Topochemical heat in-situ pyrolysis of oil shale is achieved by injecting high temperature nitrogen to promote oil shale pyrolysis and release heat, and then injecting air to trigger oil shale combustion in the early stage of oil shale pyrolysis, and then by injecting normal temperature air continuously to promote local oxidation of oil shale in the later stage. In order to verify the oil and gas recovery by topochemical heat method, Jilin University has chosen Fuyu City, Jilin Province, to carry out pilot project of oil shale in-situ pyrolysis by topochemical heat method. Besides, in order to infer the spontaneity, feasibility and difficulty of continuous pyrolysis of oil shale based on topochemical heat, this paper, the mechanism of solid-state pyrolysis and the thermodynamic analysis of transition state of oil shale in Fuyu area are discussed. Because the second stage of oil shale pyrolysis is the main stage of oil production. Therefore, the characteristics of Gibbs free energy, free enthalpy and free entropy of transition state in the main oil production stage of oil shale pyrolysis are obtained by calculation. The results show that in situ pyrolysis of oil shale topochemical heat can be carried out spontaneously and continuously, and the release characteristics of volatiles during pyrolysis of oil shale are described.

Capacity fade in lithium-ion batteries (LIBs) poses challenges for various industries. Predicting and preventing this fade is crucial, and hybrid methods for estimating remaining useful life (RUL) have become prevalent and achieved significant advancements. In this paper, we introduce a hybrid voting ensemble that combines Gradient Boosting, Random Forest, and K-Nearest Neighbors to forecast the fading capacity trend and knee point. We conducted extensive experiments using the CALCE CS2 datasets. The results indicate that our proposed approach outperforms single deep learning methods for RUL prediction and accurately identifies the knee point. Beyond prediction, this innovative method can potentially be integrated into real-world applications for broader use.

In this paper, the effect of heat injection on productivity of Fuyu oil shale during in-situ pyrolysis was studied by using heat flow coupling analysis method. It is found that fluid conducts heat transmission to the oil shale stratum mainly along the fissure formed by hydraulic fracturing. With the increase of heating time, the oil shale on both sides of fissures were effectively pyrolyzed, and the porosity of the formation increases and the diffusion range of the nitrogen to the oil shale stratum is also improved. After 200 days, the oil shale around the fractures first reaches the pyrolysis temperature, and 700 days later, the average temperature of the oil shale stratum reaches 500 °C; therefore, the whole oil shale can be effectively pyrolyzed. Productivity analysis shows that the best exploitation temperature is 500 °C. When the gas injection rate is in the range of 1.0~11.0 m³/min, different degrees of heat loss will occur, and the output is also different. The pyrolysis time reaches 100~150 days, showing the peak value of daily production, which is between 0.5~3.2 m³/day. The pressure of displacement fluid affects oil shale product recovery in in-situ pyrolysis. High pressure helps to improve the displacement efficiency of oil and gas products and increase the productivity of oil shale in-situ pyrolysis. The best acting pressure is 9.5 MPa.

In the realm of lithium-ion batteries (LIBs), issues like material aging and capacity decline contribute to performance degradation or potential safety hazards. Predicting remaining useful life (RUL) serves as a crucial method of assessing the health of batteries, thereby enhancing reliability and safety. To reduce the complexity and improve the accuracy and applicability of early RUL predictions for LIBs, we proposed a Mamba-based state space model for early RUL prediction. Due to the impacts of abnormal data, we first use the interquartile range (IQR) method with a sliding window for data cleansing. Subsequently, the top three highest correlated features are selected, and only the first 300 cycling data are used for training. The model has the ability to make forecasts using these few historical data. Extensive experiments are conducted using CALCE CS2 datasets. The MAE, RMSE, and RE are less than 0.015, 0.019, and 0.0261; meanwhile, $R^2$ is higher than 0.99. Compared to the baseline approaches (CNN, BiLSTM, and CNN-BiLSTM), the average MAE, RMSE, and RE of the proposed approach are reduced by at least 29%, 21%, and 36%, respectively. According to the experimental results, the proposed approach performs better in terms of accuracy, robustness, and efficiency.

The compactness of the oil shale reservoir and the complexity of the pore structure lead to the secondary reaction of kerogen in the process of hydrocarbon expulsion, which reduces the effective recovery of shale oil. In this paper, supercritical carbon dioxide was used as a heat carrier and a displacement medium. In a self-designed fluidized bed experimental system for pressure-controlled pyrolysis of oil shale, the experiments of oil shale pyrolysis under standard atmospheric pressure and 7.8-8.0 MPa pressure in nitrogen and carbon dioxide atmospheres were completed. The extraction efficiency of supercritical carbon dioxide at low temperature is obvious, but with the increase of temperature, the effect of extraction on pyrolysis is lower than that of temperature. Under a nitrogen atmosphere, the secondary reaction of shale oil is mainly secondary pyrolysis and aromatization. However, in a supercritical carbon dioxide atmosphere, the main reactions are secondary addition and aromatization. In addition, compared with that in the standard atmospheric pressure, it was found that the olefin synthesis reaction was obviously inhibited under a high-pressure nitrogen or supercritical carbon dioxide atmosphere.