight sandstone reservoirs of the Y Basin in China.
Abstract: Pore–throat size is a key parameter for the assessment of reservoirs. Tight sandstone has the strong heterogeneity in the distribution of pores and throats; consequently, it is very difficult to characterize their distributions. In this study, the existing pore–throat characterization techniques were used jointly with scanning electron microscopy (SEM), low-temperature nitrogen adsorption (LTNA), high-pressure mercury intrusion (HPMI), and rate-controlled mercury intrusion (RCMI) technologies to highlight features of throat sizes and distribution of pores in tight sandstone reservoirs of the Y Basin in China. In addition, full-scale maps (FSMs) were generated. The study results show that key pore types in reservoirs of the Y Basin include residual intergranular pores, dissolved pores, clay mineral pores, and microfractures. LTNA can effectively characterize the distribution of pore–throats with a radius of 2–25 nm. HPMI test results show that tight sandstones contain throats with a radius less than 1000 nm, which are mainly distributed in 25–400 nm and have a unimodal distribution. RCMI tests show that there is no significant difference in pore radius distribution of the tight sandstones, peaking at approximately 100,000–200,000 nm; the throat radius of tight sandstones varies greatly and is less than 1000 nm, in agreement with that of HPMI. Generally, the pore–throat radius distribution of tight sandstones is relatively concentrated. By using the aforementioned techniques, FSM distribution features of pore–throat radius in tight sandstone can be characterized effectively. G6 tight sandstone samples develop pores and throats with a radius of 2–350,000 nm, and the pore–throat types of tight sandstone reservoirs in Y basin are mainly mesopores and macropores.

47 citations


Journal ArticleDOI
TL;DR: In this paper, a reliable computational approach for the prediction of the rate of penetration (ROP) is proposed, which is a significant factor in drilling optimization and minimizing expensive drilling costs.
Abstract: Predicting the rate of penetration (ROP) is a significant factor in drilling optimization and minimizing expensive drilling costs. However, due to the geological uncertainty and many uncontrolled operational parameters influencing the ROP, its prediction is still a complex problem for the oil and gas industries. In the present study, a reliable computational approach for the prediction of ROP is proposed. First, fscaret package in a R environment was implemented to find out the importance and ranking of the inputs’ parameters. According to the feature ranking process, out of the 25 variables studied, 19 variables had the highest impact on ROP based on their ranges within this dataset. Second, a new model that is able to predict the ROP using real field data, which is based on artificial neural networks (ANNs), was developed. In order to gain a deeper understanding of the relationships between input parameters and ROP, this model was used to check the effect of the weight on bit (WOB), rotation per minute (rpm), and flow rate (FR). Finally, the simulation results of three deviated wells showed an acceptable representation of the physical process, with reasonable predicted ROP values. The main contribution of this research as compared to previous studies is that it investigates the influence of well trajectory (azimuth and inclination) and mechanical earth modeling parameters on the ROP for high-angled wells. The major advantage of the present study is optimizing the drilling parameters, predicting the proper penetration rate, estimating the drilling time of the deviated wells, and eventually reducing the drilling cost for future wells.

41 citations


Journal ArticleDOI
TL;DR: In this article, a single-cylinder engine fueled with MD10 and MD15 was compared with baseline mineral diesel using a fuel additive (1-dodecanol), and the results indicated that methanol blending with mineral diesel resulted in superior combustion, performance, emissions, and particulate characteristics.
Abstract: Miscibility of methanol in mineral diesel and stability of methanol–diesel blends are the main obstacles faced in the utilization of methanol in compression ignition engines. In this experimental study, combustion, performance, emissions, and particulate characteristics of a single-cylinder engine fueled with MD10 (10% v/v methanol blended with 90% v/v mineral diesel) and MD15 (15% v/v methanol blended with 85% v/v mineral diesel) are compared with baseline mineral diesel using a fuel additive (1-dodecanol). The results indicated that methanol blending with mineral diesel resulted in superior combustion, performance, and emission characteristics compared with baseline mineral diesel. MD15 emitted lesser number of particulates and NOx emissions compared with MD10 and mineral diesel. This investigation demonstrated that methanol–diesel blends stabilized using suitable additives can resolve several issues of diesel engines, improve their thermal efficiency, and reduce NOx and particulate emissions simultaneously.

