Optimization of Gas Production from Hydrate-Bearing Sediments with Fluctuation Characteristics

As an important source of low-carbon,clean fossil energy,natural gas hydrate plays an important role in improving the global energy consumption structure.Developing the hydrate industry in the South China Sea is important to achieving‘carbon peak and carbon neutrality’goals as soon as possible.Deep-water areas subjected to the action of long-term stress and tectonic movement have developed complex and volatile terrains,and as such,the morphologies of hydrate-bearing sediments(HBSs)fluctuate correspondingly.The key to numerically simulating HBS morphologies is the establishment of the conceptual model,which represents the objective and real description of the actual geological body.However,current numerical simulation models have characterized HBSs into horizontal strata without considering the fluctuation characteristics.Simply representing the HBS as a horizontal element reduces simulation accuracy.Therefore,the commonly used horizontal HBS model and a model considering the HBS’s fluctuation characteristics with the data of the SH2 site in the Shenhu Sea area were first constructed in this paper.Then,their production behaviors were compared,and the huge impact of the fluctuation characteristics on HBS production was determined.On this basis,the key parameters affecting the depressurization production of the fluctuating HBSs were studied and optimized.The research results show that the fluctuation characteristics have an obvious influence on the hydrate production of HBSs by affecting their temperatures and pressure distributions,as well as the transmission of the pressure drop and methane gas discharge.Furthermore,the results show that the gas productivity of fluctuating HBSs was about 5%less than that of horizontal HBSs.By optimizing the depressurization amplitude,well length,and layout location of vertical wells,the productivity of fluctuating HBSs increased by about 56.6%.

Hydrocarbon gas huff-n-puff optimization of multiple horizontal wells with complex fracture networks in the M unconventional reservoir

The oil production of the multi-fractured horizontal wells(MFHWs) declines quickly in unconventional oil reservoirs due to the fast depletion of natural energy. Gas injection has been acknowledged as an effective method to improve oil recovery factor from unconventional oil reservoirs. Hydrocarbon gas huff-n-puff becomes preferable when the CO_(2) source is limited. However, the impact of complex fracture networks and well interference on the EOR performance of multiple MFHWs is still unclear. The optimal gas huff-n-puff parameters are significant for enhancing oil recovery. This work aims to optimize the hydrocarbon gas injection and production parameters for multiple MFHWs with complex fracture networks in unconventional oil reservoirs. Firstly, the numerical model based on unstructured grids is developed to characterize the complex fracture networks and capture the dynamic fracture features.Secondly, the PVT phase behavior simulation was carried out to provide the fluid model for numerical simulation. Thirdly, the optimal parameters for hydrocarbon gas huff-n-puff were obtained. Finally, the dominant factors of hydrocarbon gas huff-n-puff under complex fracture networks are obtained by fuzzy mathematical method. Results reveal that the current pressure of hydrocarbon gas injection can achieve miscible displacement. The optimal injection and production parameters are obtained by single-factor analysis to analyze the effect of individual parameter. Gas injection time is the dominant factor of hydrocarbon gas huff-n-puff in unconventional oil reservoirs with complex fracture networks. This work can offer engineers guidance for hydrocarbon gas huff-n-puff of multiple MFHWs considering the complex fracture networks.

Optimization method of refracturing timing for old shale gas wells

Based on the elastic theory of porous media,embedded discrete fracture model and finite volume method,and considering the micro-seepage mechanism of shale gas,a fully coupled seepage-geomechanical model suitable for fractured shale gas reservoirs is established,the optimization method of refracturing timing is proposed,and the influencing factors of refracturing timing are analyzed based on the data from shale gas well in Fuling of Sichuan Basin.The results show that due to the depletion of formation pressure,the percentage of the maximum horizontal principal stress reversal area in the total area increases and then decreases with time.The closer the area is to the hydraulic fracture,the shorter the time for the peak of the stress reversal area percentage curve to appear,and the shorter the time for the final zero return(to the initial state).The optimum time of refracturing is affected by matrix permeability,initial stress difference and natural fracture approach angle.The larger the matrix permeability and initial stress difference is,the shorter the time for stress reversal area percentage curve to reach peak and return to the initial state,and the earlier the time to take refracturing measures.The larger the natural fracture approach angle is,the more difficult it is for stress reversal to occur near the fracture,and the earlier the optimum refracturing time is.The more likely the stress reversal occurs at the far end of the artificial fracture,the later the optimal time of refracturing is.Reservoirs with low matrix permeability have a rapid decrease in single well productivity.To ensure economic efficiency,measures such as shut-in or gas injection can be taken to restore the stress,and refracturing can be implemented in advance.

