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Research Papers

J. Energy Resour. Technol. 2018;141(4):041001-041001-11. doi:10.1115/1.4041724.

Diffusion coefficient of carbon dioxide (CO2), a significant parameter describing the mass transfer process, exerts a profound influence on the safety of CO2 storage in depleted reservoirs, saline aquifers, and marine ecosystems. However, experimental determination of diffusion coefficient in CO2-brine system is time-consuming and complex because the procedure requires sophisticated laboratory equipment and reasonable interpretation methods. To facilitate the acquisition of more accurate values, an intelligent model, termed MKSVM-GA, is developed using a hybrid technique of support vector machine (SVM), mixed kernels (MK), and genetic algorithm (GA). Confirmed by the statistical evaluation indicators, our proposed model exhibits excellent performance with high accuracy and strong robustness in a wide range of temperatures (273–473.15 K), pressures (0.1–49.3 MPa), and viscosities (0.139–1.950 mPa·s). Our results show that the proposed model is more applicable than the artificial neural network (ANN) model at this sample size, which is superior to four commonly used traditional empirical correlations. The technique presented in this study can provide a fast and precise prediction of CO2 diffusivity in brine at reservoir conditions for the engineering design and the technical risk assessment during the process of CO2 injection.

Commentary by Dr. Valentin Fuster

Research Papers: Energy Systems Analysis

J. Energy Resour. Technol. 2018;141(4):042001-042001-9. doi:10.1115/1.4041842.

Fluid flow inside heterogeneous structure of dual porosity reservoirs is presented by two coupled partial differential equations (PDE). Finding an analytical solution for the diffusivity equations is tedious or even impossible in some circumstances due to the heterogeneity of dual porosity reservoirs. Therefore, in this study, orthogonal collocation method (OCM) is proposed for solving the governing equations in dual porosity reservoirs with constant pressure outer boundary. Since no analytical solution has been proposed for this system, validation is carried out by comparing the OCM-obtained results for “dual porosity reservoirs with circular no-flow outer boundary” with both exact analytical solution and real field data. Sensitivity analyses reveal that the OCM with 13 collocation points is a good candidate for prediction of pressure transient response (PTR) in dual porosity reservoirs. OCM predicts the PTR of a real field draw-down test with an absolute average relative deviation (AARD) of 0.9%. Moreover, OCM shows a good agreement with the analytical solution obtained by Laplace transform (AARD = 0.16%). It is worth noting that OCM requires a smaller computational effort. Thereafter, PTR of dual porosity reservoirs with a constant production rate in the wellbore and constant pressure outer boundary is simulated by OCM for wide ranges of operating conditions. Accuracy of OCM and its low required computational time justifies that this approximate method can be considered as a practical candidate for pressure transient analysis in dual porosity reservoirs.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(4):042002-042002-12. doi:10.1115/1.4042003.

This work presents a theoretical thermodynamic study of a compression–absorption cascade refrigeration system using R134a and a lithium bromide–water solution as working fluids. First and second law of thermodynamics analyses were carried out in order to develop an advanced exergetic analysis, by splitting the total irreversibility and that of every component. The potential for improvement of the system is quantified, in the illustrated base-case 55.4% of the irreversibility is of avoidable nature and it could be reduced. The evaporator is the component that shows a significant potential for improvement, followed by the cascade heat exchanger, the compressor, and finally, the generator. The results of the advanced exergetic analysis can be very useful for future design and experimentation of these kinds of systems.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(4):042003-042003-8. doi:10.1115/1.4042004.

