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With the high yield of many wells represented by Well JT1 in the Maokou Formation, has catalyzed a surge in exploration activities along the platform margin facies of the Maokou Formation in central Sichuan and further showed the significant exploration potential of the Maokou Formation in the northern slope. However, the fracture cave body of the Maokou Formation exhibits a high degree of development, strong longitudinal and horizontal heterogeneity, large formation pressure differences, and drilling events such as gas kicks and lost circulation occur frequently, which seriously affects the efficient implementation of drilling. Understanding the spatial distribution of the three-pressure in the formation can help better deal with and solve the above problems. Therefore, in order to help the safe, high-quality and rapid drilling of the Maokou Formation in the study area, and enhance the efficiency of oil and gas development, this paper explores the research on the prediction method of the three-pressure of jointing well-seismic data based on the geomechanical experimental data and the actual drilling data. In the process of prediction of pore pressure, this study found that the pore pressure and formation velocity in the study area have an exponential relationship. In order to enhance the applicability of the Filippone's method in the study area and improve the prediction accuracy of pore pressure, the linear relationship between pore pressure and formation velocity in the Filippone's method is modified to an exponential relationship, and a pore pressure prediction model suitable for the work area was established. Based on the Mohr–Coulomb criterion and Huang's model, the prediction models of collapse pressure and fracture pressure applicable to the study area were established, respectively. Then, the elastic parameters were obtained through pre-stack inversion, and the three-pressure bodies were calculated based on the elastic parameter bodies. The results indicate that: (1) The three-pressure prediction method of the jointing well-seismic data in this paper can predict the formation's longitudinal and transverse pressure anomaly zones in advance. (2) The Maokou Formation in the study area is characterized by abnormally high pressure, to balance the pressure of the high-ground formation, high-density drilling fluid is necessary. (3) The prediction results of three-pressure in this paper are highly consistent with the actual drilling engineering events, which verifies the reliability of the three-pressure prediction results presented in this study. The results of the study can provide a basis for decision-making in drilling geological design, such as the determination of drilling fluid density, the evaluation of borehole stability and other engineering problems that require support from three-pressure data. [ABSTRACT FROM AUTHOR]

The National Forestland "One Map" applies the boundaries and attributes of sub-elements to mountain plots by means of spatial data to achieve digital management of forest resources. The change detection and analysis of forest space and property is the key to determining the change characteristics, evolution trend and management effectiveness of forest land. The existing spatial overlay method, rasterization method, object matching method, etc., cannot meet the requirements of high efficiency and high precision at the same time. In this paper, we investigate a fast algorithm for the detection of changes in "One Map", taking Sichuan Province as an example. The key spatial characteristic extraction method is used to uniquely determine the sub-compartments. We construct an unbalanced quadtree based on the number of maximum leaf node elements (NLNE Quad-Tree) to narrow down the query range of the target sub-compartments and quickly locate the sub-compartments. Based on NLNE Quad-Tree, we establish a change detection model for "One Map" (NQT-FCDM). The results show that the spatial feature combination of barycentric coordinates and area can ensure the spatial uniqueness of 44.45 million sub-compartments in Sichuan Province with 1 m~0.000001 m precision. The NQT-FCDM constructed with 1000–6000 as the maximum number of leaf nodes has the best retrieval efficiency in the range of 100,000–500,000 sub-compartments. The NQT-FCDM shortens the time by about 75% compared with the traditional spatial union analysis method, shortens the time by about 50% compared with the normal quadtree and effectively solves the problem of generating a large amount of intermediate data in the spatial union analysis method. The NQT-FCDM proposed in this paper improves the efficiency of change detection in "One Map" and can be generalized to other industries applying geographic information systems to carry out change detection, providing a basis for the detection of changes in vector spatial data. [ABSTRACT FROM AUTHOR]

Purpose: The purpose of this paper is to propose a method that can calculate the transportation infrastructure network service capacity enhancement given by planned transportation infrastructure projects construction. Managers can sequence projects more rationally to maximize the construction effectiveness of infrastructure investments. Design/methodology/approach: This paper designed a computational network simulation software to generate topological networks based on established rules. Based on the topological networks, the software simulated the movement path of users and calculated the average travel time. This software allows the adjustment of parameters to suit different research objectives. The average travel time is used as an evaluation index to determine the most appropriate construction sequence. Findings: In this paper, the transportation infrastructure network of Sichuan Province in China was used to demonstrate this software. The average travel time of the existing transportation network in Sichuan Province was calculated as 211 min using this software. The high-speed railways from Leshan to Xichang and from Xichang to Yibin had the greatest influence on shortening the average travel time. This paper also measured the changes in the average travel time under two strategies: shortening the maximum and minimum priorities. All the transportation network optimisation plans for Sichuan Province will be somewhere between these two strategies. Originality/value: The contribution of this research are three aspects: First, a complex network analysis method that can take into account the differences of node elements is proposed. Second, it provides an effective tool for decision makers to plan transportation infrastructure construction. Third, the construction sequence of transportation infrastructure development plan can effect the infrastructure investment effectiveness. [ABSTRACT FROM AUTHOR]

To overcome the reliance on large samples and high-quality data in existing evaluation methods, while also improving evaluation efficiency and accuracy, this paper proposes a method for rapid landslide hazard assessment. This method utilizes existing research findings and specific analytical techniques for the study area to conduct rapid assessments. Taking the landslide in Yongxing Town, Mingshan Area, Ya'an City, Sichuan Province as an example, the Analytic Hierarchy Process (AHP) is combined with the Information Value (IV) method, Certainty Factor (CF) method, and Frequency Ratio (FR) method from previous studies, The AHP-IV and AHP-FR methods assess the study area as a moderately hazardous zone, while the AHP-CF method assesses it as a slightly hazardous zone. Affected by the strong 2013 Lushan earthquake, the landslide in the study area caused permanent damage. Field investigation results show that the landslide hazard in the study area is moderate, and the AHP-IV and AHP-FR methods are more consistent with the actual field results. The AHP-CF method, due to not considering the water system factor and having certain errors in its discrimination method, leans towards a safer assessment, The results of the three evaluation methods are somewhat consistent. [ABSTRACT FROM AUTHOR]

Introduction: Fingered citron slices possess significant nutritional value and economic advantages as herbal products that are experiencing increasing demand. The grading of fingered citron slices plays a crucial role in the marketing strategy to maximize profits. However, due to the limited adoption of standardization practices and the decentralized structure of producers and distributors, the grading process of fingered citron slices requires substantial manpower and lead to a reduction in profitability. In order to provide authoritative, rapid and accurate grading standards for the market of fingered citron slices, this paper proposes a grading detection model for fingered citron slices based on improved YOLOv8n. Methods: Firstly, we obtained the raw materials of fingered citron slices from a dealer of Sichuan fingered citron origin in Shimian County, Ya'an City, Sichuan Province, China. Subsequently, high-resolution fingered citron slices images were taken using an experimental bench, and the dataset for grading detection of fingered citron slices was formed after manual screening and labelling. Based on this dataset, we chose YOLOv8n as the base model, and then replaced the YOLOv8n backbone structure with the Fasternet main module to improve the computational efficiency in the feature extraction process. Then we redesigned the PAN-FPN structure used in the original model with BiFPN structure to make full use of the high-resolution features to extend the sensory field of the model while balancing the computation amount and model volume, and finally we get the improved target detection algorithm YOLOv8-FCS. Results: The findings from the experiments indicated that this approach surpassed the conventional RT-DETR, Faster R-CNN, SSD300 and YOLOv8n models in most evaluation indicators. The experimental results show that the grading accuracy of the YOLOv8-FCS model reaches 98.1%, and the model size is only 6.4 M, and the FPS is 130.3. Discussion: The results suggest that our model offers both rapid and precise grading for fingered citron slices, holding significant practical value for promoting the advancement of automated grading systems tailored to fingered citron slices. [ABSTRACT FROM AUTHOR]

The color–area ratio in ethnic minority areas is one way to perceive cultural elements visually. The openness of spaces, sense of rhythm, and richness of color affect people's emotions and induce different psychological perceptions. Despite many ethnic minority areas being more colorful than the main traits of Han, there is no systematic quantitative study for the color elements in ethnic minority areas' landscapes, not to mention the research on the color–area ratio, main and auxiliary colors and embellishments, and layouts. Therefore, this paper studies the color–area ratio of Xiangcheng County in the Tibetan area of Ganzi Prefecture in Sichuan Province. Colors are extracted and quantitatively analyzed from six different aspects using the semantic differential (SD) method and color quantitative analysis method. In this way, low-scored (B group) and high-scored (A group) color landscape samples were extracted from the landscape image library and quantitatively analyzed by ColorImpact V4.1.2. The results show that the ethnic minority group's color layout is characterized by richer colors and stronger contrasts than the Han group. This paper contributes to academic scholarship regarding color culture in ethnic minority areas. It also provides theoretical support for preserving ethnic minority groups' cultural heritage and practical insights into color planning for urban and landscape designs. [ABSTRACT FROM AUTHOR]