Horizontal well spacing optimization and gas injection simulation for the ultra-low-permeability Yongjin reservoir

Optimal spacing for vertical wells can be effectively predicted with several published methods,but methods suitable for assessing the proper horizontal well spacing are rare.This work proposes a method for calculating the optimal horizontal well spacing for an ultra-low permeability reservoir e the Yongjin reservoir in the Juggar Basin,northwestern China.The result shows that a spacing of 640m is the most economical for the development of the reservoir.To better develop the reservoir,simulation approaches are used and a new model is built based on the calculated well spacing.Since the reservoir has an ultralow permeability,gas injection is regarded as the preferred enhanced oil recovery(EOR)method.Injection of different gases including carbon dioxide,methane,nitrogen and mixed gas are modelled.The results show that carbon dioxide injection is the most efficient and economical for the development of the reservoir.However,if the reservoir produces enough methane,reinjecting methane is even better than injecting carbon dioxide.

Optimization of Gas-Flooding Fracturing Development in Ultra-Low Permeability Reservoirs

Ultra-low permeability reservoirs are characterized by small pore throats and poor physical properties, which areat the root of well-known problems related to injection and production. In this study, a gas injection floodingapproach is analyzed in the framework of numerical simulations. In particular, the sequence and timing of fracturechanneling and the related impact on production are considered for horizontal wells with different fracturemorphologies. Useful data and information are provided about the regulation of gas channeling and possible strategiesto delay gas channeling and optimize the gas injection volume and fracture parameters. It is shown that inorder to mitigate gas channeling and ensure high production, fracture length on the sides can be controlled andlonger fractures can be created in the middle by which full gas flooding is obtained at the fracture location in themiddle of the horizontal well. A Differential Evolution (DE) algorithm is provided by which the gas injectionvolume and the fracture parameters of gas injection flooding can be optimized. It is shown that an improvedoil recovery factor as high as 6% can be obtained.

Desulfurization characteristics of slaked lime and regulation optimization of circulating fluidized bed flue gas desulfurization process--A combined experimental and numerical simulation study

Circulating fluidized bed flue gas desulfurization(CFB-FGD) process has been widely applied in recent years. However, high cost caused by the use of high-quality slaked lime and difficult operation due to the complex flow field are two issues which have received great attention. Accordingly, a laboratory-scale fluidized bed reactor was constructed to investigate the effects of physical properties and external conditions on desulfurization performance of slaked lime, and the conclusions were tried out in an industrial-scale CFB-FGD tower. After that, a numerical model of the tower was established based on computational particle fluid dynamics(CPFD) and two-film theory. After comparison and validation with actual operation data, the effects of operating parameters on gas-solid distribution and desulfurization characteristics were investigated. The results of experiments and industrial trials showed that the use of slaked lime with a calcium hydroxide content of approximately 80% and particle size greater than 40 μm could significantly reduce the cost of desulfurizer. Simulation results showed that the flow field in the desulfurization tower was skewed under the influence of circulating ash. We obtained optimal operating conditions of 7.5 kg·s^(-1)for the atomized water flow, 70 kg·s^(-1)for circulating ash flow, and 0.56 kg·s^(-1)for slaked lime flow, with desulfurization efficiency reaching 98.19% and the exit flue gas meeting the ultraclean emission and safety requirements. All parameters selected in the simulation were based on engineering examples and had certain application reference significance.

