Frontiers of Earth Science最新文献

The hail size discrimination algorithm (HSDA) and its capacity to identify hail in Shandong Province are analyzed to satisfy the localized requirement by China’s S-band dual-polarization radars. A modified HSDA is obtained by using optimized membership function thresholds based on the statistics of Shandong hail data. The results are verified by a supercell storm process. 1) The modified HSDA improves the identification of large hail and giant hail. The results are consistent with the analysis of the scattering and polarization parameter characteristics of different-size hails, the dynamic and microphysical characteristics for supercell, and the real situation. 2) The horizontal and vertical hail-size distribution characteristics are consistent with the analysis about the growth process of larger hails and the precipitation particles filtering mechanisms in supercells. Small hail first forms at the suspension echo, then is injected into the larger hail growth area above the bounded weak echo area driven by updrafts, colliding with the abundant supercooled water in the K_DP column. Finally, large hail and giant hail fall near the direction of the updrafts to form a strong echo wall, and giant hail falls 6–12 km from the central updraft. 3) The maxima of the Z_DR and K_DP columns can be used to predict the hail-growth trend, which exceeds the −20°C isotherm for the heavy-hail growth stage at high-altitude in the supercell storm. When hail falls to the ground, the Z_DR column shortens and the K_DP column disappears, which provides the observation basis from polarimetric radars for the consumption of supercooled water by hail growth.

A sandy, braided river is a typical type of river that exists in ancient and modern alluvial plains and is inherent with significant seasonal water discharge variations. The variations play an important role in the depositional process and the formation of the sedimentary architecture of braided rivers. In this paper, a braided river outcrop along the Yellow River in Fugu is used to describe the effects of seasonal hydrodynamic variations on braided river sedimentary architecture. The results show that the braided channel network exhibits two different patterns during flood period and normal period. During flood periods, the main braided channels surrounding channel bars and the secondary braided channels distributed on the top of the channel bars coexist, forming a highly braided channel network. Migration of the main braided channels control the formation of middle channel bars and side bars. The generation and evolution of the secondary braided channels reformed the upper part of preexisting channel bars and produced affiliated bars along their flow path. During the normal period, water levels decrease, causing the secondary river channels to be abandoned and forming abandoned channels, and only the main braided channels stay active. In the long term sedimentation process, strong water flow during the flood period continuously erodes pre-existing sediments and forms new sediments, while weak water flow during the normal period can only reform the main braided channels and their adjacent channel bar sediments. Based on differences in sedimentary processes and associated hydrodynamic conditions, braided river sediments are divided into two combinations. The strong hydrodynamic combination includes main braided channels, middle channel bar, and side bar, while the weak hydrodynamic combination includes secondary braided channels, abandoned channels, and affiliated bars. The proportion of strong hydrodynamic combinations is much larger than that of weak hydrodynamic combinations. Based on this, we construct a braided river sedimentary architecture model that is helpful for the fine characterization of subsurface oil and gas reservoirs.

Surface soil materials from the Gobi Desert were sieved into fraction groups of 0.063–0.125, 0.125–0.25, 0.25–0.5, 0.5–1, and 1–2 mm. These samples were placed in a field for a physical weathering and dust deposition experiment. In the natural Gobi Desert environment, the dust-sized fractions (< 0.063 mm in diameter) produced by physical weathering and via dust deposition in the above groups were 1387 ± 124, 702 ± 70, 698 ± 47, 742 ± 101, and 769 ± 75 gm⁻², respectively, from 18 October 2020 to 18 December 2021. Dust deposition during the same period was 611 ± 55 gm⁻². For the same respective groups, 5.32 ± 0.76%, 0.58 ± 0.27%, 0.53 ± 0.18%, 0.80 ± 0.52%, and 0.98 ± 0.31% (by weight) of the bulk samples were weathered into dust-sized fractions during the experimental period. The physical weathering intensities were 23.95%, 14.96%, 8.90%, and 2.81% by weight for fraction groups of 2–4, 4–8, 8–16, and > 16 mm, respectively. The fine-grained materials of the gravel were more sensitive to physical weathering than coarse materials. In natural environments, the processes of dust deposition and physical weathering were key factors affecting the surface topographical equilibrium of the Gobi Desert and dust emission in Asia.