Climatic change illustrates the need to new policy of load management. In this research, a special design of thermal energy storage (TES) system, with an appropriate storage medium that is suitable for residential and commercial buildings has been constructed and commissioned. Direct contact heat transfer is a significant factor to enhance the performance of TES. Numerous experimental runs were conducted to investigate the clathrate formation and the characteristics of the proposed TES cooling system; in addition, the effect of using nanofluid particles Al2O3 on the formation of clathrate under different operating parameters was evaluated. The experiments were conducted with a fixed amount of water 15 kg, mass of refrigerant to form clathrate of 6.5 kg, nanofluid particles concentration ranged from 0.5% to 2% and the mass flux of refrigerant varied from 150 to 300 kg/m2 s. The results indicate that there is a significant effect of using nanoparticles concentration on the charging time of the clathrate formation. The percentage of reduction in charging time of about 22% was achieved for high nanoparticles concentration. In addition, an enhancement in charging time by increasing the refrigerant flow rate reaches 38% when the mass flux varied from 200 to 400 kg/m2 s. New correlation describing the behavior of the temperatures with the charging time at different nanoparticles concentrations is presented.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(4):042004-042004-13. doi:10.1115/1.4041898.

This paper reports the comprehensive thermodynamic modeling of a modified combustion gas turbine plant where Brayton refrigeration cycle was employed for inlet air cooling along with evaporative after cooling. Exergetic evaluation was combined with the emission computation to ascertain the effects of operating variables like extraction pressure ratio, extracted mass rate, turbine inlet temperature (TIT), ambient relative humidity, and mass of injected water on the thermo-environmental performance of the gas turbine cycle. Investigation of the proposed gas turbine cycle revealed an exergetic output of 33%, compared to 29% for base case. Proposed modification in basic gas turbine shows a drastic reduction in cycle's exergy loss from 24% to 3% with a considerable decrease in the percentage of local irreversibility of the compressor from 5% to 3% along with a rise in combustion irreversibility from 19% to 21%. The environmental advantage of adding evaporative after cooling to gas turbine cycle along with inlet air cooling can be seen from the significant reduction of NOx from 40 g/kg of fuel to 1 × 10−9 g/kg of fuel with the moderate increase of CO concentration from 36 g/kg of fuel to 99 g/kg of fuel when the fuel–air equivalence ratio reduces from 1.0 to 0.3. Emission assessment further reveals that the increase in ambient relative humidity from 20% to 80% causes a considerable reduction in NOx concentration from 9.5 to 5.8 g/kg of fuel while showing a negligible raise in CO concentration from 4.4 to 5.0 g/kg of fuel.

Commentary by Dr. Valentin Fuster

Research Papers: Fuel Combustion

J. Energy Resour. Technol. 2018;141(4):042201-042201-8. doi:10.1115/1.4041841.

This work highlights the ability of the computational singular perturbation (CSP) method to calculate the significant indices of the modes on evolution of species and the degree of participation of reactions. The exploitation of these indices allows us to deduce the reduced models of detailed mechanisms having the same physicochemical properties. The mechanism used is 16 species and 41 reversible reactions. A reduction of these 41 reactions to 22 reactions is made. A constant pressure application of the detailed and reduced mechanism is made in OpenFOAM free and open source code. Following the Reynolds-averaged Navier–Stokes simulation scheme, standard k–ε and partial stirred reactor are used as turbulence and combustion models, respectively. To validate the reduced mechanism, comparison of numerical results (temperature and mass fractions of the species) was done between the detailed mechanism and the simplified model. This was done using the DVODE integrator in perfectly stirred reactor. After simulation in the computational fluid code dynamic (CFD) OpenFOAM, other comparisons were made. These comparisons were between the experimental data of a turbulent nonpremixed diffusion flame of type “DLR-A flame,” the reduced mechanism, and the detailed mechanism. The calculation time using the simplified model is considerably reduced compared to that using the detailed mechanism. An excellent agreement has been observed between these two mechanisms, indicating that the reduced mechanism can reproduce very well the same result as the detailed mechanism. The accordance with experimental results is also good.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(4):042202-042202-7. doi:10.1115/1.4041725.

