Review Article

J. Energy Resour. Technol. 2018;141(3):030801-030801-18. doi:10.1115/1.4041096.

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.

Commentary by Dr. Valentin Fuster

Research Papers: Alternative Energy Sources

J. Energy Resour. Technol. 2018;141(3):031201-031201-7. doi:10.1115/1.4041612.

Wind power is one of the most popular renewable energy sources (RES), characterized by rapid growth of installed power in the energy mix of many countries. Usually, the influence of wind technologies on the depletion of nonrenewable resources is evaluated taking into account the consumption of energy and materials in the construction phase. However, it should be noted that the major drawback of wind energy is its random availability which also influences the consumption of resources. This consumption results from the necessity of compensation for random operation of wind power plants by conventional ones operating in off-design point. In the present work, thermo-ecological cost (TEC) is proposed for the evaluation of the performance of wind generation systems operating with random accessibility of wind energy. The presented analysis focuses on the estimation of additional non-renewable energy consumption due to the part-load operation of the conventional power units. Different strategies are assumed for the compensation for the hourly wind power variations. The presented results of TEC analysis show that the part of TEC resulting from induced losses can be significant. The authors prove that, within the assessment of wind turbines, the induced losses cannot be omitted.

Commentary by Dr. Valentin Fuster

Research Papers: Energy From Biomass

J. Energy Resour. Technol. 2018;141(3):031801-031801-10. doi:10.1115/1.4041723.

Considering the potential of using concentrating solar power systems to supply the heat required for the allothermal gasification process, this study analyzes hydrogen production in such a system by assuming typical radiative heat flux profiles for a receiver of a central tower concentrated solar power (CSP) plant. A detailed model for allothermal gasification in a downdraft fixed bed tubular reactor is proposed. This considers solid and gas phases traveling in parallel flow along the reactor. Results for temperature and gas profile show a reasonable quantitative agreement with experimental works carried out under similar conditions. Aiming to maximize H2 yield, eight Gaussian flux distributions, similar to those typical of CSP systems, each with a total power of 8 kW (average heat flux 20 kW/m2), but with varying peak locations, were analyzed. The results show a maximum producer gas yield and a chemical efficiency of 134.1 kmol/h and 45.9% respectively, with a molar concentration of 47.2% CO, 46.9% H2, 3.3% CH4, and 2.6% CO2 for a distribution peak at z = 1.4 m, thus relatively close to the flue gas outlet. Hydrogen production and gas yield using this configuration were 4% and 2.9% higher than the achieved using the same power but homogeneously distributed. Solar to chemical efficiencies ranged from 38.9% to 45.9%, with a minimum when distribution peak was at the reactor center. These results are due to high temperatures during the latter stage of the process favoring char gasification reactions.

Commentary by Dr. Valentin Fuster

Research Papers: Energy Systems Analysis

J. Energy Resour. Technol. 2018;141(3):032001-032001-8. doi:10.1115/1.4041092.

In this paper, the hydrodynamic flow inside an internally circulating fluidized bed (ICFBG) was characterized using experimental and three-dimensional computational fluid dynamics (CFD) models. Eulerian-Eulerian model (EEM) incorporating the kinetic theory of granular flow was implemented in order to simulate the gas–solid flow. A full-scale plexiglass cold flow experimental model was built to verify simulation results prior to the fabrication of the gasifier. Six parameters were manipulated to achieve the optimum design geometry: fluidization flow rate of the draft tube (Qdt), aeration flow rate of the annulus (Qan), initial bed static height (Hbs), draft tube height (Hdt), draft tube diameter (Ddt), and orifice diameter (Dor). The investigated parameters showed strong effect on the particle flow characteristics in terms of the pressure difference (ΔP) and solid circulation rate (Gs). The predicted results by simulation for the optimum case were in close agreement with experimental measurements with about 5% deviation. The results show that the ICFBG operated stably with the maximum Gs value of 86.6 kg/h at Qdt of 350 LPM, Qan of 150 LPM, Hbs of 280 mm, Hdt of 320 mm, Ddt of 100 mm, and Dor of 20 mm.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032002-032002-15. doi:10.1115/1.4041663.

