Exploring the characteristics of vegetation dynamics and quantitatively analyzing the potential drivers and the strength of their interactions are of great significance to regional ecological environmental protection and sustainable development. Therefore, based on the 2000–2022 MODIS NDVI dataset, supplemented by climatic, topographic, surface cover, and anthropogenic data for the same period, the Sen+Mann–Kendall trend analysis, coefficient of variation, and Hurst exponent were employed to examine the spatial and temporal characteristics and trends of NDVI in Hubei Province, and a partial correlation analysis and geographical detector were used to explore the strength of the influence of driving factors on the spatial differentiation of NDVI in vegetation and the underlying mechanisms of interaction. The results showed that (1) the mean NDVI value of vegetation in Hubei Province was 0.762 over 23 years, with an overall increasing trend and fluctuating upward at a rate of 0.01/10a (p < 0.005); geospatially, there is a pattern of “low east and high west”; the spatial change in NDVI shows a trend of “large-scale improvement in the surrounding hills and mountains and small-scale degradation in the middle plains”; it also presents the spatial fluctuation characteristics of “uniform distribution in general, an obvious difference between urban and rural areas, and a high fluctuation of rivers and reservoirs”, (2) the future trend of NDVI in 70.76% of the region in Hubei Province is likely to maintain the same trend as that of the 2000–2022 period, with 70.78% of the future development being benign and dominated by sustained improvement, and (3) a combination of partial correlation analysis and geographical detector analysis of the drivers of vegetation NDVI change shows that land cover type and soil type are the main drivers; the interactions affecting the distribution and change characteristics of NDVI vegetation all showed two-factor enhancement or nonlinear enhancement relationships. This study contributes to a better understanding of the change mechanisms in vegetation NDVI in Hubei Province, providing support for differentiated ecological protection and project implementation.

In this article, the lower Cambrian marine shale of the southern part of the Ordos basin is taken as an example to investigate the formation environment and development models of source rocks with high organic abundance in the ancient strata of the southern North China plate. The lower Cambrian shale source rocks had a thickness of 10–80 m, with high total organic carbon contents (an average of 2.68% and maximum of 9.39%) and favorable organic matter types—mainly sapropelinite macerals—and yet low S1, S2, and hydrogen index, which indicate that the source rocks have relatively high thermal maturity. Therefore, it is demonstrated that marine shale of the lower Cambrian proves to be excellent gas source rocks at the southern part of the Ordos basin and are presently distributed mainly in the south part of the North China plate. During the early Cambrian period, paleoproductivity was relatively high, as indicated by the rich C₂₇ sterane contents, high sterane/hopane ratios, and high tricyclic terpane/hopane ratios in biomarkers and high P and Ba values in trace elements. The tectonic setting promoted the formation of highly abundant source rocks with favorable preservation conditions, as suggested by the relatively high V/Cr ratios and low Zr/Rb and Pr/Ph ratios. Thus, the paleoproductivity and preservation conditions were the main factors controlling the occurrence of highly abundant source rocks. The formation of highly abundant source rocks was under the joint effects of the tectonic setting and the undercompensation environments of the passive continental marginal slope of the Paleo-Qinling Ocean and deepwater bays. The paleo-geomorphologic troughs and/or fault depressions (because of tectonic movement) and deepwater bay environments together influenced the development scale of highly abundant source rocks, whereas the deepwater shelf environment of the continental marginal slope ensured the high quality of the source rocks.

Geological models are mainly obtained via interpolation of simulations using geostatistical algorithms, and the simulation results are highly uncertain. In this paper, several factors that have great influences on model results are analyzed. Through an analysis of the sensitive uncertain factors, it is found that the uncertainty of the lithofacies model has the greatest influence on the geological model, and the variogram has the second greatest influence. Therefore, ensuring the rationality of lithologic model can effectively reduce the uncertainty of the model. It is found that using seismic impedance as constraints can effectively improve the accuracy of the lithofacies model, and one can use the seismic impedance to obtain a reasonable variogram (effectively overcoming the shortage of well data), thus reducing the uncertainty of the model. Although the stochastic simulation technology used in geological modeling can yield many simulation results, only a limited number of models can be applied in practical work. In this paper, a probabilistic analysis method is proposed to optimize the model, which can provide a reference for business decision-making and risk assessment of oil and gas companies. Reserve uncertainty analysis in the exploration stage can determine the most probable reserve of the reservoir through the probabilistic characteristics of the reserve so as to determine the next exploration target. In the development stage, probabilistic analyses of the porosity, remaining oil saturation and other parameters related to oil field production can maximize the development of remaining oil. The idea of model optimization based on sensitivity analysis of model uncertainties proposed in this paper can effectively reduce the uncertainty of the model, improve the accuracy of the geological model and meet the needs of different research stages and levels.