Nitromethane is extensively used in drag races and in glow plug unmanned aerial vehicle (UAV) engines. However, it has not been analyzed in the combustion literature enough. Nitromethane has a low stoichiometric air–fuel ratio; it can be blended with gasoline and used in larger quantities to enhance the power output of the internal combustion (IC) engines. This could find potential use in burgeoning UAV industry. The present investigation aims at experimentally determining the laminar burning speeds of nitromethane—gasoline blends at different equivalence ratios. Tests were conducted at both ambient conditions and at elevated temperatures and pressures. A constant volume combustion chamber (CVCC) was constructed and instrumented to carry out the investigation. The pressure rise in the chamber due to combustion was acquired and analyzed to determine the laminar burning speeds. The results showed that with an increase in the nitromethane concentration in gasoline, the laminar burning speeds for all the initial conditions also increased. With the rise in initial temperatures, the laminar burning speeds were observed to increase. However, a drop was observed with a rise in the initial pressures for all the blends. The obtained results for pure gasoline were compared with existing literature. A good match was observed. The investigation also aims at providing vital experimental data, which can be used for computational fluid dynamics validation studies later.

Commentary by Dr. Valentin Fuster

Research Papers: Petroleum Engineering

J. Energy Resour. Technol. 2018;141(4):042901-042901-16. doi:10.1115/1.4041839.

In order to lessen the computational time in fractured oil reservoir simulations, all fractures are usually assumed to be as one equivalent fracture at the center or around the model. This, specially, has applications in industrial engineering software, where this assumption applies. In this study, using two general contradictory examples, it is shown that ignoring a fracture network and assuming an equivalent single-fracture has no logical justification and results in a considerable error. The effect of fracture aperture on composition distribution of a binary and a ternary mixture was also investigated. These mixtures were C1 (methane)/n-C4 (normal-butane) and C1 (methane)/C2 (ethane)/n-C4 (normal-butane), which were under diffusion and natural convection. Governing equations were numerically solved using matlab. One of the main relevant applications of this study is where permeability and temperature gradient are the key difference between reservoirs. Compositional distribution from this study could be used to estimate initial oil in place. Using this study, one can find the optimum permeability, namely the permeability at which the maximum species separation happens, and the threshold permeability (or fracture aperture), after which the convection imposes its effect on composition distribution. It is found that the threshold permeability is not constant from reservoir to reservoir. Also, one can find that full mixing happens in the model, namely heavy and light densities of top and bottom mix up together in the model. Furthermore, after maximum separation point, convection causes unification of components.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(4):042902-042902-9. doi:10.1115/1.4041843.

The rheological properties of bentonite suspensions depend on the chemical composition and the contained dominant element, such as calcium (Ca), potassium (K), and sodium (Na). Na-bentonite type is the one used in drilling fluids, because it has good dispersion stability, high swelling capacity, and outstanding rheological properties. Ca-bentonite generally has bad rheological performance; however, it can be activated by sodium to be used in drilling fluids, since there are huge unutilized Ca-bentonite resources. Many previous attempts of activation of Ca-bentonite were not feasible, upgrading required addition of many extra additives or sometimes mixed with commercial Na-bentonite to improve its properties. In this paper, a process of integrated beneficiation method is designed to efficiently remove the nonclay impurities and produce pure Ca-bentonite. An upgraded Ca-bentonite was produced using a combined thermochemical treatment in a wet process by adding 4 wt % of soda ash (Na2CO3) while heating and stirring. The new thermal treatment optimized and described in this study greatly improved the sodium activation and ions exchange process and improved bentonite properties. The thermochemically upgraded Ca-bentonite outperformed the rheological properties of the commercial bentonite. And when tested in a typical drilling fluid formulation at high temperature, the investigations showed an identical behavior of the commercial drilling grade bentonite. Moreover, the results obtained showed that the thermochemically upgraded Ca-bentonite has higher yield point/plastic viscosity (YP/PV) ratio than commercial Na-bentonite when mixed with the drilling fluid additives. Higher YP/PV ratio is expected to enhance the hole cleaning and prevent most of the drilling problems.

Commentary by Dr. Valentin Fuster
J. Energy Resour. Technol. 2018;141(4):042903-042903-9. doi:10.1115/1.4041840.

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.

Commentary by Dr. Valentin Fuster


J. Energy Resour. Technol. 2018;141(4):045501-045501-4. doi:10.1115/1.4041844.

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.

Commentary by Dr. Valentin Fuster

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