ABSTRACT The lagoonal environment is a favourable facies for organic matter (OM) enrichment. However, the controls on OM accumulation in such a setting remain unclear. Based on high‐resolution organic and inorganic geochemical data of the Jurassic lagoonal OM‐rich black shales from the Biluo Co section in the Qiangtang Basin, the paleosalinity, paleoclimate, redox and biotic productivity were investigated to reveal the OM accumulation mechanism in a lagoonal environment. High B/Ga ratios, coupled with low Mo/TOC and Cd/Mo ratios, indicate that the studied shales were deposited under a highly restricted hypersaline environment. These conditions are compatible with a barrier‐lagoon setting in the study area. Sr/Cu and Rb/Sr ratios indicate a semi‐humid to semi‐arid climate. Enrichment factors of redox‐sensitive trace elements (i.e., Mo, U and V) as well as Th/U and C org /P ratios reveal an anoxic to euxinic bottom water column. High ratios of P/Ti, Ni/Al, Zn/Al and Cd/Al imply a high surficial bioproductivity level. The strong positive correlations among redox conditions, biotic productivity and OM contents indicate that the first two factors were the primary controls on OM enrichment. Paleosalinity and paleoclimate during the black shale deposition indirectly govern OM accumulation via different positive feedback processes. Hypersaline‐induced water‐column stratification fostered reducing benthic conditions, thereby creating favourable preservation conditions for OM accumulation. Under semi‐humid to semi‐arid climates, enhanced fluvial delivery of nutrients to the lagoonal area led to eutrophic waters and fueled biotic productivity, ultimately resulting in high OM production. Our findings underscore that OM enrichment in the Biluo Co lagoonal black shales is interpreted as the combined influence of paleosalinity and paleoclimate, rather than the individual effect of either factor.
ABSTRACT With the proposal of the ‘whole petroleum system’ concept, conventional and unconventional resources should be assessed jointly; however, their allocation patterns remain unclear. This study analyses four US basins (i.e., Permian, Williston, Western Gulf and Denver Basins) using data from Energy Information Administration for the period 2007–2025 to clarify these patterns and provide insights for shale exploration in China. The results show that unconventional production (retention production) increased steadily across all basins, whereas conventional production (expulsion production) stabilized or declined. The expulsion‐to‐retention ratios stabilized at 0.11 in the Williston Basin and 0.35 in the Western Gulf Basin, indicating relatively mature development stages, with unconventional resources accounting for approximately 90% and 72.5% of total production, respectively. In contrast, the Permian and Denver Basins exhibit rapidly declining ratios, suggesting continued growth in unconventional production. The ratio is primarily controlled by thermal maturity (Ro), total organic carbon, brittle mineral content and the pressure coefficient, with Ro being the most influential factor. Among the four basins, the Permian Basin demonstrates the greatest potential for future growth. For the Chang 7 Member of China's Ordos Basin, estimated expulsion efficiency indicates unconventional resources are approximately one to two times the volume of conventional resources. Overall, the expulsion‐to‐retention ratio proves a valuable proxy for evaluating exploration maturity and resource potential and offers practical guidance for the assessment of complex continental shale petroleum systems in China.
ABSTRACT The South Caspian Basin (SCB) is one of the world's major hydrocarbon provinces, characterized by an exceptionally thick sedimentary succession, complex deep‐basin architecture and high hydrocarbon potential. Although numerous studies have addressed individual sectors and tectonic elements of the basin, detailed structural information remains fragmented across the Azerbaijani, Turkmen and Iranian sectors. The aim of this study is to integrate the available geological and geophysical information within a single basin‐wide framework and to reconstruct, at a consistent regional scale, the principal structural levels and sediment‐thickness patterns of the entire SCB. Data integration and interpretation were carried out using the GeoFrame software package. Structural maps were constructed for the crystalline basement surface and the tops of the Cretaceous, Miocene and Lower Pliocene Productive Series, and isopach maps were compiled for the Paleogene–Miocene succession and the Productive Series. The maps integrate seismic interpretation, drilling and well‐log information and published geological and geophysical constraints from the Azerbaijani, Turkmen and Iranian sectors within one consistently scaled regional mapping framework. The resulting basin‐wide reconstruction refines the spatial relationships amongst the Azerbaijan, Ogurchin and Iranian depressions, major structural highs and regional deep‐seated fault systems, and documents a progressive increase in structural complexity from the basement and Cretaceous levels to the Miocene and Productive Series. To the best of the author's knowledge, a comparable integrated set of structure and isopach maps covering the principal stratigraphic levels across all three national sectors of the SCB has not previously been published. The reconstruction also permits evaluation of alternative deep‐structural interpretations, including the possible influence of interpreted rift‐related zones; these deeper interpretations remain hypotheses requiring verification by future deep seismic imaging and drilling. The integrated maps provide a regional framework for evaluating deeply buried exploration targets and for future geological and geophysical investigations across the entire basin.
ABSTRACT Hipparionine fossils from the newly explored Gazlope locality of the Sulaiman Range, Sakhi Sarwar, District Dera Ghazi Khan, South Punjab, are reported and described in detail. The recovered material comprises isolated upper and lower premolars and molars. Taxonomic identification based on morphometric analysis recognized three species of the family Equidae: Sivalhippus nagriensis , Sivalhippus theobaldi and Cremohipparion antelopinum . Stratigraphic analysis indicates that the Gazlope fossil‐bearing beds are equivalent to the Middle Siwalik Subgroup (11.5–3.5 Ma), supporting their Late Miocene–Early Pliocene age. Sivalhippus nagriensis and Sivalhippus theobaldi are the dominant taxa in the Gazlope fossil assemblage. This study provides the first comprehensive record of hipparionine equids from the Gazlope locality, extending the known geographic distribution of hipparionine equids in the western Sulaiman Range beyond the classic Potwar Siwalik localities and improving regional biostratigraphic correlations.
ABSTRACT Landslide susceptibility assessment (LSA) is a critical strategy for disaster prevention and mitigation. However, current machine learning‐based LSA algorithms often exhibit instability under data‐sparse conditions and suffer from a lack of physical interpretability. To address these challenges, this study proposes a physics‐integrated multi‐task neural network (PIMTN). The proposed framework incorporates slope‐stability information derived from the infinite slope model into a multi‐task neural network through an auxiliary learning task. The model simultaneously performs landslide susceptibility classification and learns a physics‐derived diluted probability of failure (DPOF). Through joint optimization, the auxiliary DPOF task influences the shared representation and guides susceptibility prediction towards spatial patterns consistent with physics‐derived slope‐stability information. Comparative experiments demonstrate that the PIMTN outperforms benchmark models (Precision: 0.737, F 1‐Score: 0.754, AUC: 0.817). Furthermore, quantitative analysis confirms the superiority of the proposed model and the effectiveness of knowledge transfer from the physical domain. This framework presents a novel solution for enhancing model interpretability and improving predictive robustness under limited‐inventory conditions.