In order to explore the impact of education and training of farmers' professional cooperatives on agricultural green production, this paper uses the Oprobit model to analyze the impact of the time, methods, and content of cooperative education and training on green production willingness based on 534 micro-survey data of cooperative members in Sichuan Province. And then the instrumental variable method (IV-Oprobit) is used for endogeneity treatment and robustness test. The results show that: (1) Cooperative education and training time can significantly promote the green production willingness of members. Specifically, for every additional hour of education and training, the probability of "very willing" to participate in green production increases by 1.7%; (2) the four types of education and training methods of cooperative project demonstration, on-site training, bulletin board publicity, and online information publicity are all positively affecting the willingness of members to green production, and on-site training is the most effective method; (3) the three education and training contents of cognition, emotion and skills all positively affect the green production intention of members, and cognition is the most effective content; (4) the methods and contents of cooperative education and training have an interactive effect on the influence of members' green production willingness. Based on this, this paper proposes policy suggestions to optimize the functions, training methods, and content design of green production education and training in cooperatives. [ABSTRACT FROM AUTHOR]

In the early twentieth century, traditional handicraft was challenged by the latest technology in China. It is reflected by ethnic costumes combining new and old, as in the waistcoat of this study. This waistcoat made at Gyalrong Tibetan area in Sichuan, China, displays unique local features in terms of its brilliant colors and comprehensive craftsmanship. This study employs techniques such as optical microscopy, infrared spectroscopy, scanning electron microscope and high performance liquid chromatography-mass spectrometry to investigate various aspects of this waistcoat, including its fabrics and dyes. The results showed that the waistcoat was primarily made of cotton and silk, with a bamboo paper layer, and that silk as well as twisted gold and silver threads were employed for the embroidery. Various embroidery techniques were applied, with patterns, color combinations, and characteristics being consistent with those of Tibetan and Shu (蜀) embroidery. In terms of dyeing technology, a wide range of colors were achieved through multi-step dyeing processes using natural dye stuffs like pagoda bud, and synthetic dyes like magenta. These findings indicates that modern technologies were well integrated into traditional garment manufacture in the early twentieth century in China. [ABSTRACT FROM AUTHOR]

The forest-based wellness industry, as a rapidly growing sector that integrates various business forms with extensive coverage and an extended industrial chain, is undergoing rapid development due to the increasing aging population and people’s suboptimal health conditions. As a forerunner in developing the forest-based wellness industry, Sichuan province is known for its early development, proactive efforts, diverse models, and significant impact in this industry. It has achieved certain milestones in terms of top-level design, pilot demonstration, standardized guidance, and public awareness campaigns to promote the development of this industry. Therefore, this paper utilizes Sichuan as a case study to systematically summarize and analyze the key practices made by the province in promoting the rapid development of the industry by investigating the development trajectory of the forest-based wellness industry. Additionally, it examines the development trends of this industry from the perspectives of supply, demand, and consumption. Finally, this paper proposes several measures to facilitate the high-quality development of the forest-based wellness industry. These measures encompass nurturing specialized talent in forest-based wellness, enhancing market players’ capabilities in this domain, conducting extensive research on technologies that promote this industry, actively seeking support from relevant policies, and promoting integrated development across diverse sectors. [ABSTRACT FROM AUTHOR]

Szechwan lovage rhizome (SLR, the rhizome of Ligusticum chuanxiong Hort., Chuanxiong in Chinese transliteration) is one Chinese materia medica (CMM) commonly used to activate blood circulation and remove blood stasis. SLR is applicable to most blood stasis syndromes. It has significant clinical efficacy in relation to human diseases of the cardiocerebrovascular system, nervous system, respiratory system, digestive system, urinary system, etc. Apart from China, SLR is also used in Singapore, Malaysia, the European Union, and the United States of America. However, the current chemical markers in pharmacopeia or monography for the quality assessment of SLR are not well characterized or specifically characterized, nor do they fully reflect the medicinal efficacy of SLR, resulting in the quality of SLR not being effectively controlled. CMM can only have medicinal efficacy when they are applied in vivo to an organism. The intensity of their pharmaceutical activities can more directly represent the quality of CMM. Therefore, the chemical constituents and pharmacological actions of SLR are reviewed in this paper. In order to demonstrate the medicinal efficacy of SLR in promoting blood circulation and removing blood stasis, bioassay methods are put forward to evaluate the pharmaceutical activities of SLR to improve hemorheology, hemodynamics, and vascular microcirculation, as well as its anti-platelet aggregation and anticoagulation properties. Through comprehensive analyses of these pharmaceutical properties, the quality and therapeutic value of SLR are ascertained. [ABSTRACT FROM AUTHOR]

Spatial population distribution data is the discretization of demographic data into spatial grids, which has vital reference significance for disaster emergency response, disaster assessment, emergency rescue resource allocation, and post-disaster reconstruction. The random forest (RF) model, as a prominent method for modeling the spatial distribution of population, has been studied by many scholars, both domestically and abroad. Specifically, research has focused on aspects such as multi-source data fusion, feature selection, and data accuracy evaluation within the modeling process. However, discussions about parameter optimization methods during the modeling process and the impact of different optimization methods on modeling accuracy are relatively limited. In light of the above circumstances, this paper employs the RF model to conduct research on population spatialization with multi-source spatial information data. The study primarily explores the differences in model parameter optimization achieved through random search algorithms, grid search algorithms, genetic algorithms, simulated annealing algorithms, Bayesian optimization based on Gaussian process algorithms, and Bayesian optimization based on gradient boosting regression tree algorithms. Additionally, the study investigates the influence of different optimization algorithms on the accuracy of population spatialization modeling. Subsequently, the model with the highest accuracy is selected as the prediction model for population spatialization. Based on this model, a spatial population distribution dataset of Sichuan Province at a 1 km resolution is generated. Finally, the population dataset created in this paper is compared and validated with open datasets such as GPW, LandScan, and WorldPop. Experimental results indicate that the spatial population distribution dataset produced by the Bayesian optimization-based random forest model proposed in this paper exhibits a higher fitting accuracy with real data. The Coefficient of Determination (R2) is 0.6628, the Mean Absolute Error (MAE) is 12,459, and the Root Mean Squared Error (RMSE) is 25,037. Compared to publicly available international datasets, the dataset generated in this paper more accurately represents the spatial distribution of the population. [ABSTRACT FROM AUTHOR]

Natural fractures are widely developed and distributed in tight sandstone reservoirs in the western Sichuan Basin, China, influenced by complex tectonic movements and diagenetic processes. These natural fractures serve as the main flow channels and important storage spaces in such reservoirs. Understanding their development characteristics and controlling factors determines the positioning and production efficiency of tight gas wells. This paper first explores the types and characteristics of natural fractures in the second member of the Upper Triassic Xujiahe Formation (T3x2) in the western Sichuan Basin through outcrop investigations, core observations, image log interpretations, and thin section analyses. We study the main influencing factors controlling the development and distribution of tectonic shear fractures by combining the characterization of fracture attributes. The results show that the tight sandstone reservoirs in the T3x2 mainly contain tectonic fractures, diagenetic fractures, and overpressure fractures, among which shear fractures in tectonic fractures are the main types. There are four sets of tectonic shear fractures in the study area, oriented in the E-W, N-S, NE-SW, and NW-SE directions. The dip angles of fractures range from 20° to 80°, with an average dip angle of 53°, predominantly consisting of high-angle fractures. The lengths of fractures are mainly within 100 cm, with a mean value of 47.53 cm, and 76.2% of fractures have lengths less than 50 cm. Fracture apertures range from 2.51 to 163.19 μM, with an average of 30.54 μM. The proportion of effective fractures in tectonic shear fractures reaches 85.7%. The development of tectonic shear fractures is primarily influenced by lithology, rock mechanics stratigraphy, diagenetic processes and facies, and faults. Lithology stands as the fundamental factor influencing the degree of fracture development in tight reservoirs. In rocks with the same composition, as the grain size decreases, the degree of fracture development increases. Simultaneously, with the rise in muddy content, fracture development diminishes in siltstone, argillaceous siltstone, silty mudstone, and mudstone. The formation and distribution of fractures are governed by rock mechanics stratigraphy, primarily manifested as a decrease in fracture density with an increase in rock mechanics layer thickness within a certain range. Diagenetic processes affect the abundance of tectonic shear fractures by influencing the mechanical properties of rocks. The stronger the compaction and cementation, the poorer the physical properties, and the higher the brittleness of the rocks, resulting in a greater abundance of tectonic shear fractures. Rocks with strong compaction and robust cementation facies exhibit high brittleness, rendering them more susceptible to fracturing under identical stress conditions. Fractures are highly prevalent in both the hanging wall and footwall of faults. As the distance from the fault increases, the linear density of fractures significantly decreases, owing to the uneven distribution of stress perturbation caused by fault activity. [ABSTRACT FROM AUTHOR]