36 citations


Journal ArticleDOI
TL;DR: In this article, the authors used a simplified combustion model based on the flamelet concept to provide acceptable results with minimum computational costs and reasonable running times, however, the simulation can neglect small combustion chamber details such as valve crevices, valve recesses, and piston crevice volume.
Abstract: Three-dimensional computational fluid dynamics internal combustion engine simulations that use a simplified combustion model based on the flamelet concept provide acceptable results with minimum computational costs and reasonable running times. Moreover, the simulation can neglect small combustion chamber details such as valve crevices, valve recesses, and piston crevices volume. The missing volumes are usually compensated by changes in the squish volume (i.e., by increasing the clearance height of the model compared to the real engine). This paper documents some of the effects that such an approach would have on the simulated results of the combustion phenomena inside a conventional heavy-duty direct injection compression-ignition engine, which was converted to port fuel injection spark ignition operation. Numerical engine simulations with or without crevice volumes were run using the G-equation combustion model. A proper parameter choice ensured that the numerical results agreed well with the experimental pressure trace and the heat release rate. The results show that including the crevice volume affected the mass of a unburned mixture inside the squish region, which in turn influenced the flame behavior and heat release during late-combustion stages.

Journal ArticleDOI
TL;DR: In this paper, a rainbow-shaped piezoelectric energy harvester mounted on the inner layer of a pneumatic tire for providing enough power for microelectronics devices required for monitoring intelligent tires is presented.
Abstract: Intelligent tires can be used in autonomous vehicles to insure the vehicle safety by monitoring the tire and tire-road conditions using sensors embedded on the tire. These sensors and their wireless communication systems need to be powered by energy sources such as batteries or energy harvesters. The deflection of tires during rotation is an available and reliable source of energy for electric power generation using piezoelectric energy harvesters to feed tire self-powered sensors and their wireless communication systems. The aim of this study is to design, analyze, and optimize a rainbow-shaped piezoelectric energy harvester mounted on the inner layer of a pneumatic tire for providing enough power for microelectronics devices required for monitoring intelligent tires. It is shown that the designed piezoelectric energy harvester can generate sufficient voltage, power, and energy required for a tire pressure monitoring system (TPMS) with high data transmission speed or three TPMSs with average data transmission speed. The effect of the vehicle speed on the voltage and electric energy generated by the designed piezoelectric is also studied. The geometry and the circuit load resistance of the piezoelectric energy harvester are optimized in order to increase the energy harvesting efficiency. It is shown that the optimized rainbow piezoelectric energy harvester can reach the highest power generation among all the strain-based energy harvesters that partially cover the inner layer of the tire.

Journal ArticleDOI
TL;DR: In this article, a multishell thermodynamic model was developed to measure laminar burning speed of biomass/air mixture with varying CO2 concentrations, based on the pressure rise data collected from a cylindrical chamber during combustion.
Abstract: Biomass has been considered as a valuable alternative fuel recently. A fundamental property of biomass/air flame, laminar burning speed, is measured in this research. Experiments have been made in a cylindrical combustion vessel with two end windows. Central ignition has been used to start the combustion process. A high-speed CMOS camera capable of taking pictures of 40,000 frames per second has been used to study morphology of flame front. Flames are initially smooth, and as pressure and flame radius increase, cracks and cells appear on the flame surface. In this paper, experimental results have only been reported for smooth flames. A multishell thermodynamic model to measure laminar burning speed of biomass/air mixture with varying CO2 concentrations (0%–60%), based on the pressure rise data collected from a cylindrical chamber during combustion, has been developed in this paper. Burning speed has been only reported for flame radii larger than 4 cm in radius in order to have negligible stretch effect. Power law correlations, to predict burning speed of biomass/air mixtures, based on the measured burning speeds, have been developed for a range of temperatures of 300–661 K, pressures of 0.5–6.9 atmospheres, equivalence ratios of 0.8–1.2, and CO2 concentrations 0%–60%. Moreover, the measured laminar burning speeds have been compared with simulation results using a one-dimensional steady-state laminar premixed flame program with GRI-Mech 3.0 mechanism and other available data from literatures. Comparison with existing data has been excellent.

