During the Late Ordovician period, changes in climate and mass extinctions were observed; however, the factors influencing these phenomena have not been fully understood. In order to understand the relationships among redox water conditions, climates, and mass extinctions in the Late Ordovician, this study analyzes the chemical index of alteration (CIA) in shales and ⁸⁷Sr/⁸⁶Sr in carbonate leachates as proxies of changes in chemical weathering intensity and chemical weathering rate in the Late Ordovician (mainly from Katian to Hirnantian). The results show that an enhanced chemical weathering rate (increased ⁸⁷Sr/⁸⁶Sr ratios) and decreased chemical weathering intensity (decreased CIA values) characterized the late Katian, which might be attributed to the global orogenesis and enhanced precipitation/runoff under the warming climate (late-Boda warming). This enhanced chemical weathering rate contributed to the CO₂ drawdown in the P. pacificus biozone, corresponding to the initiation of cooling and further glaciation. Meanwhile, the enhanced weathering-induced high primary productivity could have contributed to the expansion of anoxic seawater in the Katian, which further caused the Katian extinction. The Hirnantian Glaciation was characterized by high ⁸⁷Sr/⁸⁶Sr ratios in carbonates and extremely low CIA values in shales, which were likely related to the exposure of continents during low sea level and the glacial grinding of unweathered rocks. This study shows that the highest denudation rate and lowest chemical weathering intensity in the Hirnantian stage might have resulted in enhanced CO₂ release and contributed to the end of glaciation.

The deeply buried Upper Ediacaran Qigebrak Formation dolostones in the Tarim Basin are promising future hydrocarbon exploration targets in China. However, the origin of these pervasive matrix dolomites is not well understood, which hampers further hydrocarbon exploration. In this study, petrographic, isotopic (C, O, and Sr), rare earth element (REE), and clumped isotope analyses were performed to unravel the mechanisms of early dolomitization. Petrographic investigations indicate that the Qigebrak Formation carbonates were completely replaced by three distinct types of dolomites: (1) dolomicrite (MD-1), (2) fabric-preserving dolomite (MD-2), and (3) fabric-destructive dolomite (MD-3). Despite different crystal textures, these three dolomite types have a narrow range of δ¹³C and ⁸⁷Sr/⁸⁶Sr values similar to those of coeval seawater. Furthermore, their seawater-normalized REE compositions display a seawater-like REE pattern with positive Ce anomalies. These findings suggest that the dolomitization fluids were seawater derived. From the clumped isotope temperature (T_Δ47 ≈ 60 °C) and the δ¹⁸O water values of the dolomitization fluids, it can be inferred that the main mechanism for the formation of matrix dolomites was seepage-reflux dolomitization by mesosaline to penesaline seawater in the evaporative environment. MD-1 and MD-2 precipitated from mesosaline to penesaline seawater in slightly evaporated settings. MD-3 was likely formed via recrystallization of MD-1 and/or MD-2 at a greater depth. This study provides an insight into early dolomitization processes related to mesosaline to penesaline seawater, which may make the origins of dolomite reservoirs with similar geological backgrounds better understood.

In order to meet the needs of geologists for the analysis of data characterizing field outcrops (rock sections or formations exposed on the ground surface), this study developed a field digital outcrop visualization platform based on Cesium (a 3D geospatial visualization technology) digital outcrop characterization technology. The platform was developed based on WebGL (a protocol for rendering interactions on web pages), which overcame the shortcomings of traditional software in terms of visualization, cross-device, cross-platform, and ease of use. Firstly, UAV inclined photography is used for data collection, which transforms a large amount of geological data into an intuitive 3D geological model, while the visualization platform provides rich measurement and mapping tools for the identified features, which more intuitively displays the outcrop information, helps geological explorers to understand the geological conditions in the field more quickly and comprehensively, and improves the analysis efficiency and ease-of-use of outcrop characterization data. Combined with the improved VGG19 (a deep convolutional neural network architecture) algorithm model, it has excellent performance in dealing with the fine texture and complex structure of rocks, which significantly improves the accuracy of lithology identification. The synergistic application of this technology provides geologists with a faster and more comprehensive means to understand the geological conditions in the field. The reliability of combining the Cesium digital outcrop characterization technology with the VGG19 lithology identification algorithm in geological exploration is verified through case studies. The synergistic application of this technology will greatly enhance the efficiency and ease of analysis of outcrop characterization in the field, and provide new perspectives for future research in geosciences.