[Background] Dujiangyan irrigation area is an important grain producing area in Sichuan Province, and corn is the main grain crop in Sichuan Province. Dujiangyan Irrigation Project Water Conservancy Project has a large scale and reasonable layout. The area of Dujiangyan irrigation area has gradually increased, and the permanent population has reached 30.3 million. The agriculture is developed, and the water demand is large. The agricultural development in many areas is restricted by the supply capacity of water resources. [Objective] The irrigation water demand of Dujiangyan irrigation area in each growth period of corn was analyzed, and the reasonable regulation of water resources in Dujiangyan irrigation area was carried out, so as to realize the yield increase of corn in the irrigation area. [Method] Eight kinds of meteorological elements in Dujiangyan irrigation area in the past 15 years were collected to calculate water demand, effective precipitation, water profit and loss index and irrigation water demand during maize growth period in the past 15 years; Using the monthly irrigation water consumption model, the irrigation water is allocated at different growth stages of corn to maximize the corn yield in each sub irrigation area, and the irrigation water for corn at each growth stage in each sub irrigation area is determined. [Result] The average annual water demand of maize in Dujiangyan irrigation area is 376 mm, the average annual effective precipitation is 368 mm, the average annual water profit and loss index is -0.24, and the total irrigation water in the whole growth period of maize in the irrigation area is 420 million m m³, Among them, the outer river irrigation area is 30 million m m³, The irrigation area of Bihe River is 44 million m m³, The irrigation area of Tongjiyan is 19 million m m³, The Heilongtan irrigation area is 44 million m m³, The irrigation area of Renmin Canal is 96 million m m³, The second irrigation area of Renmin Canal is 112 million m³, The Dongfeng Canal irrigation area is 75 million m m³. [Conclusion] The water demand of maize in Dujiangyan irrigation area did not change significantly during its growth period, which was related to the planting varieties. During the three key growth stages of jointing, tasseling, and lactation, irrigation requires a large amount of water and requires timely regulation and replenishment of water. The water demand for corn irrigation in the Pihe irrigation area, Renmin Canal 1, and Renmin Canal 2 sub irrigation areas is relatively high, and some of them are located at the tail of the hills, which may cause problems such as seedling dehydration. Therefore, it is necessary to implement staggered scheduling in the plain irrigation area and hilly irrigation area, where water is transported from the plain irrigation area to the hilly irrigation area and stored in the hilly irrigation area. Therefore, this paper carries out precise water resources regulation and control in each growth period of maize sub irrigation areas in order to achieve the yield increase of maize in Dujiangyan irrigation area. [ABSTRACT FROM AUTHOR]

Carbonate reservoirs are characterized by abundant reserves and are currently focal points for development in oil and gas producing regions such as the Ahdab oilfield, Tarim Basin, Sichuan Basin, and Ordos Basin. The primary method for exploiting carbonate reservoirs is waterflooding. However, due to the complex pore structure and pronounced heterogeneity of carbonate rocks, the waterflooding process often leads to an unclear distribution of remaining oil and low waterflooding recovery efficiency, significantly impacting the stable and high production of carbonate reservoirs. This paper presents a two-phase flow model of oil and water in distinct pore structures by integrating fluid flow equations and interface tracking equations. It visually represents the waterflooding process at the pore scale, elucidates the distribution and formation mechanism of remaining oil, and discusses the mechanism of microscopic displacement efficiency change. The study reveals that: 1) After waterflooding, the distribution patterns of remaining oil can be categorized into dead-end remaining oil, pressure balance remaining oil, wall-bound remaining oil, Jamin effect remaining oil, and water-encapsulating remaining oil, which are governed by microscopic pore structure, wettability, and preferential flow paths; 2) From the perspective of actual reservoir displacement efficiency, intergranular pores > intergranular dissolved pores > visceral foramen > mould pore, with this trend being more pronounced under hydrophilic wetting conditions; 3) Given the oil-wet to strong oil-wet wettability characteristics of these carbonate rocks, capillary forces pose significant resistance during waterflooding. The conclusion underscores the importance of leveraging the reservoir's microscopic pore structure and wettability characteristics for actual oil wells, elucidating the evolutionary law of the mechanical mechanism of oil-water interface advancement, clarifying oil-water percolation characteristics at the pore scale, and understanding the microscopic displacement physical mechanism, all of which are crucial for guiding the design of schemes aimed at enhancing reservoir recovery efficiency. [ABSTRACT FROM AUTHOR]

Rainstorm is one of the global meteorological disasters that threaten the safety of transportation infrastructure and the connectivity of transportation system. Aiming to support the resilience assessment of transportation infrastructure in three representative regions: Sichuan–Chongqing, Yangtze River Delta, and Beijing-Tianjin-Hebei-Shandong, rainfall data over 40 years in the three regions are collected, and the temporal distribution of rainfall are analyzed. Prediction equations of rainfall are established. For the purpose of this, the probabilistic density function (PDF) is assigned to the rainfall by fitting the frequency distribution histogram. Using the assigned PDF, the rainfall data are transformed into standard normal space where regression of prediction equations is performed and the prediction accuracy is tested. The results show that: (1) The frequency of rainfall in the three regions follows a lognormal distribution based on which the prediction equations of rainfall can be established in standard normal space. The error of regression shows no remarkable dependence on self-variables, and the significance analysis indicates that the equations proposed in this paper are plausible for predicting rainfalls for the three regions. (2) The Yangtze River Delta region has a higher risk of rainstorm disaster compared to the other two regions according to the frequency of rainfall and the return period of precipitation concentration. (3) Over the period of 1980–2021, the Sichuan–Chongqing region witnessed an increase in yearly rainfall but a decrease in rainstorm disasters, whereas the other two regions experienced a consistent rise in both metrics. [ABSTRACT FROM AUTHOR]

Although atmospheric CO2 concentrations collected by satellites play a crucial role in understanding global greenhouse gases, the sparse geographic distribution greatly affects their widespread application. In this paper, a hybrid CNN and spatiotemporal Kriging (CNN-STK) model is proposed to generate a monthly spatiotemporal continuous XCO2 dataset over China at 0.25° grid-scale from 2015 to 2020, utilizing OCO-2 XCO2 and geographic covariates. The validations against observation samples, CAMS XCO2 and TCCON measurements indicate the CNN-STK model is effective, robust, and reliable with high accuracy (validation set metrics: R2 = 0.936, RMSE = 1.3 ppm, MAE = 0.946 ppm; compared with TCCON: R2 = 0.954, RMSE = 0.898 ppm and MAE = 0.741 ppm). The accuracy of CNN-STK XCO2 exhibits spatial inhomogeneity, with higher accuracy in northern China during spring, autumn, and winter and lower accuracy in northeast China during summer. XCO2 in low-value-clustering areas is notably influenced by biological activities. Moreover, relatively high uncertainties are observed in the Qinghai-Tibet Plateau and Sichuan Basin. This study innovatively integrates deep learning with the geostatistical method, providing a stable and cost-effective approach for other countries and regions to obtain regional scales of atmospheric CO2 concentrations, thereby supporting policy formulation and actions to address climate change. [ABSTRACT FROM AUTHOR]

Taking the Longmaxi deep-marine shale gas reservoir in Zigong region as the research target, this paper aimed to characterize the nano-scale pore structure and investigate the reservoirs' heterogeneity based on fractal theory. By conducting a series of experimental studies, mainly including TOC, XRD, gas adsorption (N2 and CH4), we were able to clarify the main controlling factors for the heterogeneity of deep shale pore structure. Our results indicated that the deep marine shale possessed a significant amount of organic matter, as the average TOC value is 3.68%. The XRD analysis results show that quartz and clay were the main mineral types, and the total content of these two minerals averaged 77.5%. Positive correlations were observed between TOC and quartz, while TOC decreases as the clay mineral increases, this discovery indicating that quartz is biogenic. Based on FHH (Frenkele-Halseye-Hill) method, by using the LTNA adsorption isotherms, we took relative pressure P/P0 = 0.5 as the boundary, then two separate fractal dimension were deduced, D1 and D2 represent the fractal characteristics of small and large pores, respectively. Our study revealed that both D1 and D2 demonstrated positive correlations with N2 adsorption pore volume and adsorption specific surface area, while negatively correlated with the adsorption average pore diameter. Moreover, the two fractal dimensions showed positive associations with TOC and quartz and negative associations with clay. Additionally, D1 and D2 also demonstrated a positive correlation with Langmuir volume. The presence of micropores was found to significantly influence the formation of an irregular pore structure in shale. As the pore size decreased, the adsorption specific surface area increased, resulting in a more intricate pore structure, and the fractal dimension of the pores elevated, ultimately. This intricate structure is beneficial for the accumulation of shale gas. These research findings offer valuable insights for the comprehensive assessment of deep shale gas, and enrich our knowledge of enrichment mechanisms in deep shale gas reservoirs. [ABSTRACT FROM AUTHOR]

Background: Health has effects on children's academic performance. Qi deficiency is generally used to assess an individual's health in the Chinese traditional medicine theory. This study explores the effects of qi deficiency on children's academic performance and examines whether mental fatigue mediates these effects. Methods: A total of 550 students aged 10-13 in fifth-grade were surveyed in a big primary school in Sichuan Province in November 2023 using paper-pencilbased questionnaires. Qi deficiency and mental fatigue were assessed, and exam scores in Chinese and Mathematics were recorded. Pearson's correlation and linear regression analyses were used to test the mediation model and hypotheses. Results: The fifth-grade students had mild qi deficiency (M = 2.09) and a mild state of mental fatigue (M = 2.38) on a five-point Likert scale. The average exam scores in Mathematics and Chinese were 70.07 and 74.44 points out of 100, respectively. Qi deficiency was associated with Mathematics scores (r = -0.37, p < 0.01) and Chinese scores (r = -0.30, p < 0.01), and mental fatigue (r = 0.47, p < 0.01). Furthermore, mental fatigue was associated with Mathematics scores (r = -0.46, p < 0.01) and Chinese scores (r = -0.34, p < 0.01). Linear regression analyses showed that qi deficiency significantly predicted Mathematics scores (β = -0.26, p < 0.01), Chinese scores (β = -0.19, p < 0.01), and mental fatigue (β = 0.41, p < 0.01). When qi deficiency was controlled for, mental fatigue significantly predicted Mathematics scores (β = -0.28, p < 0.01) and Chinese scores (β = -0.17, p < 0.01). Conclusion: The mediation model and hypotheses were well supported, indicating that mental fatigue mediated the influence of qi deficiency on academic performance of fifth-grade students. Furthermore, the mediation effect of mental fatigue on Mathematics scores was a little stronger than that on Chinese scores. [ABSTRACT FROM AUTHOR]