Journal ArticleDOI
TL;DR: In this article, the effects of different impurity compositions, considering binary mixtures of CO2 and He, CO, O2, N2, H2, CH4, or H2S on various S-CO2 cycle components are examined.
Abstract: With the increasing demand for electric power, the development of new power generation technologies is gaining increased attention. The supercritical carbon dioxide (S-CO2) cycle is one such technology, which has relatively high efficiency, compactness, and potentially could provide complete carbon capture. The S-CO2 cycle technology is adaptable for almost all of the existing heat sources such as solar, geothermal, fossil, nuclear power plants, and waste heat recovery systems. However, it is known that optimal combinations of operating conditions, equipment, working fluid, and cycle layout determine the maximum achievable efficiency of a cycle. Within an S-CO2 cycle, the compression device is of critical importance as it is operating near the critical point of CO2. However, near the critical point, the thermo-physical properties of CO2 are highly sensitive to changes of pressure and temperature. Therefore, the conditions of CO2 at the compressor inlet are critical in the design of such cycles. Also, the impurity species diluted within the S-CO2 will cause deviation from an ideal S-CO2 cycle as these impurities will change the thermodynamic properties of the working fluid. Accordingly, the current work examines the effects of different impurity compositions, considering binary mixtures of CO2 and He, CO, O2, N2, H2, CH4, or H2S on various S-CO2 cycle components. The second part of the study focuses on the calculation of the basic cycles and component efficiencies. The results of this study will provide guidance and define the optimal composition of mixtures for compressors and coolers.

Journal ArticleDOI
TL;DR: In this paper, the authors have strived to compile the basic momentum models that have been widely assumed in the literature for design and performance estimation of straight bladed vertical axis wind turbine (SB-VAWT) of Darrieus type.
Abstract: Momentum models or streamtube models represent one of the fundamental approaches in modeling the aerodynamics of straight bladed vertical axis wind turbine (SB-VAWT) of Darrieus type. They are based on momentum (actuator disk) theory and widely used in performance evaluation of VAWTs. In this short review, the authors have strived to compile the basic momentum models that have been widely assumed in the literature for design and performance estimation of SB-VAWTs of Darrieus type. A comprehensive demonstration of the formulation needed for the implantation of these models is also proposed. Three streamtube models are investigated in this paper, namely, the single streamtube (SST), the multiple streamtube (MST), and the double multiple streamtube (DMST) models. Each of these models has it merits and demerits which are also thoroughly discussed in this review.

Journal ArticleDOI
TL;DR: A hybrid artificial intelligence (AI) model is constructed to predict the short-term natural gas consumption and examine the effects of the factors in the consumption cycle and the prediction results demonstrated that the proposed model can give a better performance ofShort-termnatural gas consumption forecasting compared to the estimation value of existing models.
Abstract: Forecasting of natural gas consumption has been essential for natural gas companies, customers, and governments. However, accurate forecasting of natural gas consumption is difficult, due to the cyclical change of the consumption and the complexity of the factors that influence the consumption. In this work, we constructed a hybrid artificial intelligence (AI) model to predict the short-term natural gas consumption and examine the effects of the factors in the consumption cycle. The proposed model combines factor selection algorithm (FSA), life genetic algorithm (LGA), and support vector regression (SVR), namely, as FSA-LGA-SVR. FSA is used to select factors automatically for different period based on correlation analysis. The LGA optimized SVR is utilized to provide the prediction of time series data. To avoid being trapped in local minima, the hyper-parameters of SVR are determined by LGA, which is enhanced due to newly added “learning” and “death” operations in conventional genetic algorithm. Additionally, in order to examine the effects of the factors in different period, we utilized the recent data of three big cities in Greece and divided the data into 12 subseries. The prediction results demonstrated that the proposed model can give a better performance of short-term natural gas consumption forecasting compared to the estimation value of existing models. Particularly, the mean absolute range normalized errors of the proposed model in Athens, Thessaloniki, and Larisa are 1.90%, 2.26%, and 2.12%, respectively.

