Buoyancy-driven flows are prevalent in a wide range of geophysical and astrophysical systems. In this review, we focus on threepivotal effects that significantly influence the dynamics and transport properties of buoy...Buoyancy-driven flows are prevalent in a wide range of geophysical and astrophysical systems. In this review, we focus on threepivotal effects that significantly influence the dynamics and transport properties of buoyancy-driven flows and may have impli-cations for natural systems. These effects pertain to the role of boundary conditions, the impact of rotation, and the effect offinite size. Boundary conditions represent how the fluid flow interacts with different kinds of surfaces. Rotation, as the Earth’srotation in geophysical systems or the whirling of astrophysical systems, introduces Coriolis and centrifugal forces, leading tothe profound vortical structure and distinct transport property. Finite size, representing geometrical constraints, influences thebehavior of buoyancy-driven flows across varying geometrical settings. This review aims to provide a holistic understanding ofthe intricate interplay of these factors, offering insights into the complex natural phenomena from the perspectives of the threeeffects.展开更多
Landslides triggered by heavy rainfall pose a serious threat globally, endangering infrastructure and lives. Many previous landslide studies lack comprehensiveness and site specificity. Thus, a comprehensive investiga...Landslides triggered by heavy rainfall pose a serious threat globally, endangering infrastructure and lives. Many previous landslide studies lack comprehensiveness and site specificity. Thus, a comprehensive investigation is essential to understand the failure mechanisms and contributing factors for assessing potential future hazards. This study aims to investigate the debris flow landslide that occurred in Kavalappara, Kerala, India, on August 8, 2019, through an integrated approach combining geophysical test, weathering characterization, geotechnical, and numerical analyses. Shear wave velocity(V_s) was determined using the Multi-Channel Analysis of Surface Waves(MASW) test to obtain the substrata of the slope. Residual and unsaturated soil properties were obtained through ring shear and dew point potentiometer tests. The mineralogical composition of the soil was identified using Field-Emission Scanning Electron Microscopy(FE-SEM), Energy Dispersive XRay Analysis(EDAX), and X-Ray Diffraction(XRD) patterns. These investigation results focused on slope stability during rainfall infiltration using Limit Equilibrium(LEM) and Finite Element Analysis(FEM) for both low and high-intensity rainfall. Finally, the progressive failure mechanism of the landslide was analysed using the Finite Difference program(FDM). The soil profile showed a variation from loose to dense, with a V_(s) range of 172.85 m/s to 440.53 m/s. No rock layers were identified down to a depth of 15 m. The landslide area consists of migmatite as a parent rock, and the soil was identified as silty clay, comprising quartz and clay minerals. The FEM and LEM analyses reveal that the factor of safety was reduced to 0.83 due to increased pore water pressure and the degree of saturation. The pore water pressure ratio(r_(u)), estimated at 0.32, was used in the FDM. The landslide, initiated at r_u of 0.35, reached maximum velocities of 15.4 m/s horizontally and 12.4 m/s vertically. This study helps disaster management to analyse debris flow and find effective mitigation strategies for hilly areas.展开更多
Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transfo...Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.展开更多
Geophysical techniques play key roles in the measuring, monitoring, and verifying the safety of CO2 sequestration and in identifying the efficiency of CO2-enhanced oil recovery. Although geophysical monitoring techniq...Geophysical techniques play key roles in the measuring, monitoring, and verifying the safety of CO2 sequestration and in identifying the efficiency of CO2-enhanced oil recovery. Although geophysical monitoring techniques for CO2 sequestration have grown out of conventional oil and gas geophysical exploration techniques, it takes a long time to conduct geophysical monitoring, and there are many barriers and challenges. In this paper, with the initial objective of performing CO2 sequestration, we studied the geophysical tasks associated with evaluating geological storage sites and monitoring CO2 sequestration. Based on our review of the scope of geophysical monitoring techniques and our experience in domestic and international carbon capture and sequestration projects, we analyzed the inherent difficulties and our experiences in geophysical monitoring techniques, especially, with respect to 4D seismic acquisition, processing, and interpretation.展开更多
Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies...Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies. Large deviations between model and true edges are common because of the interference of depth and errors in computing the derivatives; thus, edge detection methods cannot provide information about the depth of the source. To simultaneously obtain the horizontal extent and depth of geophysical anomalies, we use normalized edge detection filters, which normalize the edge detection function at different depths, and the maxima that correspond to the location of the source. The errors between model and actual edges are minimized as the depth of the source decreases and the normalized edge detection method recognizes the extent of the source based on the maxima, allowing for reliable model results. We demonstrate the applicability of the normalized edge detection filters in defining the horizontal extent and depth using synthetic and actual aeromagnetic data.展开更多
2021年7月发射的风云三号E星(FY-3E)是世界首颗民用晨昏轨道气象卫星,其搭载的WindRAD双频测风雷达具有全球海面风场探测能力。本文首先基于FY-3E/WindRAD L1级观测资料,研究了雷达海面后向散射和风场之间的非线性关系,分别建立了适用于...2021年7月发射的风云三号E星(FY-3E)是世界首颗民用晨昏轨道气象卫星,其搭载的WindRAD双频测风雷达具有全球海面风场探测能力。本文首先基于FY-3E/WindRAD L1级观测资料,研究了雷达海面后向散射和风场之间的非线性关系,分别建立了适用于C和Ku波段VV/HH极化的地球物理模式函数(GMF)。随后,结合最大似然估计法(MLE)对WindRAD散射计探测资料进行风场反演。利用海洋浮标、中法海洋卫星散射计(CSCAT)和美国国家环境预报中心(NCEP)模式风场资料对WindRAD反演风场进行验证。结果显示:WindRAD反演风速与浮标风速偏差约为0.2 m s^(-1),均方根误差(RMSE)在1.13~1.44 m s^(-1)之间,优于2 m s^(-1)的业务化应用的风速精度要求;两者风向偏差在1.4°~3.0°之间,RMSE在25.3°~30.1°之间。WindRAD和CSCAT风场具有较好的一致性,风速RMSE在1.37~1.6 m s^(-1)之间,风向RMSE在22.9°~25.9°之间。WindRAD和NCEP模式风速RMSE在1.87~2.23 m s^(-1)之间,风向RMSE在22.4°~27.1°之间。研究表明WindRAD散射计C和Ku波段VV/HH极化反演风场均具有较高的精度,充分显示了WindRAD载荷在全球海面风场探测方面的应用潜力和价值。展开更多
基金supponted by the National Natural Science Foundation of China (Grant Nos 12202173,12072144,12232010,12372219,and 12302282).
文摘Buoyancy-driven flows are prevalent in a wide range of geophysical and astrophysical systems. In this review, we focus on threepivotal effects that significantly influence the dynamics and transport properties of buoyancy-driven flows and may have impli-cations for natural systems. These effects pertain to the role of boundary conditions, the impact of rotation, and the effect offinite size. Boundary conditions represent how the fluid flow interacts with different kinds of surfaces. Rotation, as the Earth’srotation in geophysical systems or the whirling of astrophysical systems, introduces Coriolis and centrifugal forces, leading tothe profound vortical structure and distinct transport property. Finite size, representing geometrical constraints, influences thebehavior of buoyancy-driven flows across varying geometrical settings. This review aims to provide a holistic understanding ofthe intricate interplay of these factors, offering insights into the complex natural phenomena from the perspectives of the threeeffects.
文摘Landslides triggered by heavy rainfall pose a serious threat globally, endangering infrastructure and lives. Many previous landslide studies lack comprehensiveness and site specificity. Thus, a comprehensive investigation is essential to understand the failure mechanisms and contributing factors for assessing potential future hazards. This study aims to investigate the debris flow landslide that occurred in Kavalappara, Kerala, India, on August 8, 2019, through an integrated approach combining geophysical test, weathering characterization, geotechnical, and numerical analyses. Shear wave velocity(V_s) was determined using the Multi-Channel Analysis of Surface Waves(MASW) test to obtain the substrata of the slope. Residual and unsaturated soil properties were obtained through ring shear and dew point potentiometer tests. The mineralogical composition of the soil was identified using Field-Emission Scanning Electron Microscopy(FE-SEM), Energy Dispersive XRay Analysis(EDAX), and X-Ray Diffraction(XRD) patterns. These investigation results focused on slope stability during rainfall infiltration using Limit Equilibrium(LEM) and Finite Element Analysis(FEM) for both low and high-intensity rainfall. Finally, the progressive failure mechanism of the landslide was analysed using the Finite Difference program(FDM). The soil profile showed a variation from loose to dense, with a V_(s) range of 172.85 m/s to 440.53 m/s. No rock layers were identified down to a depth of 15 m. The landslide area consists of migmatite as a parent rock, and the soil was identified as silty clay, comprising quartz and clay minerals. The FEM and LEM analyses reveal that the factor of safety was reduced to 0.83 due to increased pore water pressure and the degree of saturation. The pore water pressure ratio(r_(u)), estimated at 0.32, was used in the FDM. The landslide, initiated at r_u of 0.35, reached maximum velocities of 15.4 m/s horizontally and 12.4 m/s vertically. This study helps disaster management to analyse debris flow and find effective mitigation strategies for hilly areas.