Efficient exploration of geothermal resources is the basis of exploitation and utilization of geothermal resources. In recent years, Geographic Information System (GIS) has been increasingly used for the exploration owing to its power ability to integrate and analyze multiple sources of data related to the formation of geothermal resources, such as geology, geophysics, and geochemistry. Correctly understanding the control effect of evidence factors on geothermal resources is the premise and basis of whether the prediction results of evidence weight model are accurate. Traditionally, the conventional weight of evidence model assume that each evidence factor exerts a uniform controlling effect on the formation and distribution of geothermal resources. However, recent research indicates significant variations in the controlling ability of factors such as faults and granites, influenced by factors like activity levels and crystalline ages. Yet, studies addressing this differential control are lacking. To address this gap, we propose a series of weight of evidence models using abundant geological, geophysical, and geothermal data from the western Sichuan plateau, a high-temperature geothermal hotspot in China. This study aims to investigate the impact of varying controlling abilities of evidence factors on the evaluation model, with faults and granites as a case. Performance metrics include prediction rate, success rate index, receiver operating characteristic curve (ROC) and prediction rate of geothermal well. The findings of this research reveal that the weight of evidence model developed through the methodology outlined in this study exhibits superior performance compared to the conventional weight of evidence model. This superiority is evidenced by higher prediction rates, success indices, prediction rate of geothermal wells, and larger AUC values of ROC. Among these models, the weight of evidence model considering both fault and granite classification have the best performance in model evaluation indicators, with a prediction rate of 22.528 and a success index of 0.015408 in the very high potential area. The prediction rate and success index of the high potential area are 3.656 and 0.0025, respectively, and the prediction rate and success index of the middle potential area are 1.649 and 0.001128, respectively, and the AUC value is 0.808, indicating that the model has good accuracy. In terms of geothermal well prediction, the total prediction rate of geothermal favorable areas based on fault and granite classification evidence weight model is as high as 47.0526. Therefore, when constructing the weight of evidence model, the influence of the difference control of evidence factors on the formation of geothermal resources should be fully considered. These results underscore the effectiveness of the proposed methodology in enhancing the predictive accuracy and reliability of geothermal resource assessment in this study. Based on the prediction results of the weight of evidence model considering both fault and granite classification, four favorable geothermal areas with abundant surface heat display are identified in this paper, namely Kangding, Litang, Batang and Ganzi-Dege. In addition, the relatively weak surface heat display areas such as Jiulong, Daofu, Luhuo and Derong also show high geothermal potential. Some attention should be paid to geothermal exploration in the future. [ABSTRACT FROM AUTHOR]

Recent exploration has revealed that the Middle Triassic Leikoupo Formation 32 Submember (T2/32) in the Sichuan Basin contains unconventional marl reservoirs with significant natural gas potential. Due to limited cores, old wells, and conventional logs, however, the lithological understanding of T2/32 is incomplete and relies solely on inaccurate mud logs. This lack of lithological foundation challenges geology and petroleum research. To identify complex lithology, this paper presents a double-hierarchical workflow to identify seven types of lithology using logs. The first order distinguishes salt, anhydrite, and marl, while the second order further subdivides marl into anhydrite marl, argillaceous limestone, shaly limestone, and limy shale. Different rocks' logging response characteristics are summarized based on quantity-limited cores and micro-resistivity imaging logs. Lithological identification of 2D and 3D plots is established using sensitive GR, DEN, and RT. Corresponding identification standards are built in two hierarchies. According to these standards, the lithology of T2/32 is identified in a total of 119 wells. Finally, the lithological characteristics of vertical, horizontal, and plane are discussed in the research area. The research results may aid in comprehending the entire lithological characteristics of the complex marl reservoir in T2/32 of the Sichuan Basin. It would help the exploration potential of petroleum systems in turn. [ABSTRACT FROM AUTHOR]

Small-scale landslides that occur at unexpected locations and seasons can cause severe losses of life and property. Unusually, the Shidang landslide occurred prior to the rainy season in Jinkouhe County, Sichuan Province, China, resulting in 19 deaths and missing persons. In this paper, landslide characteristics and causes are revealed through a field investigation, laboratory experiments, and numerical calculations. The results show that the Shidang landslide was a small-scale landslide with a total volume of approximately 19500 m3, originating from hollow colluvial deposits. The geomorphological hollow above the landslide provided topographic conditions for the collection of subsurface runoff. Groundwater flow was transported downward along dolomite and accumulated in the area above shale, with a low conductivity. Groundwater table rise combined with the decrease in the soil strength led to landslide occurrence. Improper siting of residential areas and insufficient vigilance against post-rainfall landslides caused this tragedy. Considering the post-disaster lessons, it is strongly recommended that in the future, more attention should be given to the investigation of landslides triggered by groundwater, especially in determining landslide hydrological system boundaries. In mountainous areas where the developable space is limited, areas with hollow landforms are potentially at risk of geohazards. This paper could provide a reference for the prevention and management of similar landslides and new insights for updating landslide investigation systems and residential housing plans. [ABSTRACT FROM AUTHOR]

Landslides constitute a significant hazard to human life, safety and natural resources. Traditional landslide investigation methods demand considerable human effort and expertise. To address this issue, this study introduces an innovative landslide segmentation framework, EMR-HRNet, aimed at enhancing accuracy. Initially, a novel data augmentation technique, CenterRep, is proposed, not only augmenting the training dataset but also enabling the model to more effectively capture the intricate features of landslides. Furthermore, this paper integrates a RefConv and Multi-Dconv Head Transposed Attention (RMA) feature pyramid structure into the HRNet model, augmenting the model's capacity for semantic recognition and expression at various levels. Last, the incorporation of the Dilated Efficient Multi-Scale Attention (DEMA) block substantially widens the model's receptive field, bolstering its capability to discern local features. Rigorous evaluations on the Bijie dataset and the Sichuan and surrounding area dataset demonstrate that EMR-HRNet outperforms other advanced semantic segmentation models, achieving mIoU scores of 81.70% and 71.68%, respectively. Additionally, ablation studies conducted across the comprehensive dataset further corroborate the enhancements' efficacy. The results indicate that EMR-HRNet excels in processing satellite and UAV remote sensing imagery, showcasing its significant potential in multi-source optical remote sensing for landslide segmentation. [ABSTRACT FROM AUTHOR]

There are significant challenges in attracting young people's attention to the protection and inheritance of intangible cultural heritage (ICH). Even Sichuan opera, a highly interactive and entertaining local cultural representative, struggles with inheritance issues. To solve this problem, this paper utilizes Augmented Reality (AR) technology to achieve a virtual try-on of Sichuan opera costumes and interactive face transformation for Sichuan opera. By virtual modeling, skeleton binding, weight setting of Sichuan opera dan-role costumes, and rendering mapping using body tracking and ray tracing as well as cloth simulation techniques, the AR try - on of Sichuan opera costumes is realized. Additionally, the representative facial masks of Sichuan opera's face-changing and role types are digitally reconstructed in 3D, and AR interactive face transformation is accomplished through visual programming. Experimental results demonstrate that in the AR environment, real-time matching and stable interaction among human body movements, costumes, and facial masks are achieved. By conducting AR experiments and surveys among the youth group, it is found that compared to traditional methods, AR technology is more effective in capturing the attention and recognition of the younger generation. This is beneficial for the inheritance and development of intangible cultural heritage within this demographic. [ABSTRACT FROM AUTHOR]

Fracture network fracturing is pivotal for achieving the economical and efficient development of shale gas, with the connectivity among fracture networks playing a crucial role in reservoir stimulation effectiveness. However, flow back data that reflect fracture network connectivity information are often ignored, resulting in an inaccurate prediction of the effective fracture network volume (EFNV). The accurate calculation of the EFNV has become a key and difficult issue in the field of shale fracturing. For this reason, the accurate shale gas effective fracture network volume inversion method needs to be improved. Based on the flow back characteristics of fracturing fluids, a tree-shaped fractal fracture flow back mathematical model for inversion of EFNV was established and combined with fractal theory. A genetic algorithm workflow suitable for EFNV inversion of shale gas was constructed based on the flow back data after fracturing, and the fracture wells in southern Sichuan were used as an example to carry out the EFNV inversion. The reliability of the inversion model was verified by testing production, cumulative gas production, and microseismic results. The field application showed that the inversion method proposed in this paper can obtain tree-shaped fractal fracture network structure parameters, fracture system original pressure, matrix gas breakthrough pressure, fracture compressibility coefficient, reverse imbibition index, equivalent main fracture half length, and effective initial fracture volume (EIFV). The calculated results of the model belong to the same order of magnitude as those of the HD model and Alkouh model, and the model has stronger applicability. This research has important theoretical guiding significance and field application value for improving the accuracy of the EFNV calculation. [ABSTRACT FROM AUTHOR]