Journal ArticleDOI
TL;DR: In this article, a general method is formulated for assessing the wind turbine power upgrades using operational data based on the study of the residuals between the measured power output and a judicious model of the power output itself, before and after the upgrade.
Abstract: Wind turbine upgrades have recently been spreading in the wind energy industry for optimizing the efficiency of the wind kinetic energy conversion. These interventions have material and labor costs; therefore, it is fundamental to estimate the production improvement realistically. Furthermore, the retrofitting of the wind turbines sited in complex environments might exacerbate the stress conditions to which those are subjected and consequently might affect the residual life. In this work, a two-step upgrade on a multimegawatt wind turbine is considered from a wind farm sited in complex terrain. First, vortex generators and passive flow control devices have been installed. Second, the management of the revolutions per minute has been optimized. In this work, a general method is formulated for assessing the wind turbine power upgrades using operational data. The method is based on the study of the residuals between the measured power output and a judicious model of the power output itself, before and after the upgrade. Therefore, properly selecting the model is fundamental. For this reason, an automatic feature selection algorithm is adopted, based on the stepwise multivariate regression. This allows identifying the most meaningful input variables for a multivariate linear model whose target is the power of the upgraded wind turbine. For the test case of interest, the adopted upgrade is estimated to increase the annual energy production to 2.6 ± 0.1%. The aerodynamic and control upgrades are estimated to be 1.8% and 0.8%, respectively, of the production improvement.

Journal ArticleDOI
TL;DR: In this paper, the optimal design of a composite offshore wind turbine blade was determined through a parametric study by using a finite element method, where the skin thickness, thickness and width of the spar flange, and thickness, location and length of the front and rear spar web were varied until design criteria were satisfied.
Abstract: In order to obtain an optimal design of composite offshore wind turbine blade, take into account all the structural properties and the limiting conditions applied as close as possible to real cases. This work is divided into two stages: the aerodynamic design and the structural design. The optimal blade structural configuration was determined through a parametric study by using a finite element method. The skin thickness, thickness and width of the spar flange, and thickness, location, and length of the front and rear spar web were varied until design criteria were satisfied. The purpose of this article is to provide the designer with all the tools required to model and optimize the blades. The aerodynamic performance has been covered in this study using blade element momentum (BEM) method to calculate the loads applied to the turbine blade during service and extreme stormy conditions, and the finite element analysis was performed by using abaqus code to predict the most critical damage behavior and to apprehend and obtain knowledge of the complex structural behavior of wind turbine blades. The approach developed based on the nonlinear finite element analysis using mean values for the material properties and the failure criteria of Hashin to predict failure modes in large structures and to identify the sensitive zones.

Journal ArticleDOI
TL;DR: In this article, a parabolic trough solar collector (PTSC) plant is combined with a liquid air energy storage (LAES) system, and the GA is used to optimize the proposed system for different air storage mass flow rates.
Abstract: In this paper, a parabolic trough solar collector (PTSC) plant is combined with a liquid air energy storage (LAES) system. The genetic algorithm (GA) is used to optimize the proposed system for different air storage mass flow rates. The roundtrip exergy ratio is considered as the objective function and pressures of six points and mass flow rates of five points are considered as design parameters. The effects of some environmental and key parameters such as different radiation intensities, ambient temperatures, output pressures of the second compressor, and mass flow rates of the collectors fluid on the exergy ratio are investigated. The results revealed that the system could produce 17526.15 kJ/s (17.5 MW) power in high demands time and 2233.48 kJ/s (2.2 MW) power in low demands time and the system shows that a value of 15.13% round trip exergy ratio is achievable. Furthermore, the exergy ratio decreased by 5.1% when the air storage mass flow rate increased from 10 to 15 kg/s. Furthermore, the exergy ratio decreases by increasing the collectors inside fluid mass flow rate or by decreasing radiation intensity.