High temperature that reaches to 50 °C in summer, high humidity, and dust storms are considered as the main characteristics of the climate of many countries around the world such as those in the Gulf States, Asia, and Africa. According to the latest studies, air conditioning (A/C) systems in the residential areas used around 65% of the generated energy. This paper is aimed at presenting a new residential thermal model that can be used to estimate the energy consumption of A/C units used to achieve comfort in houses. The results of the newly developed residential thermal model will be compared with exiting residential thermal models using simscape in matlab program and data measurements. Different physical properties of the house that affect the heat gains through the house envelop at different weather conditions, and the internal heat gains are taken into account in this study. Hourly, daily, monthly, and annually energy consumption and coefficient of performance (COP) are calculated, based on actual hourly outdoor temperature measurements and indoor generation heat for the year 2017, using the three thermal models and compared with the pertinent actual measurements. The total measured energy consumption for nine months' work in 2017 was 14488.09 kWh, and the total energy consumption predicted by the simulation for the simple model, intermediate model, and comprehensive model were 8438.40 kWh, 12656.10 kWh, and 13900.61 kWh, respectively, with deviations of 41.75%, 12.65%, and 4.05%, respectively, from the actual measurements.

Commentary by Dr. Valentin Fuster

Research Papers: Fuel Combustion

J. Energy Resour. Technol. 2018;141(3):032201-032201-6. doi:10.1115/1.4041106.

In the present study, a comprehensive mathematical method is developed to realize the flame expansion in the melting furnace zones. For this purpose, the furnace is composed of two zones: flame and post flame zones. Two different scenarios are covered in this research: Using lycopodium as a substitute fuel which is then converted to methane after the vaporization process, supplying the system with methane directly as a conventional fuel. The equations governing the problem with the required boundary conditions are developed and solved in each zone. The obtained results show great compatibility with the experimental findings in this research. Since lycopodium as the replacement fuel mostly contains volatile materials, one of the challenges in this study lies on understanding the effect of particle vaporization on the temperature distribution in a furnace. It is concluded that the average temperature in zones α1, α2, β1, and β2, is reduced by about 5 K, while it is increased by approximately the same amount in zones χ1, χ2, δ1, and δ2 after considering lycopodium as a fuel. Moreover, the role of vaporization and radiation on the combustion characteristics is studied in details. The achieved results from this analysis can be implemented in several industrial applications aiming for improving the energy efficiency outcome from their systems.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032202-032202-8. doi:10.1115/1.4041095.

Biogas is a renewable source of energy produced by anaerobic digestion of organic material and composed mainly of methane (CH4) and carbon dioxide (CO2). Despite its lower heating value, biogas can still replace fossil fuels in several engineering stationary power generation and other industrial applications. Although numerous published studies were devoted to advance our understating of biogas combustion, experimental data of some parameters such as turbulent burning velocity (St) under certain operating conditions is still lacking. The present study aims to experimentally determine biogas turbulent burning velocity under normal temperature and pressure conditions. Turbulent premixed biogas–air flame was ignited at the center of a 29 L fan-stirred spherical combustion chamber of nearly homogeneous and isotropic turbulence. Test conditions consisted of varying turbulence intensity and biogas surrogate composition. Outwardly propagating biogas flames were tracked and imaged using Schlieren imaging technique. The results showed that, by increasing turbulence and reducing methane percentage in the surrogate, the flammability of the mixture shrinked. In addition, the curve fits of biogas turbulent burning velocity versus the equivalence ratio exhibited two different trends. The peak of turbulent burning velocity shifted away from nearly lean equivalence ratio toward the stoichiometric at a fixed turbulence intensity and higher CH4 percentage in the surrogate. However, for the same biogas surrogate composition, the peak of turbulent burning velocity shifted away from stoichiometric toward leaner equivalence ratio with increased turbulence intensity.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032203-032203-8. doi:10.1115/1.4041411.