In this paper, taking the Wufeng Formation-Longmaxi Formation shales in the southeastern region of the Sichuan Basin as an example, the thin section, X-ray, geochemical testing and TIMA techniques are used to systematically study the source analysis and characterization of quartz fractions, and in turn, the mechanism of the development of highly brittle shale reservoirs is revealed. The results of the study show that the high quartz mineral content segments are well stacked with the organic matter enriched segments. Excess silica occurs in the lower part of the Wufeng -Longmaxi Formation, and some samples in the middle and upper part of the Wufeng and Longmaxi Formation have excess silica deficit; the K2O/Na2O ratio is generally >1, reflecting that the reservoir quality is affected by the biogenic silica. Land- sourced detrital quartz grains, on the other hand, are significantly larger and are generally distributed over a range of tens to more than a hundred micrometers, often with clay minerals and organic matter around the periphery. Biogenic siliceous fossils are mainly developed in the lower part of the Wufeng-Longmaxi Formation, dominated by biogenic siliceous remains such as radiolarians. TIMA test results show that quartz belongs to the mineral type with absolutely dominant content ratio in the bottom samples of the Wufeng-Longmaxi Formation and reflects the characteristics of fine-grained-muddy/ carbonaceous horizontal laminar deposition. There are three different types of quartz grain distribution patterns in shale reservoirs, including excess silica type, multi-source silica type, and land-source silica type. The layers of highly brittle shale reservoirs are all at the bottom of Wufeng-Longmaxi Formation, which is rich in biogenic silica, and at the same time, they are also in the active layers of montmorillonite and other abundant volcanic activities, and they are developed in the closed basins as well as the deep-water land scaffolds, so that the reservoirs have a good self-sealing; at the same time, the combination of microcrystalline quartz+organic matter makes the reservoirs have an excellent mechanical brittleness. [ABSTRACT FROM AUTHOR]

Old landslides in the Loess Plateau, Northwest China usually occurred over a relatively long period, and their sizes are usually smaller compared to old landslides in the alpine valley areas of Sichuan, Yunnan, and Southeast Tibet. These landslide areas may have been changed either partially or greatly, and they are usually covered with vegetation and similar to their surrounding environment. Therefore, it is a great challenge to detect them using high-resolution remote sensing images with only orthophoto view. This paper proposes the optimal-view and multi-view strategic hybrid deep learning (OMV-HDL) method for old loess landslide detection. First, the optimal-view dataset in the Yan'an area (YA-OP) was established to solve the problem of insufficient optical features in orthophoto images. Second, in order to make the process of interpretation more labor-saving, the optimal-view and multi-view (OMV) strategy was proposed. Third, hybrid deep learning with weighted boxes fusion (HDL-WBF) was proposed to detect old loess landslides effectively. The experimental results with the constructed optimal-view dataset and multi-view data show that the proposed method has excellent performance among the compared methods—the F1 score and AP (mean) of the proposed method were improved by about 30% compared with the single detection model using traditional orthophoto-view data—and that it has good detection performance on multi-view data with the recall of 81.4%. [ABSTRACT FROM AUTHOR]

This study focuses on constructions that are vulnerable to fire hazards during wildfire events, and these constructions are known as 'exposures', which are an increasingly significant area of disaster research. A key challenge lies in estimating dynamically and comprehensively the risk that individuals are exposed to during wildfire spread. Here, 'exposure risk' denotes the potential threat to exposed constructions from fires within a future timeframe. This paper introduces a novel method that integrates a spatiotemporal knowledge graph with wildfire spread data and an exposure risk analysis model to address this issue. This approach enables the semantic integration of varied and heterogeneous spatiotemporal data, capturing the dynamic nature of wildfire propagation for precise risk analysis. Empirical tests are employed for the study area of Xichang, Sichuan Province, using real-world data to validate the method's efficacy in merging multiple data sources and enhancing the accuracy of exposure risk analysis. Notably, this approach also reduces the time complexity from O   (m × n × p) to O   (m × n) . [ABSTRACT FROM AUTHOR]

In this paper, the optimal estimation method of rock shear strength parameters is studied. Aiming at the heteroscedasticity problem in rock shear strength data, a weighted linear regression method is introduced. In the linear regression analysis of rock shear strength, it is generally assumed that the observation errors of dependent variables obey the same normal distribution, but the heteroscedasticity problem in triaxial strength data is ignored. In this paper, the open-pit sandstone in the southwest of Sichuan Province is used as the research object, and the triaxial strength data of sandstone under different confining pressures are obtained. The weighted linear regression method is used to analyze and solve the problem of heteroscedasticity of the data. This paper first introduces the theoretical basis and related statistical methods of rock shear strength and then elaborates on the concept and application scope of weighted linear regression. The theoretical formula and test method of weighted linear regression are proposed, and the definition and calculation method of weight in weighted regression are explained. Finally, the experimental data of open-pit sandstone in the southwest of Sichuan Province are verified. The research results prove the effectiveness of the weighted least squares method in the estimation of rock shear strength parameters. The research results can provide a relevant theoretical basis for the selection of shear strength parameters. [ABSTRACT FROM AUTHOR]

Potato (Solanum tuberosum L.) is an essential staple crop in China. Appropriate storage methods and technology are critical to ensure the quality of seed potatoes, which is closely related to the field performance. So far, the diffused light storage (DLS) technique has been widely applied to potato crop. In this paper, two special potato varieties ('Chuanyu 117' and 'Mira') were treated at DLS for 60 days, and the effects of growth conditions on tuber sprouts and subsequent field performance were evaluated. The results showed that the DLS treatment significantly promoted the greening of potato tubers from highland and simultaneously affected the average sprouting rate, sprout length and number of sprouts at different storage stages, which indicated obvious interacting correlations between DLS treatments and potato varieties. Especially for 'Mira', the shortest average sprout length (2.7 mm) was obtained under 40–200 lx light level, while 'Chuanyu 117' had the shortest average sprout length (1.3 mm) under 5–10 lx and its sprout length was also controlled within 2.3 mm under 200–2000 lx. In the cultivation experiment that followed, the potato tubers with 4–6 mm and 2–3 mm sprout length had the highest yield after 90 days and 110 days planting, respectively. Overall, these results demonstrated that for seed potatoes harvested from the highland area followed by storing for 30 days in the lowland, the sprout length can be better controlled at 2–3 mm to obtain short and strong sprouts when stored under 40–200 lx or 200–2000 lx diffused light for 60 days, which is especially suitable in terms of fast field emergence after planting and final tuber yield for the autumn and winter cultivation of potato in the Chengdu Plain. It is also suggested that the DLS technique on seed potatoes could be used in the mixed single and double-cropping areas in Sichuan and other areas with similar geographical and climatic conditions. The findings of this study have several important implications in the storage, transportation, processing as well as seed potato market for commercial practice. [ABSTRACT FROM AUTHOR]

The Longmaxi Formation in the Sichuan Basin is a hotspot formation for shale gas exploration. In this paper, taking the Longmaxi Formation shale in Yuxi area as an example, a large number of TOC tests, X-diffraction whole-rock mineral fraction tests, electron microscope observations, physical properties, gas content, and CT scanning experiments were carried out, which in turn analyzed the characteristics of the shale gas reservoir and the factors influencing the gas content. The results of the study show that there are seven types of shale facies developed in Yuxi area, which are organic-rich siliceous shale facies (I), organic-rich carbonate-siliceous shale facies (II), organic-rich clayey shale facies (III), organic-poor clayey shale facies (IV), organic-poor carbonate-siliceous shale facies (V), organic-poor siliceous shale facies (VI), and organic-poor siliceous-carbonate shale facies (VII). The microstructural characteristics of the shale reflect that it was disturbed by multiple environmental factors at the time of deposition, and the sources of brittle minerals include both terrestrial clasts and biogenic siliciclastics. The bottom 30 m shale of Longmaxi Formation has good physical properties and gas content, which is a high-quality target section for shale gas exploration and development. TOC, Ro, permeability, quartz content and clay mineral content all have a significant effect on shale gas content and are important control factors for shale gas content. [ABSTRACT FROM AUTHOR]