Journal ArticleDOI
TL;DR: In this paper, a high performance drilling fluid was designed for unconventional reservoirs to minimize the formation damage and borehole instability using organophilic clay treated with trimethyl octylammonium bromide, novel in-house synthesized gemini surfactant, and a high-molecular weight polymer.
Abstract: High-performance drilling fluid was designed for unconventional reservoirs to minimize the formation damage and borehole instability using organophilic clay treated with trimethyloctylammonium bromide, novel in-house synthesized gemini surfactant, and a high-molecular weight polymer. This gemini surfactant has not been reported in the literature for drilling fluid applications. The performance of designed drilling fluid was evaluated and compared with the base drilling fluid (4 w/v.% bentonite dispersion water). Shale dispersion, linear swelling, filtration, and rheological experiments were performed to investigate the effect of drilling fluids on borehole stability and formation damage. The combined use of organophilic clay and surfactant in the drilling fluid formulation reduced the shale dispersion up to 89%. The linear swelling experiment of shale sample shows 10% swelling of the core in the modified drilling fluid while in base fluid 13% swelling of shale was observed. It was found that modified drilling fluid interactions with shale were greatly reduced using a surfactant and associative polymer in the drilling fluid formulation. Rheological properties of drilling fluids were stable, and filtration characteristics showed that the filtrate volume was within the acceptable limit. The designed drilling fluid made a thin and impermeable filter cake that prevents the invasion of drilling fluid into the formation. This study opens a new direction to reduce the formation damage and borehole instability using organophilic clay, surfactant and high-molecular weight additive in water-based drilling fluid.

Journal ArticleDOI
TL;DR: In this paper, the authors investigated the reoxidation characteristics of coal seams mined from coal seams and showed that the cross point temperature of raw coal (146.3°C) was reduced to 137.1°C after it was pre-oxidized at 90°C.
Abstract: After coal seam mining, the residual coal is soaked with the accumulated water in goaf, and its spontaneous combustion characteristics were changed after air-dried. To study the reoxidation characteristics of soaked and air-dried coal, temperature-programmed experiments were carried out, and the cross point temperatures and index gases were investigated. Results showed that the cross point temperature of raw coal (146.3 °C) was reduced to 137.1 °C after it was pre-oxidized at 90 °C. The cross point temperature of water-soaked, and air-dried coal (96 h) was 122.5 °C, while the cross point temperature of water-soaked, air-dried (96 h) and pre-oxidized (90 °C) coal was 111.5 °C. Although CO was produced in the initial slow oxidation phase, it was found that C2H4 and C3H8 were not generated. In the rapid oxidation stage, different pretreatments affected the gas generation and the overall oxidative degree was consistent with the cross point temperature. The generation temperature and the concentration of C2H4 and C3H8 were decreased after the coal was water-soaked, air-dried, and pre-oxidized. Furthermore, the high-energy chemicals and functional groups were studied, which could be used to explain the physical experiment oxidation characteristics of different coals.

Journal ArticleDOI
TL;DR: In this article, the authors discuss nanoparticle transport phenomena in porous media with its focus on the filtration mechanisms, the underlying interaction forces, and factors dominating nanoparticles transport behaviour.
Abstract: Over the past few decades, due to the special features (i.e., easily produced, large-surface-area-to-volume ratio, and engineered particles with designed surface properties), nanoparticles have not only attracted great attentions from the oil and gas industry, but also had various applications from drilling and completion, reservoir characterization, to enhanced oil recovery (EOR). As sensors or EOR agents, thus, fate and behaviour of nanoparticles in porous media are essential and need to be investigated thoroughly. Nevertheless, most of the published review papers focus on particle transport in saturated porous media, and all of them are about steady-state flow conditions. So far, no attempts have been extended to systematically review current knowledge about nanoparticle transport in porous media with single-phase and two-phase flow systems under both steady-state and unsteady-state conditions. Accordingly, this review will discuss nanoparticle transport phenomena in porous media with its focus on the filtration mechanisms, the underlying interaction forces, and factors dominating nanoparticle transport behaviour in porous media. Finally, mathematical models used to describe nanoparticle transport in porous media for both single-phase flow and two-phase flow under steady-state and transient flow conditions will be summarized, respectively.

