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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]

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To improve the accuracy of data processing and interpretation, effective suppression of the regional background field and extraction of the local anomaly field for further analyses represent urgent issues that need to be solved in the wide-field electromagnetic methods. The present study proposes an anomaly separation technique based on the residual method to develop the basic idea of regional field separation in gravity and magnetic exploration. The proposed technique can effectively suppress the regional background field and highlight local anomalies, such as faults and thin layers in inversion imaging, overcoming the shortcomings of traditional interpretation methods. Based on the interpolation-cutting method, a dynamically improved interpolation-cutting operator is proposed to obtain the regional background field by separating it from the local anomaly field. Furthermore, one- and two-dimensional complex geoelectric models are designed to perform calculations, inverse imaging, and anomaly separation. It has been demonstrated that the local anomaly information extracted by the anomaly separation technology describes accurate strata, structures, and faults, obviously superior to the traditional processing results. The proposed method is used to separate the anomalies from the wide-field electromagnetic inversion imaging in the Changning area of the southern Sichuan Province. The local information of the structures, thin layers, and faults obtained by the anomaly separation results is highly consistent with the seismic profile, indicating that the proposed anomaly separation technology is effective and reliable. Further, the proposed technology can effectively improve the inversion imaging accuracy and the interpretation reliability of traditional wide-field electromagnetic methods; thus, it has important application value. [ABSTRACT FROM AUTHOR]

Previous studies on optical remote sensing mapping of landslides mainly focused on new landslides that have occurred, but little attention was paid to the early landslide due to its high concealment. InSAR technology, a prevalent method to detect early landslides, only can be used to identify the potential hazards of slow deformation. Therefore, it is necessary to explore new method of early landslides mapping by integrating all types of direct and indirect early features, such as cracks on slopes, small collapses inside and topographic features. In this study, an object-oriented image analysis method based on slope unit division and multi-scale segmentation was proposed to obtain accurate location and boundary extraction of early landslides. In the middle- and small-scale segmentation, the object, texture, spectrum, geometric features, topographic features, and other features were obtained to determine the local feature location of early landslides. The slope unit boundary was combined with the feature of a large-scale segmentation object to determine the scope of landslides. This method was tested in the Xianshui River basin in the Daofu County, Sichuan Province, China. The results demonstrate that: (1) Such features as landslide cracks and the small collapse at the bottom of slope can effectively determine the landslide position. (2) The slope unit division and the correct setting of shape factors in multiple segmentation can effectively determine the landslide boundary. (3) The accuracy of landslide location extraction was 83.33%, and the accuracy of boundary extraction for early landslides that were completely identified was evaluated as 82.67%. It is indicated that this method can improve the accuracy of boundary extraction and meet the requirements of the early landslides mapping. [ABSTRACT FROM AUTHOR]

How to acquire landslide disaster information quickly and accurately has become the focus and difficulty of disaster prevention and relief by remote sensing. Landslide disasters are generally featured by sudden occurrence, proposing high demand for emergency data acquisition. The low-altitude Unmanned Aerial Vehicle (UAV) remote sensing technology is widely applied to acquire landslide disaster data, due to its convenience, high efficiency, and ability to fly at low altitude under cloud. However, the spectrum information of UAV images is generally deficient and manual interpretation is difficult for meeting the need of quick acquisition of emergency data. Based on this, UAV images of high-occurrence areas of landslide disaster in Wenchuan County and Baoxing County in Sichuan Province, China were selected for research in the paper. Firstly, the acquired UAV images were pre-processed to generate orthoimages. Subsequently, multi-resolution segmentation was carried out to obtain image objects, and the barycenter of each object was calculated to generate a landslide sample database (including positive and negative samples) for deep learning. Next, four landslide feature models of deep learning and transfer learning, namely Histograms of Oriented Gradients (HOG), Bag of Visual Word (BOVW), Convolutional Neural Network (CNN), and Transfer Learning (TL) were compared, and it was found that the TL model possesses the best feature extraction effect, so a landslide extraction method based on the TL model and object-oriented image analysis (TLOEL) was proposed; finally, the TLOEL method was compared with the object-oriented nearest neighbor classification (NNC) method. The research results show that the accuracy of the TLOEL method is higher than the NNC method, which can not only achieve the edge extraction of large landslides, but also detect and extract middle and small landslides accurately that are scatteredly distributed. [ABSTRACT FROM AUTHOR]

The current fluid imbibition models used in shale usually assume a pore shape to be circular, whereas the pore shapes significantly deviate from that. One approach to correct this deviation is to introduce a pore shape factor into the models although it is challenging. This paper provides a way to calculate the specific shape factors of irregular inorganic and organic pores in shale based on SEM images analyses. Then, combining with the percentages of the organic and inorganic pores, a group of weighted-average pore shape factors of Longmaxi shale samples was calculated (0.587～0.667). Another group of pore shape factors (0.359～0.615) was also matched from the shale fluid imbibition curves, close to the previous values, which confirmed the validity of the proposed method. This work may provide an effective support in exploring the fluid imbibition or flow mechanisms in shale, especially considering the strong pore wall effects under nano-scale. • A method is provided to calculate the shape factors of irregular inorganic and organic pores. • The pore shape factor of organic pores is commonly higher than that of inorganic pores. • Ignoring the pore shape factor may cause an overestimation in fluid imbibition volume prediction. [ABSTRACT FROM AUTHOR]

Recovering from major earthquakes is a challenge, especially in mountainous environments where postearthquake hazards may cause substantial impacts for prolonged periods of time. Although such impacts were reported in the 1923 Great Kantō earthquake and the 1999 Chi-Chi earthquake, careless reconstruction in hazard-prone areas and consequently huge losses were witnessed following the 2008 Wenchuan earthquake in the Sichuan province of China, as several reconstructed settlements were severely damaged by mass movements and floods. In order to summarize experiences and identify problems in the reconstruction planning, a monitoring of one of the settlements, the town of Longchi, was carried out by image interpretation and field investigation. Seven inventories containing buildings, farmlands, roads and mitigation measures were made to study the dynamics of elements at risk and exposure over a period of 11 years. It was found that the total economic value of the newly reconstructed buildings was several times more than in the preearthquake situation in 2007, because of enormous governmental investment. Postseismic hazards were not sufficiently taken into consideration in the recovery planning before the catastrophic debris flow disaster in 2010. As a result, the direct economic loss from postseismic disasters was slightly more than the loss caused by the Wenchuan earthquake itself. The society showed an impact-adapt pattern, experiencing losses from disasters and then gaining resistance by abandoning buildings in hazard-prone areas and installing mitigation measures. The locations potentially exposed to postearthquake hazards were summarized, and a possible timetable for reconstruction was proposed. Problems might be encountered in hazard assessment, and possible solutions were discussed. [ABSTRACT FROM AUTHOR]