Optimization of the Gas Generator in Composite Power System with Tip-Jet Rotor

The key and bottleneck of research on the tip-jet rotor compound helicopter lies in the power system. Computational Fluid Dynamics (CFD) was used to numerically simulate the gas generator and rotor inner passage of the tip-jet rotor composite power system, studying the effects of intake mode, inner cavity structure, propellant components, and injection amount on the characteristics of the composite power system. The results show that when a single high-temperature exhaust gas enters, the gas generator outlet fluid is uneven and asymmetric;when two-way high-temperature exhaust gas enters, the outlet temperature of the gas generator with a tilted inlet is more uniform than that with a vertical inlet;adding an inner cavity improves the temperature and velocity distribution of the gas generator's internal flow field;increasing the energy of the propellant is beneficial for improving the available moment.

Power optimization of gas pipelines via an improved particle swarm optimization algorithm

In past decades dynamic programming, genetic algorithms, ant colony optimization algorithms and some gradient algorithms have been applied to power optimization of gas pipelines. In this paper a power optimization model for gas pipelines is developed and an improved particle swarm optimization algorithm is applied. Based on the testing of the parameters involved in the algorithm which need to be defined artificially, the values of these parameters have been recommended which can make the algorithm reach efficiently the approximate optimum solution with required accuracy. Some examples have shown that the relative error of the particle swarm optimization over ant colony optimization and dynamic programming is less than 1% and the computation time is much less than that of ant colony optimization and dynamic programming.

Optimization of pulsed current gas tungsten arc welding process parameters to attain maximum tensile strength in AZ31B magnesium alloy

An empirical relationship to predict tensile strength of pulsed current gas tungsten arc welded AZ31B magnesium alloy was developed. Incorporating process parameters such as peak current, base current, pulse frequency and pulse on time were studied. The experiments were conducted based on a four-factor, five-level, central composite design matrix. The developed empirical relationship can be effectively used to predict the tensile strength of pulsed current gas tungsten arc welded AZ31B magnesium alloy joints at 95% confidence level. The results indicate that pulse frequency has the greatest influence on tensile strength, followed by peak current, pulse on time and base current.

Optimization of shale gas reservoir evaluation and assessment of shale gas resources in the Oriente Basin in Ecuador

The petroleum geological features of hydrocarbon source rocks in the Oriente Basin in Ecuador are studied in detail to determine the potential of shale gas resources in the basin. The favorable shale gas layer in the vertical direction is optimized by combining logging identification and comprehensive geological analysis. The thickness in this layer is obtained by logging interpretation in the basin. The favorable shale gas accumulation area is selected by referring to thickness and depth data. Furthermore, the shale gas resource amount of the layer in the favorable area is calculated using the analogy method. Results show that among the five potential hydrocarbon source rocks, the lower Napo Formation is the most likely shale gas layer. The west and northwest zones, which are in the deep-sea slope and shelf sedimentary environments, respectively, are the favorable areas for shale gas accumulation. The favorable sedimentary environment formed thick black shale that is rich in organic matter. The black shale generated hydrocarbon, which migrated laterally to the eastern shallow water shelf to form numerous oil fields. The result of the shale gas resource in the two favorable areas,as calculated by the analogy method, is 55,500×10;m;. This finding shows the high exploration and development potential of shale gas in the basin.

Research on low carbon emission optimization operation technology of natural gas pipeline under multi-energy structure

In order to reduce the carbon emissions of natural gas pipelines,based on the background of different energy structures,this paper proposes a general low carbon and low consumption operation model of natural gas pipelines,which is used to fine calculate the carbon emissions and energy consumption of natural gas pipeline.In this paper,an improved particle swarm optimization(NHPSO-JTVAC)algorithm is used to solve the model and the optimal scheduling scheme is given.Taking a parallel pipeline located in western China as an example,the case is analyzed.The results show that after optimization,under the existing energy types,the pipeline system can reduce 31.14%of carbon emissions,and after introducing part of new energy,the pipeline system can reduce 34.02%of carbon emissions,but the energy consumption has increased.

