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To determine the best CO2 injection and brine production strategy for achieving both the optimal water production and the optimal CO2 storage capacity while maintaining operational safety in CO2 enhanced brine production, three injection scenarios based on the typical geological parameters of the Junggar Basin in China are compared. They are the sole CO2 injection, sole water production and combined CO2 enhanced water recovery, and for the combined CO2 enhanced water recovery scenario, both the co-production of brine and pre-production of brine are considered. It is found that compared to the pre-production of brine, the combination of pre- and co-production of brine can be more effective in controlling the pressure perturbation and in increasing the CO2 storage capacity. However the volume of co-produced brine plays a smaller role in the pressure build-up. The influence of number of pumping wells is also analyzed. Although increasing the number of wells can enhance the CO2 storage, the economic analysis reveals that the revenue in water production and CO2 storage cannot compensate the expensive investment required in well drilling. The injection strategy is essential to the efficiency of CO2 enhanced water recovery; this paper compares the strategies for pre-production and co-production of brine on CO2 enhanced shale gas recovery. The conclusions given in this paper can serve as a reference for the design engineers interested in CO2 storage with co-production of brine.

Carbon dioxide geological sequestration simultaneously combined with water production from deep saline aquifer can effectively address the challenge faced by modern energy systems of reducing carbon dioxide emissions and water intensity while providing reliable, affordable, and secure energy. However, little attention has been paid to date in the literature on determining the carbon dioxide injection strategy for achieving both the optimal water production and the optimal carbon dioxide storage capacity while maintaining operational safety. This paper first establishes three injection–extraction scenarios based on the typical geological parameters of the Junggar Basin in China to analyze the effect of carbon dioxide injection on water extraction and the effect of water extraction on the carbon dioxide storage. The three injection scenarios considered are sole carbon dioxide injection, sole water production and combined carbon dioxide enhanced water recovery. The carbon dioxide enhanced water recovery scenario is then optimized using a genetic algorithm to determine the trade-off between the maximum possible water recovery and the safe carbon dioxide storage for both the constant mass injection and the variable time-dependent mass injection (for achieving constant pressure injection). The influence of number of pumping wells is also analyzed. It can be concluded from this work that the carbon dioxide enhanced water recovery technology can effectively manage the pressure perturbation caused by the carbon dioxide injection as well as the water production while significantly enhancing the carbon dioxide storage capacity, security and water production efficiency. Injection strategy is essential to the efficiency of carbon dioxide enhanced water recovery; the genetic algorithm based optimizer combined with the well-known multi-phase flow solver TOUGH2, designated as GA-TOUGH2 is used for the optimization of injection scenarios. It is found that in the allowable range of pressure perturbations, a higher carbon dioxide injection rate is more beneficial for carbon dioxide storage as well as for water production. Constant pressure injection operation is superior to the constant rate injection and leads to higher carbon dioxide storage capacity and stability, and water production efficiency. Adding pumping wells can somewhat enhance the carbon dioxide storage capacity especially for the constant pressure injection operation compared to the constant rate injection operation as well as the water production efficiency; however, the enhancement in water production is very small compared to the single well and cannot be regarded as economical considering the additional capital cost of well drilling. This paper addresses the method of combined numerical simulation and optimization for carbon dioxide enhanced water recovery from saline aquifers that can be employed in the implementation of enhanced water recovery at industrial scale.

How to minimize the emission of air pollutants while making decisions about mitigating climate change has become a hot research topic. Considering the homologous homology of the two types of emissions, it is completely feasible to achieve synergistic control for different pollutants through a rational allocation of technology investment. To attain this goal, in this paper, I propose a pollutant synergistic control model. Carbon and sulfur emissions are chose as the major control object. Under a weak condition, I obtained analytical expressions for two types of cleaner technology investment paths, technology capital accumulation paths, and emission reduction paths. Further, characteristics of the respective paths, and the conditions for meeting the corresponding theoretical inflection points or peaks, were analyzed, which lays a foundation for applications of the theory. In particular, this study draws the necessary and sufficient conditions for an internal solution to the choice of cleaner technology, which is a powerful and practical evaluation index. The theoretical predictions were verified with numerical simulation. The investment of the two types of cleaner technologies peaked during the 10th period, and the capital accumulation peaked during 15th period after a slight delay. The actual measured investment and subsidy feedback gains were around the 0.04 and 0.02 levels. In addition, different combinations of targets for sulfur and carbon reduction also simulated scenarios in which the model had different internal solutions. The relevant theoretical exploration work in this paper has deep implications for policy decisions in the real world.