[Objective] In recent years, high-yield gas wells, such as those in eastern Sichuan, Tarim Oilfield, and Dongfang Gas in the South China Sea, have been increasingly common. However, these wells are not without their challenges. The production pipe string of Sangao gas wells is prone to vibration failure due to the impact of high-speed gas. Taking the Kuqa high-pressure gas area of the Tarim Oilfield as an example, 19 failure incidents have been recorded out of 15 wells, resulting in huge economic property losses and, regrettably, casualties. The primary cause of these failures has been identified as the excessive dynamic load caused by pipe string vibration. Therefore, understanding the vibration characteristics of the production pipe string has become a crucial study area. The production string in oil and gas wells possesses its unique characteristics. Its large slenderness ratio results in a very low overall stiffness, which is difficult to simulate in a typical small experimental system. [Methods] In this study, we established a test bench for large production string evaluation. We developed an extensive, elongated string model using Polyethylene pipe to replicate the vibration characteristics of the production string under high-speed fluid impact. [Results] The experimental results show that the production string in Sangao gas wells vibrates at a constant frequency under the influence of a high-speed fluid. The vibration amplitude is most pronounced in the middle and bottom parts of the string. It was also observed that an increase in gas yield correlates with an increase in the severity of the pipe column's vibration. An effective method of curtailing this vibration amplitude involves increasing the wall thickness of the tubing. However, it is important to note that while this may reduce the tubing amplitude, it does not change the vibration frequency of the tubing string. The packer installation position also plays a pivotal role in vibration suppression. If the packer is installed too high or too low, it fails to effectively suppress vibration. The optimal placement for a single packer has been found to be at the 8/10 position of the string, where it can efficiently suppress vibration. This paper further delves into the analysis of displacement, frequency, and vibration characteristics of simulated tubing when subjected to a high-speed fluid within the tubes. [Conclusions] This study further explores the effects of pipe wall thickness, gas yield, and packer setting positions on the vibration characteristics of simulated tubing. The following conclusions were drawn from the research. When the fluid Reynolds number within the tube reaches 21 430, the simulated tubing presents a second-order vibration mode. This results in a substantial amplitude in the middle and bottom sections of the simulated tubing, which are prone to contact and collision with the casing wall, potentially resulting in pipe string failure. The wall thickness of the tubing exerts little effect on the vibration frequency of the simulated tubing. However, it significantly affects the vibration amplitude. The thicker the tubing, the smaller the vibration amplitude of the simulated tubing. Therefore, tubing vibration can be effectively suppressed by increasing tubing thickness during the actual production process. The larger the gas production, the greater the frequency and amplitude of the simulated tubing vibration. When gas production is excessively large, the tubing is likely to collide severely with the casing wall, thereby increasing the risk of tubing failure. Therefore, it is crucial in the actual production process to determine the daily gas output reasonably, keeping in mind the bearing limit of the tubing. Packers suppress string vibration by limiting the lateral displacement of the string. Installing multiple packers proves to be more effective than a single packer in suppressing vibration. [ABSTRACT FROM AUTHOR]

With the gradual decline of natural gas production, reserve upgrading has become one of the important issues in natural gas exploration and development. However, the traditional reserve upgrade forecasting method is often based on experience and rules, which is subjective and unreliable. Therefore, a prediction method based on neural network is proposed in this paper to improve the accuracy and reliability of reserve upgrade prediction. In order to achieve this goal, by collecting the relevant data of natural gas exploration and development in Sichuan Basin, including geological parameters, production parameters and other indicators, and processing and analyzing the data, the relevant characteristics of reserves increase are extracted. Then, a neural network model based on multi-layer perceptron (MLP) is constructed and trained and optimized using backpropagation algorithm. The results show that the prediction accuracy of the constructed neural network model can reach more than 90% and can effectively predict the reserve upgrading. Experiments show that the model has high accuracy and reliability, and is significantly better than the traditional prediction methods. The method has good stability and reliability, and is suitable for a wider range of natural gas fields. [ABSTRACT FROM AUTHOR]

Deep shale reservoirs (3500–4500 m) exhibit significantly different stress states than moderately deep shale reservoirs (2000–3500 m). As a result, the brittleness response mechanisms of deep shales are also different. It is urgent to investigate methods to evaluate the brittleness of deep shales to meet the increasingly urgent needs of deep shale gas development. In this paper, the quotient of Young's modulus divided by Poisson's ratio based on triaxial compression tests under in situ stress conditions is taken as SSBV (Static Standard Brittleness Value). A new and pragmatic technique is developed to determine the static brittleness index that considers elastic parameters, the mineral content, and the in situ stress conditions (BIEMS). The coefficient of determination between BIEMS and SSBV reaches 0.555 for experimental data and 0.805 for field data. This coefficient is higher than that of other brittleness indices when compared to SSBV. BIEMS can offer detailed insights into shale brittleness under various conditions, including different mineral compositions, depths, and stress states. This technique can provide a solid data-based foundation for the selection of 'sweet spots' for single-well engineering and the comparison of the brittleness of shale gas production layers in different areas. [ABSTRACT FROM AUTHOR]

The exploration and development potential of shale gas reservoirs in the Sichuan Basin is enormous; however, it also faces difficulties such as complex structures, strong heterogeneity, and unclear geophysical response characteristics. Fine prediction of geostress is an important part of shale gas exploration and development, which directly affects the implementation effect of reservoir evaluation, well trajectory design, and fracture reconstruction. The existing geostress prediction techniques lack high-precision seismic data constraints, making it difficult to accurately reflect the planar distribution characteristics of geostress in the block with rapid changes in complex tectonic zones. At the same time, the geophysical response characteristics of geostress in the Sichuan Basin are unknown, and the geostress seismic prediction technology lacks theoretical basis. This paper combines numerical simulation and physical experiments and defines the characteristics of the geophysical response of shale gas reservoirs in the Sichuan Basin changing with the stress field, and technical countermeasures for geostress seismic prediction have been established to provide technical means for accurate prediction of the geostress field in the shale gas block. Based on the geostress sensitive parameters obtained from prestack seismic inversion, the geostress field prediction of a shale gas work area in the Sichuan Basin is realized. [ABSTRACT FROM AUTHOR]

The Yarlung Zsangbo Grand Canyon (YGC) is an important pathway for water vapor transport from southern Asia to the Tibetan Plateau (TP). This area exhibits one of the highest frequencies of convective activity in China, and precipitation often induces natural disasters in local communities, which can dramatically affect their livelihoods. In addition, the produced precipitation gives rise to vast glaciers and large rivers around the YGC. In 2018, the Second Tibetan Plateau Scientific Expedition and Research Program tasked a research team to conduct an "investigation of the precipitation process in the water vapor channel of the Yarlung Zsangbo Grand Canyon" (INVC) in the southeastern TP. This team subsequently established a comprehensive observation system of land–air interaction, water vapor, clouds, and rainfall activity in the YGC. This paper introduces the developed observation system and summarizes the preliminary results obtained during the first two years of the project. Using this INVC observation network, herein, we focus on the development of rainfall events on the southeastern TP. This project also helps to monitor geohazards in the key area of the Sichuan–Tibet railway, which traverses the northern YGC. The observation datasets will benefit future research on mountain meteorology. [ABSTRACT FROM AUTHOR]

The exploration and comprehensive assessment of fractured-vuggy reservoir information have perennially constituted focal points and challenges within the domain of oil and gas reservoir evaluation. The verification of geological phenomena, identification of various fracture and hole types, and the quantitative characterization thereof currently present pressing challenges. This study meticulously examines the deep carbonate reservoirs within the Dengying Formation in the Penglai gas region of the Sichuan Basin. The Core Rolling Scan images reveal five discernible features: unfilled holes, filled holes, filled fractures, open fractures, and algae. The analysis pinpoints three primary challenges in semantic segmentation recognition: the amalgamation of feature scales, class imbalance, and the scarcity of datasets with substantial sample sizes. To address these challenges, this paper introduces a Multi-Scale Feature Aggregation Pyramid Network model (MFAPNet), achieving a pixel accuracy of 68.04% in recognizing the aforementioned five types. Lastly, the model is employed in calculating core porosity, exposing a scaling relationship between wellbore image porosity and core porosity ranging from 1.5 to 3 times. To a certain extent, it reveals the correlation between the wellbore image logging data and the actual formation of the Dengying Formation in the Penglai Gas Field of the Sichuan Basin, and also provides a basis for the subsequent logging evaluation of the formation. The partial code and CHA355 dataset are publicly available at https://github.com/zyng886/MFAPNet. [ABSTRACT FROM AUTHOR]

Machine learning models have been widely used in landslide susceptibility prediction. However, landslide multidimensional feature extraction, model generalization ability, and prediction quantification of deep learning are still challenging. This paper proposes a new approach, the landslide density-based bidirectional long short-term memory (LD-BiLSTM) model with multichannel input and an optimized sampling strategy to predict and map landslide susceptibility in active seismic mountainous areas of Sichuan Province, China. First, to ensure the generalization ability of the LD-BiLSTM model, other regions in Sichuan were selected as the model training area independent of the prediction area (Luding County). Multichannel landslide datasets were constructed to extract high-dimensional geospatial features of landslides. Subsequently, the landslide density of each grid cell was utilized as the label for the corresponding input sample. The LD-BiLSTM model was improved by using transfer learning and sampling optimization strategies, which makes our method attenuate the impact of historical landslide inventory deviation on the spatial susceptibility mode compared with the existing DL model, which usually uses landslide objects (LO) as input sample labels. Model performance evaluation results show that the LD-BiLSTM model (precision = 0.903, recall = 0.899, F1-score = 0.901, Area under receiver operating characteristic curve (AUC) = 0.940) outperformed the LO-BiLSTM model (precision = 0.812, recall = 0.815. F1-score = 0.813, AUC = 0.910) in the case areas. Meanwhile, the performance of the LD-BiLSTM model (AUC = 0.9407) significantly outperformed both the information value (IV) (AUC = 0.7207) model and the random forest (RF) (AUC = 0.8116) models in the landslide prediction area (Luding), which confirms that the proposed LD-based method is superior to traditional LO-based methods. Significantly, our approach can effectively extract the spatial distribution of landslides and predict potential landslides in complex high-mountain environments. [ABSTRACT FROM AUTHOR]