Journal ArticleDOI
TL;DR: In this paper, a unified weather research and forecasting (WRF) forecasting system called urban WRF-solar (uWRF-Solar) was proposed to forecast solar irradiance considerably well for the global horizontal irradiance (GHI) with an R2 value of 0.93 for clear sky conditions, 0.61 for cloudy sky conditions and finally,0.39 for overcast conditions.
Abstract: Recent developments in the weather research and forecasting (WRF) model have made it possible to accurately estimate incident solar radiation. This study couples the WRF-solar modifications with a multilayer urban canopy and building energy model (BEM) to create a unified WRF forecasting system called urban WRF–solar (uWRF-solar). This paper tests the integrated approach in the New York City (NYC) metro region as a sample case. Hourly forecasts are validated against ground station data collected at ten different sites in and around the city. Validation is carried out independently for clear, cloudy, and overcast sky conditions. Results indicate that the uWRF-solar model can forecast solar irradiance considerably well for the global horizontal irradiance (GHI) with an R2 value of 0.93 for clear sky conditions, 0.61 for cloudy sky conditions, and finally, 0.39 for overcast conditions. Results are further used to directly forecast solar power production in the region of interest, where evaluations of generation potential are done at the city scale. Outputs show a gradient of power generation produced by the potential available solar energy on the entire uWRF-solar grid. In total, the city has a city photovoltaic (PV) potential of 118 kWh/day/m2 and 3.65 MWh/month/m2.

Journal ArticleDOI
TL;DR: In this paper, the effect of CO2 as a diluent on the laminar burning speed of propane-CO2-air mixtures was examined in a cylindrical constant volume chamber with a Z-shaped Schlieren system, coupled with a high speed CMOS camera to capture the propagation of the flames at speeds up to 4000 frames per second.
Abstract: This experimental research examined the effect of CO2 as a diluent on the laminar burning speed of propane–air mixtures. Combustion took place at various CO2 concentrations (0–80%), different equivalence ratios (0.7<ϕ<1.2) and over a range of temperatures (298–420 K) and pressures (0.5–6.2 atm). The experiments were performed in a cylindrical constant volume chamber with a Z-shaped Schlieren system, coupled with a high-speed CMOS camera to capture the propagation of the flames at speeds up to 4000 frames per second. The flame stability of these mixtures at different pressures, equivalence ratios, and CO2 concentrations was also studied. Only laminar, spherical, and smooth flames were considered in measuring laminar burning speed. Pressure rise data as a function of time during the flame propagation were the primary input of the multishell thermodynamic model for measuring the laminar burning speed of propane-CO2-air mixtures. The laminar burning speed of such blends was observed to decrease with the addition of CO2 and to increase with the gas temperature. It was also noted that the laminar burning speed decreases with increasing pressure. The collected experimental data were compared with simulation data obtained via a steady one-dimensional (1D) laminar premixed flame code from Cantera, using a detailed H2/CO/C1–C4 kinetics model encompassing 111 species and 784 reactions.

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TL;DR: In this article, a pragmatic and consistent framework has been developed and validated to accurately predict reservoir performance in tight sandstone reservoirs by coupling the dynamic capillary pressure with gas production models.
Abstract: In this paper, a pragmatic and consistent framework has been developed and validated to accurately predict reservoir performance in tight sandstone reservoirs by coupling the dynamic capillary pressure with gas production models. Theoretically, the concept of pseudo-mobile water saturation, which is defined as the water saturation between irreducible water saturation and cutoff water saturation, is proposed to couple dynamic capillary pressure and stress-induced permeability to form an equation matrix that is solved by using the implicit pressure and explicit saturations (IMPES) method. Compared with the conventional methods, the newly developed model predicts a lower cumulative gas production but a higher reservoir pressure and a higher flowing bottomhole pressure at the end of the stable period. Physically, a higher gas production rate induces a greater dynamic capillary pressure, while both cutoff water saturation and stress-induced permeability impose a similar impact on the dynamic capillary pressure, though the corresponding degrees are varied. Due to the dynamic capillary pressure, pseudo-mobile water saturation controlled by the displacement pressure drop also affects the gas production. The higher the gas production rate is, the greater the effect of dynamic capillary pressure on the cumulative gas production, formation pressure, and flowing bottomhole pressure will be. By taking the dynamic capillary pressure into account, it can be more accurate to predict the performance of a gas reservoir and the length of stable production period, allowing for making more reasonable development schemes and thus improving the gas recovery in a tight sandstone reservoir.