This paper presents lubricating oil performance in a compression ignition (CI) engine fueled with a binary fuel blend of 70% aamla seed oil biodiesel and 30% eucalyptus oil (EU) on volume basis. This blended fuel was stable and congruent with engine-fuel system. Initially, the engine was operated with normal diesel fuel as per standard endurance test. The same endurance test was performed with the above binary biodiesel blended fuel in the engine under somewhat modified engine operational condition. The lubricating oil was examined at a specified interval to evaluate the impact of the fuel on lubricating oil properties. Quantification of various metal debris concentrations was carried out using inductive coupled plasma atomic emission spectroscopy. After experimentation, the lubricating oil samples were analyzed using analytical ferrography that showed lower wear debris concentrations from binary biodiesel blend than diesel fuel operated engine. The better lubricating property of binary biodiesel blended fuel resulted in lower wear and improved performance of engine parts. Relatively low wear and concentrations of all metal wear were found in the lubricating oil with binary biodiesel blended fuel engine revealed better performance of engine with this fuel blend. No technical problem was encountered during the long-term endurance tests with the binary biodiesel blended fuel under modified engine parameters.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032204-032204-11. doi:10.1115/1.4041545.

The results obtained on wear assessment from a compression ignition (CI) engine fueled with a blend of 70% amla seed biodiesel (AB) and 30% eucalyptus oil (EU) on volume basis (called AB70EU30). The results showed stable engine operation and good operability of the engine-fuel system with the binary biodiesel fuel blend. The feasibility of this blend over a long-term endurance tests was explored. The specific assessment examination included the fate of cylinder head, pump plunger, injector nozzle, and piston crown, which affects the engine performance and engine life. The experimental results revealed better tribological performance characteristics with the binary fuel blend as compared to contemporary diesel fuel. No specific problem was encountered during the long-term endurance tests with the binary fuel blend using the modified engine parameters. The results show that the binary fuel mixture offers good potential for use as diesel fuel in CI engines while maintaining good performance and endurance.

Commentary by Dr. Valentin Fuster

Research Papers: Natural Gas Technology

J. Energy Resour. Technol. 2018;141(3):032701-032701-10. doi:10.1115/1.4041413.

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.

Commentary by Dr. Valentin Fuster

Research Papers: Oil/Gas Reservoirs

J. Energy Resour. Technol. 2018;141(3):032801-032801-12. doi:10.1115/1.4041662.

In our previous study, a series of experiments had been conducted by applying different pressure depletion rates in a 1 m long sand-pack. In this study, numerical simulation models are built to simulate the lab tests, for both gas/oil production data and pressure distribution along the sand-pack in heavy oil/methane system. Two different simulation models are used: (1) equilibrium black oil model with two sets of gas/oil relative permeability curves; (2) a four-component nonequilibrium kinetic model. Good matching results on production data are obtained by applying black oil model. However, this black oil model cannot be used to match pressure distribution along the sand-pack. This result suggests the description of foamy oil behavior by applying equilibrium black oil model is incomplete. For better characterization, a four-component nonequilibrium kinetic model is developed aiming to match production data and pressure distribution simultaneously. Two reactions are applied in the simulation to capture gas bubbles status. Good matching results for production data and pressure distribution are simultaneously obtained by considering low gas relative permeability and kinetic reactions. Simulation studies indicate that higher pressure drop rate would cause stronger foamy oil flow, but the exceed pressure drop rate could shorten lifetime of foamy oil flow. This work is the first study to match production data and pressure distribution and provides a methodology to characterize foamy oil flow behavior in porous media for a heavy oil/methane system.