This paper presents a hybrid process combine micro reciprocated wire-EDM which uses reciprocated travelling wire with 50 μm diameter as tool electrode, with the precision forging, achieving the economical and high-efficiency sustainable production of micro gears. A micro gear mold with 0.1 mm module and 10 tooth number is devised, and the 14.5 μm mold fit clearance is determined by analyzing the established mold matching model and conducting the numerical simulation of precision forging. During the micro reciprocated wire-EDM of micro gear mold from SKD11, the basic experiments are performed to study the effect of the main parameters on machining accuracy and productivity, and whilst the proper machining parameters are obtained. The micro gear punch and die are successfully fabricated by micro reciprocated wire-EDM, showing good surface quality with 0.90 μm and 0.83 μm Ra respectively, and low dimensional deviations of ≤1.3 μm and 2.1 μm respectively. Finally, the precision forging of the micro gears are conducted on ultrafine grained (UFG) high purity copper by the machined micro gear mold. The forged micro gears have high forming precision with ≤4.1 μm deviation from the micro gear mold and smooth surface with 0.86 μm copied from the micro gear die cavity, verifying the feasibility of the proposed method for the sustainable production of micro gears.

Ground control is an integral element of mine design and worker safety. The use of concrete pillars for underground mines is of paramount importance to maintaining the economic and operational security of structures. This paper deals with the use of fiber-reinforced concrete (FRC) as pillars via laboratory and field tests. The strength performance of prepared concrete reinforced with glass, polypropylene and polyacrylonitrile fibers was researched by a mechanical press and a computed tomography (CT) tool. Samples were tested for fiber volume fractions of 0, 0.4, 0.8 and 1.2 wt%, respectively. Results have indicated that, with the addition of fibers, the strength was improved first due to a bridging effect and then decreased due to a pull-out effect. Compared to the reference sample, the absorbed energy prevents FRC from deterioration by mechanisms of matrix cracking, fiber-matrix interface debonding and fiber rupture. The peak strains of FRC linearly rise with increasing fiber. The gray value distribution curves have also good correspondence with 2D CT pore and crack distributions, which reveal that gray value processing could depict the structural behavior of concretes reinforced with or without fiber. Theoretical analyses show that the pillar remains stable for sustainable mining. Besides, the location and size of FRC pillars are suitable for numerical calculations of the trial stope. The findings of this study can offer a key reference for the orebody pillar recovery in underground mines.

On Sep 26, 2015, an expressway tunnel through Chaoyang mountain of Qingdao China collapsed during construction. Fortunately, no victims were identified in this disaster. In order to ensure construction safety and realize the purpose of environmental protection and clean production, this paper investigated the collapse factors of the shallow tunnel by simulation and field measurement. In view of the key factors, a method combined with support and grouting was proposed to deal with the tunnel collapse accident. It shows that the main factors affecting the stability of the surrounding rock are excavation cycles, excavation section width, interval time from excavation to support, concrete strength and arch spacing. The numerical simulation results show that the tunnel with side-wall-support is more stable than that without side-wall-support to surrounding rock deformation, and the support is the key factor. After using this method, the percentage decrease of the settlement rate is 86.18%, and the percentage decrease of the convergence rate is 87.35%. This method is an effective method maintaining the stability of surrounding rock above the tunnel.

This paper presents a machine learning assisted computational workflow to optimize a CO2-WAG project considering both hydrocarbon recovery and CO2 sequestration efficacies. A compositional field-scaled numerical simulation model is structured to investigate the fluid flow dynamics of an on-going CO2-EOR project in the Farnsworth Unit (Texas, US). Artificial-neural-network (ANN) based proxy models are trained to predict time-series project responses including hydrocarbon production, CO2 storage and reservoir pressure data. The outputs of the proxy model not only serve for evaluating the objective function but also provide significant physical and economic constraints to the optimization processes. In this work, the objective function considers both the oil recovery and CO2 sequestration volume. Moreover, the project net present values (NPV) and reservoir pressure are employed to screen the optimum solutions. The proposed optimization workflow couples the Particle Swarm Optimization (PSO) algorithm and the ANN proxies to maximize the prescribed objective function. The results of this work indicate that the presented workflow is a more robust approach to co-optimize the CO2-EOR projects. Results show that the optimized case can store about 94% of the purchased CO2 within Farnsworth Unit. Comparing to the baseline case, the CO2 storage amount of the found optimal case increases by 21.69%, and the oil production improves 8.74%. More importantly, the improvements in CO2 storage and hydrocarbon recovery lead to 8.74% greater project NPV and 19.79% higher overall objective function value, which confirms the success of the developed co-optimization approach for CO2 sequestration and oil recovery. The lessons and experiences earned from this work provides significant insights into the decision-making process of similar CO2-EOR cases.