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TL;DR: In this paper, a mathematical model of a multifractured horizontal well with considering segmented fracture (SF) for better evaluation of fracture and reservoir properties is presented, and the results of sensitivity analysis are benefit of parameter estimation during history matching.
Abstract: Nowadays, production performance evaluation of a multifractured horizontal well (MFHW) has attracted great attention. This paper presents a mathematical model of an MFHW with considering segmented fracture (SF) for better evaluation of fracture and reservoir properties. Each SF consists of two parts: fracture segment far from wellbore (FSFW) and fracture segment near to wellbore (FSNW) in segmented fracture model (SFM), which is different from fractures consists of only one segment in common fracture model (CFM). Employing the source function and Green's function, Newman's product method, Duhamel principle, Stehfest inversion algorithm, and Laplace transform, production solution of an MFHW can be obtained using SFM. Total production rate is mostly contributed from FSNW rather than FSFW in many cases; ignoring this phenomenon may lead to obvious erroneous in parameter interpretation. Thus, clear distinctions can be found between CFM and SFM on the compound type curves. By using decline curve analysis (DCA), the influences of sensitive parameters (e.g., dimensionless half-length, dimensionless production rate, conductivity, and distance between SF) on compound type curves are analyzed. The results of sensitivity analysis are benefit of parameter estimation during history matching.

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TL;DR: In this article, an innovative investigation of the nonroad modified diesel engine is reported with the effective use of the hybrid entropy-VIKOR approach, where the engine load, injection timing, injection pressure, and compression ratio were selected as engine operating parameters for experimentation at the constant speed of 1500 rpm engine.
Abstract: Excessive use of diesel engines and continuous increase in environmental pollution has drawn the attention of researchers in the area of the compression ignition engine. In this research article, an innovative investigation of the nonroad modified diesel engine is reported with the effective use of the hybrid Entropy-VIKOR approach. Hence, it becomes necessary to prioritize and optimize the performance defining criteria, which provides higher BTE along with lower emission simultaneously. The engine load, injection timing (Inj Tim), injection pressure (Inj Pre), and compression ratio (Com R) were selected as engine operating parameters for experimentation at the constant speed of 1500 rpm engine. The effect on engine performance parameters (BTE and BSEC) and emission (carbon monoxide (CO), total oxide of carbon (TOC), oxides of nitrogen (NOx), hydrocarbon (HC), and smoke) was studied experimentally. The optimum results were observed at load 10.32 kg, Inj Tim 20 deg btdc, Inj Pre 210 bar, and Com R 21:1 at which highest BTE of 22.24% and lowest BSEC of 16,188.5 kJ/kWh were obtained. Hybrid entropy-VIKOR approach was applied to establish the optimum ranking of the nonroad modified diesel engine. The experimental results and numerical simulation show that optimizing the engine operating parameters using the entropy-VIKOR multicriteria decision-making (MCDM) technique is applicable.

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TL;DR: In this article, the effects of interfacial tension, (IFT) permeability, oil viscosity, and the salinity of the imbibition fluid were determined, combining with nuclear magnetic resonance (NMR)-based core analysis.
Abstract: Fracturing is a fundamental technique for enhancing oil recovery of tight sandstone reservoir. The pores in tight reservoirs generally have small radii and generate tremendous capillary force; accordingly, the imbibition effect can significantly affect retention and absorption of the fracturing fluid. In this study, the imbibition behaviors of the fracturing fluid were experimentally investigated, and the effects of interfacial tension, (IFT) permeability, oil viscosity, and the salinity of the imbibition fluid were determined. In addition, combining with nuclear magnetic resonance (NMR)-based core analysis, fluid distribution, and the related variations in imbibition and displacement processes were analyzed. Finally, some key influencing factors of imbibition of the residual fracturing fluid, the difference and correlation between imbibition and displacement, as well as the contribution of imbibition to displacement were explored so as to provide optimization suggestions for guiding the application of oil-displacing fracturing fluid in exploration. Results show that imbibition recovery increased with time, but the imbibition rate gradually dropped. There exists an optimal interfacial tension that corresponds to maximum imbibition recovery. In addition, imbibition recovery increased as permeability and salinity increases and oil viscosity decreases. Furthermore, it was found that extracted oil from the movable pore throat space was almost equal to that from the irreducible pore throat space during imbibition and their contribution in the irreducible pore throat space was greater than in the movable pore throat space in the displacement process. Hence, imbibition plays a more important role during the displacement process in the reservoirs with finer porous structure than previously thought.