Landslides are common natural disasters that cause serious damage to ecosystems and human societies. To effectively prevent and mitigate these disasters, an accurate assessment of landslide hazards is necessary. However, most traditional landslide hazard assessment methods rely on static assessment factors while ignoring the dynamic changes in landslides, which may lead to false-positive errors in the assessment results. This paper presents a novel landslide hazard assessment method for the Zagunao River basin, China. In this study, an updated landslide inventory was obtained for the Zagunao River basin using data from interferometric synthetic aperture radar (InSAR) and optical images. Based on this inventory, a landslide susceptibility map was developed using a random forest algorithm. Finally, an evaluation matrix was created by combining the results of deformation rates from both ascending and descending data to establish a hazard level that considers surface deformation. The method presented in this study can reflect recent landslide hazards in the region and produce dynamic assessments of regional landslide hazards. It provides a basis for the government to identify and manage high-risk areas. [ABSTRACT FROM AUTHOR]

Siliceous minerals of the Dengying Formation in the Gaoshiti–Moxi area in the central Sichuan Basin exhibit four types of quartz crystals (cryptocrystalline quartz, chalcedony, microcrystalline quartz, and megacrystalline quartz) and three structural types: cryptocrystalline, microcrystalline, and mosaic (laminated mosaic, window-hole interrupted mosaic, and arc-laminated mosaic). Siliceous minerals have a great influence on the storage performance of the reservoirs in the Dengying Formation. According to the petrophysical parameters of the Dengying Formation and porosity intersection diagrams, the siliceous dolomite and the reservoirs have low impedance characteristics, which makes it difficult to distinguish between them and leads to difficulties in the characterization and prediction of the reservoirs. The transverse wave velocity is favorable for reservoir characterization. Currently, the main method used to estimate the transverse wave velocity is petrophysical modeling, which establishes a relationship between the elastic and physical parameters of the reservoir. In this paper, the siliceous minerals in the dolomite in the study area are regarded as solid inclusions, and the calculation method of the rock matrix modulus is improved by using solid replacement. Then, an improved petrophysical model is constructed by combining the KT (Kuster–Toksöz) model, the DEM (Discrete Element Method) model, the Gassmann equation, and the Wood equation. The transverse wave velocity is estimated using the improved model under the constraint of the longitudinal wave velocity. The shapes of the transverse wave velocity curves obtained by the improved model and the deviations from the measured velocities are significantly better than those of the Xu–Payne model and other models. The results show that the improved model can effectively estimate the transverse wave velocity of the reservoir in this area, which provides a basis for future reservoir predictions in this area. [ABSTRACT FROM AUTHOR]

Low-field nuclear magnetic resonance (LF-NMR) technology plays a growing role in studying reservoirs for oil displacement characteristics. To better explore the reservoir characteristics of Da'anzhai in the Sichuan Province of China, this paper uses LF-NMR imbibition flooding experiments to study the improvement of oil displacement efficiency for shale oil reservoirs in Southwest China by different imbibition flooding technologies. In this article, experiments in scanning electron microscopy, X-ray diffraction analysis, and rock mechanics were conducted to analyze the geological features of the reservoir in the study area. In combination with the test results of the nuclear magnetic resonance method, the field technology has been reformed to improve the oil recovery efficiency. The results show that the Da'anzhai area is mainly composed of interbedded shale and limestone, with a relatively low organic carbon content and low average porosity. The pores shouted are predominantly concentrated in the range of 1–100 nm, and there are micrometer-sized pores. The mineral composition of the area is primarily quartz, dolomite, and calcite, rich in clay minerals. The degree of the development of natural fractures is not high, and the mean coefficient of stress differential in two directions is 0.19. The content of brittle minerals is greater than 50%, meaning that the overall compressibility is good. The results of the stratified T2 test show that the imbibition efficiency of shale in this area is low. The imbibition efficiency of the three cores is the best in 0–20 mm, and the imbibition efficiency is low in the 40–60-mm section. The optimum imbibition formula 2 has an apparent promoting effect on the imbibition of shale in this area. Based on the optimal formula system of imbibition flooding experiments, the average reservoir volume of reconstruction (SRV) in the Sichuan Basin increased from 39 million cubic meters to 46 million cubic meters. The oil production test went from "seeing boiling oil" to almost 2 tons/day, making a significant breakthrough in "oil production." As a result, LF-NMR technology is used to investigate the effects of core imbibition and oil displacement. The results can be used as a guide for applying on-site oil production technology transformation, which is of constructive importance for improving production. [ABSTRACT FROM AUTHOR]

Late Permian to middle Triassic volcanic activities were very strong, however, volcanic records in the early Triassic strata are less reported than those of the Permo-Triassic boundary and the Triassic Olenekian-Anisian boundary in the Yangtze plate, especially within the Sichuan basin. We conduct zircon U-Pb dating and geochemical analysis of the tephra which was first found in the early Triassic Jialingjiang Formation from the Maliuping section, Hechuan, Chongqing. The volcanic ash in the paper yields the new 248.5 ± 0.7 Ma U-Pb age consistent with those of volcanic ashes in these contemporaneous strata in the Yangtze plate. Geochemical characters of whole-rock samples show lower contents in SiO2, K2O and higher components in Al2O3, CaO, MgO, relatively enriched LREE and depleted HREE with distinct negative Eu anomaly, and conspicuous Ba, Nb, Ta, Sr, P, Ti depletion and Th, U, K, Nd enrichment, which is similar to those of the Mung Bean rock of the Triassic Olenekian-Anisian boundary, and those of acidic volcanics from the Sanjiang orogenic belt and Shiwandashan-Qiangfang suture zone during the Early-Middle Triassic. Trace elements of whole rock and analysed zircons of the tuff imply its primary magma derived from Rhyodacite/Dacite and its tectonic setting of volcanic arc granite with continental crust affinity. The early Triassic volcanism during the syn-collision stage of the Paleo-Tethys evolution was less active than those of the Permo-Triassic boundary and the Triassic Olenekian-Anisian boundary, while the volcanic event may have a crucial effect on prolonging fully biotic recovery and entirely ecosystem turnover soon after the Permian-Triassic mass extinction. [ABSTRACT FROM AUTHOR]

We report five new dinosaur track sites in Chaya County, about 120 km southeast of Changdu City. The track assemblages are dominated by sauropods (45 tracks), which have been identified tentatively as cf. Brontopodus. Also present are two thyreophoran trackways consisting of 13 tracks that show strong similarities with the ichnogenus Deltapodus, the potential trackmakers of which were probably stegosaurids. The sauropod tracks from the Chaya region are dominated by large tracks with different affinities if compared to those of the Changdu area. The isolated sauropod tracks from Changdu and Chaya regions show similar morphological patterns, but those from the Chaya region lack large scale tracks. This paper compares and discusses the known ichno and body fossil records of sauropods, theropods, and ornithischians from the Middle Jurassic of Yunnan, Sichuan, and eastern Tibet and their importance for our understanding of dinosaur faunas from this region. The absence of basal neornithischian records in the Yunnan and Changdu regions is likely a preservational bias but also an ecological pecularity cannot be completely excluded. The palaeogeographic position of the four sampled skeleton and track sites suggests the possible existence of a corridor through which faunal exchanges were taking place throughout the Jurassic. [ABSTRACT FROM AUTHOR]

This paper investigates the origin of ultra-deep dolostone and the factors influencing large-scale dolostone reservoirs, focusing on the Sinian Dengying Formation and the Cambrian Longwangmiao Formation in the Sichuan Basin. The study involves petrology, microscale X-ray diffraction, trace element analysis, and C-O-Sr-Mg isotope experiments to provide a detailed analysis. The research findings indicate that the Dengying and Longwangmiao formations comprise six types of matrix dolostone and four types of cement. The Dengying Formation, which developed under a sedimentary background of a restricted platform, contains special microbial and microcrystalline dolostones. The dolomite grains are small (<30 µm) and have a low order degree (Min=0.55), with large unit cell parameters and an extremely high Na content (Max=788 ppm). The 87Sr/86Sr value of the dolostone is consistent with contemporaneous seawater, while the δ13C and δ18O values are lower than those of the contemporaneous seawater. The δ26Mg value is small (Min=−2.31‰). Powder crystal, fine-crystalline, and calcite dolostones with coarser and more ordered crystals exhibit similar δ13C and 87Sr/86Sr values to microbial and microcrystalline dolostone. During the sedimentary period of the Dengying Formation, ancient marine conditions were favorable for microbial survival. Microorganisms induced the direct precipitation of primary dolomite in seawater, forming microbial and microcrystalline dolostones during the seawater diagenesis period. During the subsequent diagenesis period, dolostones underwent the effects of dissolution-recrystallization, structures, and hydrothermal fluids. This resulted in the formation of dolostone with coarser crystals, a higher degree of order, and various types of cement. The Longwangmiao Formation was developed in an inter-platform beach characterized by special particle dolostone. The particle dolostone has a large grain size (>30 µm), high order degree (Min=0.7), small unit cell parameters, high Na content (Max=432 ppm), and low Fe and Mn content. The δ26Mg and δ13C values are consistent with the contemporaneous seawater, while the δ18O and 87Sr/86Sr values are higher than those of the contemporaneous seawater. There is mutual coupling between multiple-period varying δ26Mg values and sedimentary cycles. The dolostone in the Longwangmiao Formation resulted from the metasomatism of limestone by evaporated seawater. The thickness and scale of the dolostone in the Longwangmiao Formation are controlled by the periodic changes in sea level. The period of dolostone development from the Sinian to the Cambrian coincides with the transition from Rodinia's breakup to Gondwana's convergence. These events have resulted in vastly different marine properties, microbial activities, and sedimentary climate backgrounds between the Sinian and the Cambrian. These differences may be the fundamental factors leading to the distinct origins of dolostone formed in the two periods. The distribution of sedimentary facies and deep tectonic activities in the Sichuan Basin from the Sinian to the Cambrian is influenced by the breakup and convergence of the supercontinent. This process plays a key role in determining the distribution, pore formation, preservation, and adjustment mechanisms of ultra-deep dolostone reservoirs. To effectively analyze the genesis and reservoir mechanisms of ultra-deep dolostone in other regions or layers, especially during the specific period of supercontinent breakup and convergence, it is crucial to consider the comprehensive characteristics of seawater properties, microbial activities, sedimentary environment, and fault systems driven by tectonic activities. This can help predict the distribution of high-quality and large-scale ultra-deep dolostone reservoirs. [ABSTRACT FROM AUTHOR]