Addressing the multifaceted and growing optimization challenges in various fields, including renewable energy, structural design, and large-scale industrial operations, necessitates continuous refinement of metaheuristic algorithms. The Beaver Behavior Optimizer (BBO) has recently been proposed as a competitive swarm intelligence approach. However, the original BBO mechanism still exhibits tendencies toward stagnation in high-dimensional and complex local optima landscapes due to fixed update rules. To elevate robustness and solution quality, this paper introduces an enhanced Beaver Behavior Optimizer (CCBBO), which suppresses structural bias by integrating a mathematical Crisscross-Strategy (CC). The CC mechanism, comprising Horizontal Crossover Search (HCS) and Vertical Crossover Search (VCS), strategically promotes non-linear and comprehensive information exchange across solution dimensions. This integration enables CCBBO to explore the search space more thoroughly and perform exploitation more precisely than the original BBO. The performance of CCBBO is rigorously substantiated through extensive experiments on the CEC2017 benchmark suite. The results decisively demonstrate that CCBBO achieves the best overall performance with the lowest average Friedman rank of 1.5517, significantly outperforming the original BBO (rank 2.8966) and eight other state-of-the-art optimizers. Furthermore, CCBBO is applied to a 60-dimensional real-world oil reservoir production optimization problem. Comparative analysis reveals that CCBBO consistently achieves a significantly higher mean Net Present Value (NPV) of 9.512 × 10⁸ USD and the lowest standard deviation of 1.481 × 10⁷ USD under identical constraints, confirming its status as a robust and stable optimization tool for tackling complex decision-making problems in engineering domains.

Seasonal delta is a sandy fan-shaped sedimentary system formed by seasonal river flooding in continental basins. Modern sedimentary finds that seasonal deltas mainly develop in an arid-semi-arid climate environment with gentle terrain. However, the study of seasonal deltas in ancient rock records is still insufficient, leading to misinterpretations as other sedimentary systems, which poses challenges to the correct understanding of the origin and spatial distribution of sand body deposits. In this study, the red bed deposits of the Cretaceous Baxigai Formation in the west of the Tabei Uplift were selected as the research object. Based on core observation and description, a comprehensive analysis of the sedimentary environment, sedimentary characteristics and sedimentary model of the Baxigai Formation was carried out using data such as well-logging and analytical testing, combined with modern depositional characteristics. Research shows that the sedimentary sequence of the Baxigai Formation red bed developed a seasonal delta sedimentary system in the arid climate. The seasonal delta deposits provide an opportunity to understand the influencing of river flow and total sedimentary loading vary greatly on the sedimentary model, sedimentary mechanism, and distribution of sand bodies in arid climates. The sedimentary process of the seasonal delta in the Baxigai Formation was controlled by the dual-stage sedimentation process in an arid paleoclimate. During the flood period, the supercritical flow sedimentary structures are widely developed in the major distributary channels, and the distributary channels migrate and bifurcate frequently. On the delta plain, crevasse channels are formed through the avulsion of major distributary channels. During the dry period, due to the consumption of water seepage and evaporation transfer, terminal distributary channels are abandoned, crevasse channels are not developed, and the sediment is exposed. The density of the distributary channels is reduced, and the total sedimentary loading is low. The distributary channels sand body is the skeleton sand body of the seasonal delta. This study is of great significance for accurately explaining the formation process of seasonal deltas and provides a useful reference for further exploration and deployment of oil and gas reservoirs and paleogeographic reconstruction in the study area.

Based on natural gas compositions, carbon isotope ratios, and geological analysis, the genesis and origin of gases in the Lower Paleozoic of Ordos basin are discussed. Due to differences in distribution and genesis, the gases in Lower Paleozoic were divided into five types, namely western margin gas, weathered crust gas, pre-salt gas, Ordovician deep gas, and Cambrian gas. The results show that the δ ¹³C₁ and δ ¹³C₂ of western margin gas range from −35.6 to −38.9‰ and from −27.2 to −35.9‰, respectively, indicating oil-type gas and mainly from the O₁k and O₂w marine source rocks. The δ ¹³C₁ of weathered crust gas varies from −31.2 to −37.8‰, but δ ¹³C₂ is mostly around −25.0‰, which indicates weathered crust gas originates from the Carboniferous–Permian coal-measure source rocks. In contrast, δ ¹³C₁ and δ ¹³C₂ in the pre-salt strata are mostly less than −30.0‰. Yet its distribution of Δ(δ ¹³C₂–δ ¹³C₁) is from −1.7 to 13.6‰, and C₁/C₂ + C₃ is of 6.68–4372.50. These indicate that the pre-salt gas is mainly high-over mature oil cracking gas from the O₁m marine source rock. The δ ¹³C₁ of Ordovician deep gas is averaging −39.4‰, and δ ¹³C₂ varies from −25.4 to −33.0‰, which imply coexistence of oil-type and coal-type gas. It is presumed that the C–P coal-type gas may migrate into and accumulate at Ordovician deep reservoirs through unconformity and fault. The δ ¹³C₂ and Δ(δ ¹³C₂–δ ¹³C₁) of Cambrian gas are both the most negative, respectively, averaging −34.9‰ and averaging −3.2‰, indicating over-mature oil-type gas. Formation and evolution of the Qingyang paleo-uplift result in that the Cambrian gas mainly comes from the Cambrian or Ordovician marine source rocks in the southern basin.