Commentary by Dr. Valentin Fuster

Research Papers: Petroleum Engineering

J. Energy Resour. Technol. 2018;141(3):032901-032901-11. doi:10.1115/1.4040073.

Compressor stations in natural gas networks should perform such that time-varying demands of customers are fulfilled while all of the system constraints are satisfied. Power consumption of compressor stations impose the most operational cost to a gas network so their optimal performance will lead to significant money saving. In this paper, the gas network transient optimization problem is addressed. The objective function is the sum of the compressor's power consumption that should be minimized where compressor speeds and the value status are decision variables. This objective function is nonlinear which is subjected to nonlinear and combinatorial constraints including both discrete and continuous variables. To handle this challenging optimization problem, a novel approach based on using two different structure intelligent algorithms, namely the particle swarm optimization (PSO) and cultural algorithm (CA), is utilized to find the optimum of the decision variables. This approach removes the necessity of finding an explicit expression for the power consumption of compressors as a function of decision variables as well as the calculation of objective function derivatives. The objective function and constraints are evaluated in the transient condition by a fully implicit finite difference numerical method. The proposed approach is applied on a real gas network where simulation results confirm its accuracy and efficiency.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032902-032902-10. doi:10.1115/1.4041094.

In this work, an oil-soluble surfactant was studied to enhance crude oil mobilization in a cryolite-packed miniature bed. The cryolite packed bed provided a transparent, random porous medium for observation at the microscopic level. In the first part of the paper, oil-soluble surfactants, Span 80 and Eni-surfactant (ES), were dissolved directly into the crude oil. The porous medium was imbued with the crude oil (containing the surfactants), and de-ionized water was the flooding phase; in this experiment, the system containing ES had the best performance. Subsequently, sodium dodecyl sulfate (SDS), a hydrosoluble surfactant, was used to solubilize the ES, with the SDS acting as a carrier for the ES to the contaminated porous media. Finally, the SDS/ES micellar solutions were used in oil-removal tests on the packed bed. Grayscale image analysis was used to quantify the oil recovery effectiveness for the flooding experiments by measuring the white pixel percentage in the packed bed images. The SDS/ES flooding mixture had a better performance than the SDS alone.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032903-032903-9. doi:10.1115/1.4041525.

Wax deposition is an extremely common occurrence affecting flow assurance in oil fields. Under the laminar flow condition, the effect of the flow rate on wax deposition is still unclear. In this study, a flow loop test was conducted by considering the depletion effect to investigate the flow effect on wax deposition in single-phase laminar flow. The measured data were compared with the estimated data using models (wax deposition, hydrodynamic, and heat transfer models). The data obtained from the models were matched with the measured data; thus, thereby model parameters were tuned and the wax deposit thickness along the pipeline was estimated with respect to flow rate. The study results indicate that the wax deposit thickness decreases when the flow rate increases at the thickest spot (TS). The volume of wax deposits increases when the flow rate increases. An increase in the flow rate increases the distance between the inlet and the location of the TS.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032904-032904-8. doi:10.1115/1.4041155.

Axial excitation tools (AETs) have the ability to improve slide-drilling efficiency by reducing the friction between the drillstring and the wellbore wall. However, drag-reduction effects are not always satisfactory, and excessive vibration may cause failures of downhole tools in some cases. Thus, a mathematical model was proposed to simulate the vibration responses of a drillstring. In the model, velocity-dependent friction is adopted to calculate the friction-reduction effect. The effect of drillstring joints on the weight on bit (WOB) was first investigated. The simulation results indicate that the joints intensify the stick-slip motion of the drillstring system. The effect of the location of an AET was then examined. The results show that it is better to place an AET near the drill bit rather than near the rear of a build section. Because the frictional drag acting on the lower portion of the drillstring dominates the axial stick-slip motion of a drill bit. Finally, the resonance responses were examined in terms of the drillstring system acceleration. The results show that resonance moderately increases the accelerations of a long horizontal drillstring system in a heavy-damping environment but that the growth of the exciting force can profoundly increase the accelerations.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032905-032905-9. doi:10.1115/1.4041661.