Hybrid data-driven framework for shale gas production performance analysis via game theory, machine learning, and optimization approaches

A comprehensive and precise analysis of shale gas production performance is crucial for evaluating resource potential,designing a field development plan,and making investment decisions.However,quantitative analysis can be challenging because production performance is dominated by the complex interaction among a series of geological and engineering factors.In fact,each factor can be viewed as a player who makes cooperative contributions to the production payoff within the constraints of physical laws and models.Inspired by the idea,we propose a hybrid data-driven analysis framework in this study,where the contributions of dominant factors are quantitatively evaluated,the productions are precisely forecasted,and the development optimization suggestions are comprehensively generated.More specifically,game theory and machine learning models are coupled to determine the dominating geological and engineering factors.The Shapley value with definite physical meaning is employed to quantitatively measure the effects of individual factors.A multi-model-fused stacked model is trained for production forecast,which provides the basis for derivative-free optimization algorithms to optimize the development plan.The complete workflow is validated with actual production data collected from the Fuling shale gas field,Sichuan Basin,China.The validation results show that the proposed procedure can draw rigorous conclusions with quantified evidence and thereby provide specific and reliable suggestions for development plan optimization.Comparing with traditional and experience-based approaches,the hybrid data-driven procedure is advanced in terms of both efficiency and accuracy.

Ensemble-based optimization of hydraulically fractured horizontal well placement in shale gas reservoir through Hough transform parameterization

Shale gas reservoirs have been successfully developed due to the advancement of the horizontal well drilling and multistage hydraulic fracturing techniques.However,the optimization design of the horizontal well drilling,hydraulic fracturing,and operational schedule is a challenging problem.An ensemble-based optimization method(EnOpt)is proposed here to optimize the design of the hydraulically fractured horizontal well in the shale gas reservoir.The objective is to maximize the net present value(NPV)which requires a simulation model to predict the cumulative shale gas production.To accurately describe the geometry of the hydraulic fractures,the embedded discrete fracture modeling method(EDFM)is used to construct the shale gas simulation model.The efects of gas absorption,Knudsen difusion,natural and hydraulic fractures,and gas-water two phase fow are considered in the shale gas production system.To improve the parameter continuity and Gaussianity required by the EnOpt method,the Hough transformation parameterization is used to characterize the horizontal well.The results show that the proposed method can efectively optimize the design parameters of the hydraulically fractured horizontal well,and the NPV can be improved greatly after optimization so that the design parameters can approach to their optimal values.

Interpretable machine learning optimization(InterOpt)for operational parameters:A case study of highly-efficient shale gas development

An algorithm named InterOpt for optimizing operational parameters is proposed based on interpretable machine learning,and is demonstrated via optimization of shale gas development.InterOpt consists of three parts:a neural network is used to construct an emulator of the actual drilling and hydraulic fracturing process in the vector space(i.e.,virtual environment);:the Sharpley value method in inter-pretable machine learning is applied to analyzing the impact of geological and operational parameters in each well(i.e.,single well feature impact analysis):and ensemble randomized maximum likelihood(EnRML)is conducted to optimize the operational parameters to comprehensively improve the efficiency of shale gas development and reduce the average cost.In the experiment,InterOpt provides different drilling and fracturing plans for each well according to its specific geological conditions,and finally achieves an average cost reduction of 9.7%for a case study with 104 wells.

Flow-Optimization to Enhance Gas Quenching Efficiency for Helical Gears Specimen

Numerical simulations based on a conjugate heat transfer solver have been carried out to analyze various gas quenching configurations involving a helical gear streamed by an air flow at atmospheric pressure in a gas quenching chamber. In order to optimize the heat transfer coefficient distribution at key positions on the specimen, configurations involving layers of gears and flow ducts comprising single to multiple gears have been simulated and compared to standard batch configurations in gas quenching. Measurements have been performed covering the local heat transfer for single gears and batch of gears. The homogeneity of the heat transfer coefficient is improved when setting up a minimal distance between the gears (batch density) and when introducing flow ducts increasing the blocking grade around the gears. An offset between layers of the batch as well as flow channels around the gears plays a significant role in increasing the intensity and the homogeneity of the heat transfer in gas quenching process.

