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The identification of shale lithology is of great importance for the exploration and development of shale reservoirs. The lithology and mineralogical composition of shale are closely related, but a small number of laboratory core analysis samples are insufficient to evaluate the lithology of the entire formation. In this study, a lithology identification method using conventional logging curves is proposed for the shale stratigraphy of the Qingshankou Formation in the Gulong Depression of the Songliao Basin, northeastern China. First, a mineral pre-training model is constructed using discrete petrophysical experimental data with logging data, and features are generated for the logging data. Second, an adaptive multi-objective swarm crossover optimization method is employed to address the imbalance of logging data. Finally, the model is combined with a Bayesian gradient boosting algorithm for lithology identification. The proposed method demonstrates superior performance to eXtreme Gradient Boosting, Support Vector Machines, Multilayer Perceptron, and Random Forest in terms of accuracy, weight perspective, and macro perspective evaluation indexes. The method has been successfully applied in actual wells, with excellent results. The results indicate that the workflow is a reliable means of shale lithology identification.

The Central Asian Orogenic Belt (CAOB) is the world's largest accretionary orogenic belt, and its formation is related to the closure of the Paleo-Asian Ocean (PAO). However, the closure time and style of the PAO remain controversial. To address these issues, this paper presents zircon U-Pb dating, whole-rock geochemistry and zircon Lu-Hf isotope analyses of the volcanic rocks in the Faku-Kaiyuan area on the northern margin of the North China Craton. The results show that the Bachagou andesites formed in the Early Permian (287 ± 2 Ma), while the Chaijialing andesites and dacites formed in the Late Permian (253.3 ± 3.7 Ma) and Middle Triassic (244.3 ± 1.3 Ma), respectively. The Bachagou andesites and Chaijialing andesites are enriched in LILEs and LREEs and depleted in HFSEs and HREEs, indicating that they formed in the active continental margins. The Chaijialing dacites show similar geochemical signatures to adakite and formed in a syn-collisional setting. Geochemistry and isotopic analysis indicates that the Bachagou andesites were derived from a partial melting of the mantle wedge that was metasomatized by subduction fluids. The Chaijialing andesites were generated from a metasomatized mantle by slab-derived and sediment fluids. The Chaijialing dacites formed by a partial melting of thickened lower crust. Combined with previous research results, we can conclude that the Eastern PAO closed by a scissor-like movement from west to east during the Late Permian–Middle Triassic. [ABSTRACT FROM AUTHOR]

The energy consumption and carbon footprint of cryptocurrencies have always been a popular topic. However, most of the existing studies only focus on one cryptocurrency, Bitcoin, and there is a lack of long-term monitoring studies that summarize all cryptocurrencies. By constructing a time series hash rate/power model, this research obtained the 10-year time series data on energy consumption dataset of global top-25 cryptocurrencies for the first time. Both the temporal coverage and the spatiotemporal resolution of the data exceed previous studies. The results show that Bitcoin's power consumption only accounts for 58% of the top-25 cryptocurrencies. After China bans cryptocurrencies, the conservative change in global CO2 emissions from 2020 will be between −0.4% and 4.4%, and Central Asian countries such as Kazakhstan are likely to become areas of rapid growth in carbon emissions from cryptocurrencies. [ABSTRACT FROM AUTHOR]