Oil–water dispersed flow occurs commonly in the petroleum industry during the production and transportation of crudes. Phase inversion occurs when the dispersed phase grows into the continuous phase and the continuous phase becomes the dispersed phase caused by changes in the composition, interfacial properties, and other factors. Production equipment, such as pumps and chokes, generates shear in oil–water mixture flow, which has a strong effect on phase inversion phenomena. The objective of this paper is to investigate the effects of shear intensity and water cut (WC) on the phase inversion region and also the droplet size distribution. A state-of-the-art closed-loop two phase (oil–water) flow facility including a multipass gear pump and a differential dielectric sensor (DDS) is used to identify the phase inversion region. Also, the facility utilizes an in-line droplet size analyzer (a high speed camera), to record real-time videos of oil–water emulsion to determine the droplet size distribution. The experimental data for phase inversion confirm that as shear intensity increases, the phase inversion occurs at relatively higher dispersed phase fractions. Also the data show that oil-in-water emulsion requires larger dispersed phase volumetric fraction for phase inversion as compared with that of water-in-oil emulsion under the same shear intensity conditions. Experiments for droplet size distribution confirm that larger droplets are obtained for the water continuous phase, and increasing the dispersed phase volume fraction leads to the creation of larger droplets.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(3):032906-032906-10. doi:10.1115/1.4041613.

Determination of optimal well locations plays an important role in the efficient recovery of hydrocarbon resources. However, it is a challenging and complex task. The objective of this paper is to determine the optimal well locations in a heavy oil reservoir under production using a novel recovery process in which steam is generated, in situ, using thermochemical reactions. Self-adaptive differential evolution (SaDE) and particle swarm optimization (PSO) methods are used as the global optimizer to find the optimal configuration of wells that will yield the highest net present value (NPV). This is the first known application, where SaDE and PSO methods are used to optimize well locations in a heavy oil reservoir that is recovered by injecting steam generated in situ using thermo-chemical reactions. Comparison analysis between the two proposed optimization techniques is introduced. On the other hand, laboratory experiments were performed to confirm the heavy oil production by thermochemical means. CMG STARS simulator is utilized to simulate reservoir models with different well configurations. The experimental results showed that thermochemicals, such as ammonium chloride along with sodium nitrate, can be used to generate in situ thermal energy, which efficiently reduces heavy-oil viscosity. Comparison of results is made between the NPV achieved by the well configuration proposed by the SaDE and PSO methods. The results showed that the optimization using SaDE resulted in 15% increase in the NPV compared to that of the PSO after 10 years of production under in situ steam injection process using thermochemical reactions.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2019;141(3):032907-032907-12. doi:10.1115/1.4042232.

In the transportation process of oil and gas, solid particle erosion in pipelines is an inevitable problem. The erosion usually occurs in fittings with changing flow directions, such as elbows. A theoretical model based on mechanism analyses is developed for predicting the solid particle erosion on the symmetry plane of elbows for annular flow. This model is a sort of generalized erosion prediction procedure, which resolves the erosion process into the description of the flow field velocity profile, particle motion rules, and penetration calculation. The 1/7th power law is adopted to represent the velocity profile of gas core, and a linear velocity profile is assigned to the liquid film. The trajectories of particles in the gas core and the liquid film are discretized, and a mathematical model is developed by analyzing external forces acting on particles. The impact speeds and angles of particles can be obtained from the mathematical model, and the penetration ratios are then estimated by incorporating the impingement information of particles into the erosion formulas. By contrast with experimental data, the mechanistic model is validated and indicates advantages in both accuracy and efficiency. Furthermore, the effects of different parameters on penetration ratios are discussed in detail, including the superficial gas velocity, superficial liquid velocity, pipe diameter, particle diameter, curvature radius, and liquid viscosity.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2019;141(3):032908-032908-9. doi:10.1115/1.4042233.

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.

Commentary by Dr. Valentin Fuster

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