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TL;DR: In this article, three different blending ratios of 5, 25, and 50% of ethanol/iso-octane and 2,5 dimethyl furan (DMF) were investigated.
Abstract: Laminar burning speed and ignition delay time behavior of iso-octane at the presence of two different biofuels, ethanol and 2,5 dimethyl furan (DMF), was studied in this work. Biofuels are considered as a better alternative source of fossil fuels. There is a potentiality that combustion characteristics of iso-octane can be improved using biofuels as an oxygenated additive. In this study, three different blending ratios of 5%, 25%, and 50% of ethanol/iso-octane and DMF/iso-octane were investigated. For laminar burning speed calculation, equivalence ratio of 0.6–1.4 was considered. Ignition delay time was measured under temperature ranges from 650 K to 1100 K. Two different mechanisms were considered in numerical calculation. These mechanisms were validated by comparing the results of pure fuels with wide range of experimental and numerical data. The characteristic change of iso-octane with the presence of additives was observed by comparing the results with pure fuel. Significant change was observed on behavior of iso-octane at 50% blending ratio. A comparison was also done on the effect of two different additives. It has found that addition of DMF brings significant changes on iso-octane characteristics comparing to ethanol.

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TL;DR: In this article, a novel technique of low salinity hot water (LSHW) injection with addition of nanoparticles has been developed to examine the synergistic effects of thermal energy, LSHW flooding and nanoparticles for enhancing heavy oil recovery, while optimizing the operating parameters for such a hybrid enhanced oil recovery (EOR) method.
Abstract: In this study, a novel technique of low salinity hot water (LSHW) injection with addition of nanoparticles has been developed to examine the synergistic effects of thermal energy, low salinity water (LSW) flooding, and nanoparticles for enhancing heavy oil recovery, while optimizing the operating parameters for such a hybrid enhanced oil recovery (EOR) method. Experimentally, one-dimensional displacement experiments under different temperatures (17 °C, 45 °C, and 70 °C) and pressures (about 2000–4700 kPa) have been performed, while two types of nanoparticles (i.e., SiO2 and Al2O3) are, respectively, examined as the additive in the LSW. The performance of LSW injection with and without nanoparticles at various temperatures is evaluated, allowing optimization of the timing to initiate LSW injection. The corresponding initial oil saturation, production rate, water cut, ultimate oil recovery, and residual oil saturation profile after each flooding process are continuously monitored and measured under various operating conditions. Compared to conventional water injection, the LSW injection is found to effectively improve heavy oil recovery by 2.4–7.2% as an EOR technique in the presence of nanoparticles. Also, the addition of nanoparticles into the LSHW can promote synergistic effect of thermal energy, wettability alteration, and reduction of interfacial tension (IFT), which improves displacement efficiency and thus enhances oil recovery. It has been experimentally demonstrated that such LSHW injection with the addition of nanoparticles can be optimized to greatly improve oil recovery up to 40.2% in heavy oil reservoirs with low energy consumption. Theoretically, numerical simulation for the different flooding scenarios has been performed to capture the underlying recovery mechanisms by history matching the experimental measurements. It is observed from the tuned relative permeability curves that both LSW and the addition of nanoparticles in LSW are capable of altering the sand surface to more water wet, which confirms wettability alteration as an important EOR mechanism for the application of LSW and nanoparticles in heavy oil recovery in addition to IFT reduction.