Two-stage robust optimization of power cost minimization problem in gunbarrel natural gas networks by approximate dynamic programming

In short-term operation of natural gas network,the impact of demand uncertainty is not negligible.To address this issue we propose a two-stage robust model for power cost minimization problem in gunbarrel natural gas networks.The demands between pipelines and compressor stations are uncertain with a budget parameter,since it is unlikely that all the uncertain demands reach the maximal deviation simultaneously.During solving the two-stage robust model we encounter a bilevel problem which is challenging to solve.We formulate it as a multi-dimensional dynamic programming problem and propose approximate dynamic programming methods to accelerate the calculation.Numerical results based on real network in China show that we obtain a speed gain of 7 times faster in average without compromising optimality compared with original dynamic programming algorithm.Numerical results also verify the advantage of robust model compared with deterministic model when facing uncertainties.These findings offer short-term operation methods for gunbarrel natural gas network management to handle with uncertainties.

Design and optimization of exhaust gas aftertreatment system for a heavy-duty diesel engine

Diesel engines meeting the latest emission regulations must be equipped with exhaust gas aftertreatment system,including diesel oxidation catalysts(DOC),diesel particulate filters(DPF),and selective catalytic reduction(SCR).However,before the final integration of the aftertreatment system(DOC+DPF+SCR)and the diesel engine,a reasonable structural optimization of the catalytic converters and a large number of bench calibration tests must be completed,involving large costs and long development cycles.The design and optimization of the exhaust gas aftertreatment system for a heavy-duty diesel engine was proposed in this paper.Firstly,one-dimensional(1D)and threedimensional(3D)computational models of the exhaust gas aftertreatment system accounting for the structural parameters of the catalytic converters were established.Then based on the calibrated models,the effects of the converter’s structural parameters on their main performance indicators,including the conversion of various exhaust pollutants and the temperatures and pressure drops of the converters,were studied.Finally,the optimal design scheme was obtained.The temperature distribution of the solid substrates and pressure distributions of the catalytic converters were studied based on the 3D model.The method proposed in this paper has guiding significance for the optimization of diesel engine aftertreatment systems.

Physics Analysis and Optimization Studies for a Fusion Neutron Source Based on a Gas Dynamic Trap

To further investigate the fusion neutron source based on a gas dynamic trap （GDT）, characteristics of the GDT were analyzed and physics analyses were made for a fusion neutron source based on the GDT concept. The prior design of a GDT-based fusion neutron source was optimized based on a refreshed understanding of GDT operation. A two-step progressive development route of a GDT-based fusion neutron source was suggested. Potential applications of GDT are discussed. Preliminary analyses show that a fusion neutron source based on the GDT concept is suitable for plasma-material interaction research, fusion material and subcomponent testing, and capable of driving a proof-of-principle fusion fission hybrid experimental facility.

Optimization of Gas Sensing Performance of Nanocrystalline SnO_2 Thin Films Synthesized by Magnetron Sputtering

Tin oxide （SnO2） is one of the most promising transparent conducting oxide materials, which is widely used in thin film gas sensors. We investigate the dependence of the deposition time on structural, morphologicaJ and hydrogen gas sensing properties of SnO2 thin films synthesized by dc magnetron sputtering. The deposited samples are characterized by XRD, SEM, AFM, surface area measurements and surface profiler. Also the H2 gas sensing properties of SnO2 deposited samples are performed against a wide range of operating temperature. The XRD analysis demonstrates that the degree of crystallinity of the deposited SnO2 films strongly depends on the deposition time. SEM and AFM analyses reveal that the size of nanoparticles or agglomerates, and both average and rms surface roughness is enhanced with the increasing deposition time. Also gas sensors based on these SnO2 nanolayers show an acceptable response to hydrogen at various operating temperatures.

Comparison of Optimization Schemes for the Flue Gas Purification System of a Garbage Incineration Power Plant

A garbage incineration power plant is proposed to be built somewhere. Due to local environmental capacity and local policy,the demand on the flue gas emission indicators of the project is high,but the conventional purification process of flue gas produced during waste incineration（ SNCR denitrification ＋dry/semi-dry deacidification ＋ adsorption of dioxins and heavy metals by activated carbon ＋ bag dusting） has been unable to meet this requirement,and the newly added wet deacidification and SCR denitrification processes can meet this requirement. The flue gas purification process was optimized,and two feasible schemes were compared to choose the better one.