The produced water from coalbed methane (CBM) wells contains abundant geochemical and microbiological information. The microbial communities in the produced water of 14 CBM wells from four coal-bearing synclines in Guizhou and Yunnan were successfully tested by using 16S rRNA amplicon sequencing technology. The results showed that the produced water contained a large number of archaea and bacteria. The bacteria mainly included the orders Bacteroidales and Clostridiales, accounting for 37.4% and 32.92%, respectively. The water contained more than 30 species of bacteria and 15 species of methanogens. Macellibacteroids was the dominant genus, followed by the genus Citrobacter. The methanogens mainly included the orders Methanobacteriales and Methanosarcinales, accounting for 57.46% and 26.49%, respectively. Methanobacterium was the dominant genus, followed by the genus Methanothrix. There were three kinds of metabolism: hydrogenotrophic methanogens, acetoclastic methanogens, and methylotrophic methanogens. The main influencing factors of archaea were coalbed properties, such as burial depth and R_o,max, while the influencing factors of bacteria were mainly the physical and chemical properties of groundwater, including Cl⁻, total dissolved solids, and HCO₃⁻. The microbial communities were segmented in the vertical direction of the coal measure strata, which can be consistent with the distribution characteristics of multiple superposed fluid systems, and the main microbial species in each section were preliminarily identified. Combining carbon and hydrogen isotopes of methane, and dissolved inorganic carbon stable carbon isotopes of produced water from CBM wells, the results showed that the microbial reduction in the Tucheng and Enhong synclines were strong and that there were obvious secondary biogases. A reduction in hydrogen-trophic methane bacteria is an important way to produce secondary biogases in the study area. These synclines are suitable to carry out microbially enhanced coalbed methane research, expanding and extending CBM stimulation technology in the later stage.

Climate change has significantly impacted the1 water resources and conservation area of the Yellow River basin. The Upper Yellow River basin (UYR), referring to the area above Lanzhou station on the Yellow River is the focus of this study, the runoff changes in the UYR would greatly impact the water resources in China. Most existing studies rely on a single hydrological model (HM) to evaluate runoff changes instead of multiple models and criteria. In terms of the UYR, outputs of the previous Coupled Model International Comparison Project (CMIP) are used as drivers of HMs. In this study, the weighted results of three HMs were evaluated using multiple criteria to investigate the projected changes in discharge in the UYR using the Shared Socioeconomic Pathways (SSPs) from CMIP6. The research’s key findings include the following. 1) Annual discharge in the UYR is expected to increase by 15.2%–64.4% at the end of the 21st century under the 7 SSPs. In the long-term (2081–2100), the summer and autumn discharge will increase by 18.9%–56.6% and 11.8%–70%, respectively. 2) The risk of flooding in the UYR is likely to increase in the three future periods (2021–2040, 2041–2060, 2081–2100) under all 7 SSPs. Furthermore, the drought risk will decrease under most scenarios in all three future periods. The verified HMs and the latest SSPs are applied in this study to provide basin-scale climate impact projections for the UYR to support water resource management.

Qinshui Basin possesses enormous deep coalbed methane (CBM) resources. Fine and quantitative description of coal reservoirs is critical for achieving efficient exploration and development of deep CBM. This study proposes a 3D geological modeling workflow that integrates three parts: geological data analysis, 3D geological modeling, and application of the model, which can accurately predict the favorable areas of CBM. Taking the Yushe-Wuxiang Block within the Qinshui Basin as a case study, lithology identification, sequence stratigraphy division, structural interpretation is conducted by integrating well logging, seismic, and drilling data. Six lithology types and regional structural characteristics of the Carboniferous-Permian coal-bearing strata are finely identified. Combining experimental testing on porosity and gas content and well testing on permeability, a 3D geological model that integrates the structural model, facies model, and property model was established. Utilizing this model, the total CBM resource volume in the study area was calculated to be 2481.3 × 10⁸ m³. Furthermore, the model is applied to predict the distribution ranges of four types of CBM favorable areas. The workflow is helpful to optimize well deployment and improve CBM resource evaluation, ultimately provide theoretical guidance for subsequent efficient exploration and development. Our study constitutes a reference case for assessing potential of CBM in other blocks due to the successful integration of multiple available of data and its practical applications.

