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Abstract Lithofacies form the basis for evaluating shale gas fields and play an important role in gas reservoir enrichment. The accurate identification of shale lithofacies is key for exploration and development. Based on well‐logged data, the accuracy of mineral content prediction using machine‐learning regression models is not ideal. Therefore, feature derivation was introduced to enhance the correlation between minerals and lithofacies and improve the data expression ability. Four machine‐learning models for mineral regression were established based on feature‐derived data sets: LightGBM, XGBoost, artificial neural network, and support vector machine. By calculating the evaluation metrics of each model, we found that LightGBM had the best prediction performance. To compare and confirm the accuracy of the model in identifying lithofacies, this study established a new method, MT‐LightGBM, which combines the LightGBM mineral content regression model with mineral ternary diagrams to identify lithofacies. By using the MT‐LightGBM model and LightGBM classification models to identify the target lithofacies, it was found that the accuracy of lithofacies identification of MT‐LightGBM reached 94%. This accuracy is high and is of great significance for understanding and evaluating underground shale reservoirs.

Abstract With the rapid development of hydraulic fracturing technology, shale gas has become a significant natural gas resource in China. At present, SRV (stimulated reservoir volume) fracturing technology is widely used to exploit shale gas reservoirs. To evaluate the shale gas reserves and design a development plan, a simple and rapid method is needed to predict the production and performance of the multistage fractured horizontal wells with stimulated reservoir volume in shale gas reservoirs. Network fractures with different lengths and widths are not symmetrical to the horizontal well. To account for the complexity of the fracture system and desorption characteristics of shale gas, a semianalytical multiregion seepage model has been established to analyze the performance of multiple fractured horizontal wells. In this paper, a triple‐porosity dual‐permeability model is developed for simulating the flow mechanism of shale gas. Different lengths and widths of network fractures, different fracture intervals, and asymmetry distribution are considered in this model. By employing the principle of Poisson's superposition and Bessel transformation, the fundamental solution of instantaneous point source function has been derived to calculate the pressure response of each hydraulic fracture. Then, the mathematical model for unsteady performance evaluation in multiple fractured horizontal wells has been obtained to simultaneously solve the pressure response of every hydraulic fracture. The sensitivity analysis in terms of the lengths and widths of network fractures, fracture intervals, and the asymmetry distribution of a complex fracture system is presented. The research results show that the SRV morphology will exert a great influence on the performance of multiple fractured horizontal wells.

Triple-porosity model is usually adopted to describe reservoirs with multiscaled pore spaces, including matrix pores, natural fractures, and vugs. Multiple fractures created by hydraulic fracturing can effectively improve the connectivity between existing natural fractures and thus increase well deliverability. However, little work has been done on pressure transient behavior of multistage fractured horizontal wells in triple-porosity reservoirs. Based on source/sink function method, this paper presents a triple-porosity model to investigate the transient pressure dynamics and flux distribution for multistage fractured horizontal wells in fractured-vuggy reservoirs with consideration of stress-dependent natural fracture permeability. The model is semianalytically solved by discretizing hydraulic fractures and Pedrosa’s transformation, perturbation theory, and integration transformation method. Type curves of transient pressure dynamics are generated, and flux distribution among hydraulic fractures for a fractured horizontal well with constant production rate is also discussed. Parametric study shows that major influential parameters on transient pressure responses are parameters pertinent to reservoir properties, interporosity mass transfer, and hydraulic fractures. Analysis of flux distribution indicates that flux density gradually increases from the horizontal wellbore to fracture tips, and the flux contribution of outermost fractures is higher than that of inner fractures. The model can also be extended to optimize hydraulic fracture parameters.

Abstract To achieve next‐generation lithium metal batteries (LMBs) with desirable specific energy and reliability, the electrolyte shown simultaneously high reductive stability toward lithium metal anode and oxidative stability toward high‐voltage cathode is of great importance. Here, we report for the first time that high‐concentration lithium bis(fluorosulfonyl)imide (LiFSI) initiates ring‐opening polymerization of 1,3‐dioxolane in presence of ethylene carbonate and ethylmethyl carbonate to produce in‐situ a novel polymeric concentrated quasi‐solid electrolyte (poly‐CQSE). The unique poly‐CQSE with 10 M LiFSI forms a mixed‐lithiophobic‐conductive LiF‐Li3N solid electrolyte interphase on lithium metal anode, and a F‐rich conformal cathode electrolyte interphase on LiNi0.5Co0.2Mn0.3O2 (NCM523) cathode simultaneously. As a result, the poly‐CQSE not only enables stable Li plating/stripping of metallic Li anode at a sound Coulombic efficiency of 95.3% without dendrite growth, but also enables a stable cycling of the Li||NCM523 quasi‐solid‐state LMB at a capacity retention of 94% over 100 cycles.

To ensure safe exploitation of the Muduchaideng Mine, we use a numerical simulation to invert the in situ stress field based on observation data from GPS stations, investigate differences in movement velocities at different locations, and analyze the lefthanded movement in the area around the wellfield. The relationship between the difference in motion velocity and the in situ stress field was explained through theoretical analysis. The law of in situ stress distribution was studied using data collected from the surrounding mines, and a regression equation as well as the relationship between the magnitudes of the three-way stresses was obtained. The inversion results were consistent with the measured data, indicating that inversion of the in situ stress field was accurate under the conditions found in the intact Ordos block. Additionally, the influence of tectonic stress on the key layer was larger than that on the bedrock of the coal seam roof, and the energy accumulated in the key layer was higher. The stress concentration coefficient of the key layer was similar to the variation law of the coal seam thickness. Therefore, the southwest area of the wellfield with a thicker coal seam is the key area for impact ground pressure prevention and control.