This paper analyzed the strong motion characteristics based on 86 three-component strong motion records of the MW 6.6 Luding earthquake. Additionally, the factors that influence the variation in ground motion for three earthquakes with similar magnitude in Sichuan Province were investigated. The analysis result indicates a strong correlation between the observed ground motion parameters and the distribution of published Modified Mercalli Intensity. The residual analysis reveals that the spectral accelerations at periods 0.1–10.0 s are amplified to 0.0798–0.3057 times the mean level in the rupture forward direction and weakened to 0.0738–0.2831 times the mean level in the rupture backward direction. The maximum pulse direction recorded by the 51LDJ station is N6°E, aligning with the vertical fault direction. The velocity pulses has distinct bidirectional pulses in the waveforms, with a PGV of 37.0 cm/s. The source effect of the strike-slip MW 6.6 Luding and MW 6.5 Jiuzhaigou earthquakes on ground motion is relatively less significant compared to the average level of mainshocks in southwest China. However, the thrust-fault MW 6.7 Lushan earthquake exhibits a stronger source effect on ground motion during short and medium periods, but a weaker source effect during long periods when compared to the average level. The anelastic attenuation of the Longmenshan, Xianshuihe, and Huya fault zones in Sichuan exhibits significant regional variation and periodic correlation. This phenomenon is closely linked to the regional tectonic background variations and the heterogeneity of crustal structure within the area. [ABSTRACT FROM AUTHOR]

Straw used to be an important raw material for heating, cooking, and raising livestock in rural areas. However, with the development of the economy, straw burning poses a great threat to the environment. Straw return is of great significance for realizing carbon peaks and carbon neutrality because of its ecological value and economic value. Based on the survey data of 540 households in Sichuan Province, China, the Probit model and CMP model are used to empirically analyze the influence of environmental policy on farmers' active straw return and its mechanism. The results show that: (1) 65.9% of farmers actively return straw to the field, and 34.1% of farmers passively return straw to the field. (2) environmental policies significantly promote farmers' initiative to return straw to the field, in which the influence of economic rewards and punishments is greater than that of administrative guidance. (3) Government propaganda and government training in government administrative guidance can promote farmers' active straw return by raising their awareness, with intermediary effects of 76.05% and 60.14%, respectively. (4) Female heads of households, high education level of heads of households, and high family income can also positively promote farmers' active straw return. [ABSTRACT FROM AUTHOR]

The Sichuan takin (Budorcas tibetanus) and the golden takin (Budorcas bedfordi) are endemic to China. Studies of their habitat ecology have attracted attention, but dedicated reviews of the topic have not been published. To fill this gap, research advances on the habitat ecology of these takin species were reviewed based on published journal papers from 2001–2022, covering habitat selection and use, as well as habitat assessment and protection. Habitat selection and use by the takins received the most frequent reports in a few protected areas, such as the Tangjiahe Nature Reserve in Sichuan and the Foping Nature Reserve in Shaanxi. Higher herb cover characterized some of the Sichuan takin habitats, while some of the golden takin population exhibited seasonal altitude migration. The focus on habitat assessment and protection differed between the two species. Studying the habitat of the Sichuan takin involves the relationship between its habitat and the protected areas and habitat status in various ranges while studying the habitat of the golden takin involves habitat distribution and change, protection effects, and corridor planning. Some issues worthy of consideration in future research are proposed, including basic habitat information, impacts of human disturbances, habitat restoration, and theoretical, independent, and comprehensive studies on both takins. Habitat conservation frameworks should be formulated for both takins to improve protection and restoration effects. This review provides convenient information to help understand the habitat characteristics of the two takins and is a reference for future research. [ABSTRACT FROM AUTHOR]

The rise of transnational and transcity education consumption suggests the increasingly important role of the capability to move in order to access quality schooling. Studies have examined the multidimensional inequalities underlying translocal education consumption. However, the role of mobility itself is not sufficiently understood. Two questions are rarely asked: (1) How is the capability to move acquired and practised to bring about translocal schooling consumption? and (2) How does the disparity in the capability to move restructure the established intergenerational capital transmission mechanism conceptualized by Bourdieu? This paper answers by theorizing a mobility-mediated, education-based intergenerational capital transmission mechanism. This framework is built upon a theoretical engagement among John Urry, Pierre Bourdieu, and Neil Smith. We substantiate this framework by examining a student migration regime in Sichuan, China. Attention is paid to the inclusion/exclusion of hypermobility-based schooling consumption regime. Empirical analysis is performed by the comparison of two social groups: (a) the middle-class households who employ mobility to chase after the footloose prime schooling resources and thus materialize their class reproduction strategy and (b) the immobile remainder who are stuck in a location deprived of quality schooling resources. [ABSTRACT FROM AUTHOR]

The unavoidable option for socially sustainable development is a low-carbon economy. One of the essential steps for China to attain high-quality development is reducing carbon emissions. It is necessary to realize low-carbon development in Sichuan, as it is not only an important economic zone but also an ecological protected area. The concurrent relationship among energy consumption, carbon emissions, and economic growth was examined in this study using the Tapio decoupling indicator, and the factors affecting energy consumption and carbon emissions in Sichuan were broken down using the logarithmic mean Divisia indicator (LMDI). The findings demonstrate a fundamental relative decoupling relationship between Sichuan's energy use and carbon emissions. Analysis of energy consumption and carbon emissions in Sichuan Province from 2005 to 2020 shows distinct patterns. From 2005 to 2012, in 2014, and from 2016 to 2020, the relationship between energy use and carbon emissions was relatively decoupled, with decoupling values ranging between 0 and 1. Absolute decoupling occurred in specific years: 2010, from 2013 to 2018, and in 2020. These periods are characterized by economic growth alongside reductions in carbon emissions. Factors affecting energy consumption and carbon emissions were consistently analyzed, showing similar impacts throughout the study periods. We find that population and economic growth are the main driving forces of these effects. The effects of energy intensity and industrial structure mainly play restraining roles, and the latter has a slightly weaker effect than the former. [ABSTRACT FROM AUTHOR]

A new Chengyuchelys latimarginalis (Xinjiangchelyidae) specimen is reported based on a well-preserved, nearly complete shell from the upper part of the Upper Jurassic Shangshaximiao Formation of Qijiang District, Chongqing Municipality, China. The Xinjiangchelyidae were widely distributed in Asia during the Jurassic and were the dominant turtle group in Asian freshwater ecosystems during the Late Jurassic. The Qijiang specimen adds a new element to the yet poorly known freshwater vertebrate fauna and extends the geographical distribution of C. latimarginalis. This paper discusses the intraspecific variation in C. latimarginalis for the first time. It provides a new insight for studying the evolution, habitat, and diversity of xinjiangchelyids. [ABSTRACT FROM AUTHOR]

More than 50 earthquakes occurred in the Luding region, including a 6.8‐magnitude earthquake on September 5, 2022, which induced huge amounts of geological disasters. As the main triggered factors for the geological disasters, the vegetation, precipitation and temperature show regular changes on the time axis. Thus, this paper based on the spatial–temporal evolution of the precipitation, temperature and normalized difference vegetation index (NDVI), focuses on the susceptibility of the Luding area using the weighted information content method (ICM) and analytic hierarchy process (AHP) for the post‐earthquake regional planning and reconstruction. In the Luding area, it was found that there were 18 debris flow gullies, and 470 geological disasters scattered in the debris flow gullies. The NDVI of the study area has been declining in recent years, with only about 12% of the NDVI increasing from 2015 to 2020. From 2011 to 2015, the annual cumulative precipitation has been dropping overall, while the July average temperature has increasing quadratic functions after decreasing trend. Furthermore, the studied area's geological hazards susceptibility was classified into five categories, with extremely low susceptibility accounting for 5.82%, low susceptibility accounting for 13.61%, moderate susceptibility accounting for 38.54%, high susceptibility accounting for 39.96% and extremely high susceptibility accounting for 2.08%. The geological disasters in moderate, high and extremely high susceptibility accounted for approximately 95.08%, and the covered area of geological disasters in moderate, high and extremely high susceptibility accounted for 88.06%. Through the receiver operating characteristic (ROC) curve of the model verification found the AUC = 0.743. The geological hazards susceptibility study results show that the approach is useful for the analysis and prevention of geological disasters. [ABSTRACT FROM AUTHOR]