Pressure mercury intrusion test is (MIP) one of the most commonly used methods to characterize pore-fracture structure. Here, we use the fractal dimension of the mercury intrusion curve to analyze the heterogeneity of pore and fracture distribution. Differing from the intrusive mercury curve, the extrusive curve provides a better representation of the seepage capacity of a reservoir. In this paper, the division method of sample types using both mercury invasive parameters (pore volume, pore volume percentage, porosity, permeability) and extrusive parameters (mercury removal efficiency) is discussed. The fractal dimension values of mercury intrusive and extrusive curves are calculated for all samples using the Menger, Thermodynamics, and Multifractal fractal models. Moreover, the fractal significance of the mercury withdrawal curve is examined. The results are as follows. 1) The samples can be divided into three types based on the mercury removal efficiency and total pore volume. Type A is characterized by lower total pore volume (< 0.08 cm³·g⁻¹) and removal efficiency (< 30%), type B has lower total pore volume (< 0.08 cm³·g⁻¹) and higher removal efficiency (> 30%), and type C has larger total pore volume (> 0.08 cm³·g⁻¹) and higher removal efficiency(> 30%). 2) Mercury removal efficiency does not correlate with the mineral composition or total pore volume, but it does show a clear positive correlation with pore volume in the range of 100 to 1000 nm. Unlike the Menger model, the mercury removal curve analyzed using the thermodynamics and multifractal model shows good fractal characteristics. 3) In contrast to the injective curves, the fractal dimension of mercury removal curves exhibits an obvious linear negative correlation with pore structure parameters and mercury removal efficiency. Moreover, the multifractal dimensions D₀–D₁₀ obtained from the mercury removal curves show a negative correlation with porosity and permeability. This indicates that fractal dimension based on the mercury extrusion curve can be used as a new parameter for characterizing pore-fracture structure heterogeneity.

Pore volume/surface area and size distribution heterogeneity are two important parameters of pore structures, which restrict the gas-water-oil migration process in sandstone reservoirs. The fractal theory has been proved to be one of the most effective methods to quantify pore distribution heterogeneity. However, the dynamic variation of porosity and permeability due to fractal characteristics has been rarely studied. In this paper, physical properties, mineral composition, and pore distribution of 18 groups of sandstone samples were analyzed using scanning electron microscope (SEM) and high-pressure mercury injection tests. Then, Sierpinski model, Menger model, thermodynamic model, and multi-fractal model were used to calculate the fractal dimension of the pore volume. Thus, the relationship between fractal dimension and porosity/permeability variation rate, and pore compressibility were studied. The results are as follows. 1) All samples can be divided into three types based on pore volume (0.9 cm³·g⁻¹) and mercury removal efficiency (35%), i.e., Type A (< 0.9 cm³·g⁻¹and < 35%); Type B (> 0.9 cm³·g⁻¹ and <35%); Type C (> 0.9 cm³·g⁻¹ and > 35%). 2) Four fractal models had poor applicability in characterizing fractal characteristics of different sample types. The fractal dimension by the Sierpinski model had a good linear correlation with that of other models. Pores with smaller volumes dominated the overall pore distribution heterogeneity by multi-fractal dimension. The pore diameter between 200–1000 nm and larger than 1000 nm was the key pore size interval that determined the fractal characteristics. 3) With the increase of confining pressures, porosity and permeability decreased in the form of a power function. The compressibility coefficient of typical samples was 0.002–0.2 MPa⁻¹. The compressibility of Types A and B was significantly higher than that of Type C, indicating that the total pore volume was not the key factor affecting the pore compressibility. The correlation of compressibility coefficient/porosity variation rate with pore volume (total and different size pore volume), fractal value and mineral component were not significant. This indicates that these three factors comprehensively restricted pore compression.

A heavy rainstorm occurred in Henan Province, China, between 19 and 21 July, 2021, with a record-breaking 201.9 mm of precipitation in 1 h. To explore the key factors that led to forecasting errors for this extreme rainstorm, as well as the dominant contributor affecting its predictability, we employed the Global/Regional Assimilation and Prediction System-Regional Ensemble Prediction System (GRAPES-REPS) to investigate the impact of the upper tropospheric cold vortex, middle-low vortex, and low-level jet on predictability and forecasting errors. The results showed that heavy rainfall was influenced by the following stable atmospheric circulation systems: subtropical highs, continental highs, and Typhoon In-Fa. Severe convection was caused by abundant water vapor, orographic uplift, and mesoscale vortices. Multiscale weather systems contributed to maintaining extreme rainfall in Henan for a long duration. The prediction ability of the optimal member of GRAPES-REPS was attributed to effective prediction of the intensity and evolution characteristics of the upper tropospheric cold vortex, middle-low vortex, and low-level jet. Conversely, the prediction deviation of unstable and dynamic conditions in the lower level of the worst member led to a decline in the forecast quality of rainfall intensity and its rainfall area. This indicates that heavy rainfall was strongly related to the short-wave throughput, upper tropospheric cold vortex, vortex, and boundary layer jet. Moreover, we observed severe uncertainty in GRAPES-REPS forecasts for rainfall caused by strong convection, whereas the predictability of rainfall caused by topography was high. Compared with the European Centre for Medium-Range Weather Forecasts Ensemble Prediction System, GRAPES-REPS exhibits a better forecast ability for heavy rainfall, with some ensemble members able to better predict extreme precipitation.