基金supported by the National Natural Science Foundation of China (Grant No.41074133)
文摘Missing data are a problem in geophysical surveys, and interpolation and reconstruction of missing data is part of the data processing and interpretation. Based on the sparseness of the geophysical data or the transform domain, we can improve the accuracy and stability of the reconstruction by transforming it to a sparse optimization problem. In this paper, we propose a mathematical model for the sparse reconstruction of data based on the LO-norm minimization. Furthermore, we discuss two types of the approximation algorithm for the LO- norm minimization according to the size and characteristics of the geophysical data： namely, the iteratively reweighted least-squares algorithm and the fast iterative hard thresholding algorithm. Theoretical and numerical analysis showed that applying the iteratively reweighted least-squares algorithm to the reconstruction of potential field data exploits its fast convergence rate, short calculation time, and high precision, whereas the fast iterative hard thresholding algorithm is more suitable for processing seismic data, moreover, its computational efficiency is better than that of the traditional iterative hard thresholding algorithm.
基金supported by National 863 Program Grant 2012AA050103 and Grant 2011KTCQ03-09
文摘Geophysical techniques play key roles in the measuring, monitoring, and verifying the safety of CO2 sequestration and in identifying the efficiency of CO2-enhanced oil recovery. Although geophysical monitoring techniques for CO2 sequestration have grown out of conventional oil and gas geophysical exploration techniques, it takes a long time to conduct geophysical monitoring, and there are many barriers and challenges. In this paper, with the initial objective of performing CO2 sequestration, we studied the geophysical tasks associated with evaluating geological storage sites and monitoring CO2 sequestration. Based on our review of the scope of geophysical monitoring techniques and our experience in domestic and international carbon capture and sequestration projects, we analyzed the inherent difficulties and our experiences in geophysical monitoring techniques, especially, with respect to 4D seismic acquisition, processing, and interpretation.
基金supported by the China Postdoctoral Science Foundation (No.2014M551188)the Deep Exploration in China Sinoprobe-09-01 (No.201011078)
文摘Edge detection is an image processing technique for finding the boundaries of objects within images. It is typically used to interpret gravity and magnetic data, and find the horizontal boundaries of geological bodies. Large deviations between model and true edges are common because of the interference of depth and errors in computing the derivatives; thus, edge detection methods cannot provide information about the depth of the source. To simultaneously obtain the horizontal extent and depth of geophysical anomalies, we use normalized edge detection filters, which normalize the edge detection function at different depths, and the maxima that correspond to the location of the source. The errors between model and actual edges are minimized as the depth of the source decreases and the normalized edge detection method recognizes the extent of the source based on the maxima, allowing for reliable model results. We demonstrate the applicability of the normalized edge detection filters in defining the horizontal extent and depth using synthetic and actual aeromagnetic data.
文摘2021年7月发射的风云三号E星(FY-3E)是世界首颗民用晨昏轨道气象卫星,其搭载的WindRAD双频测风雷达具有全球海面风场探测能力。本文首先基于FY-3E/WindRAD L1级观测资料,研究了雷达海面后向散射和风场之间的非线性关系,分别建立了适用于C和Ku波段VV/HH极化的地球物理模式函数(GMF)。随后,结合最大似然估计法(MLE)对WindRAD散射计探测资料进行风场反演。利用海洋浮标、中法海洋卫星散射计(CSCAT)和美国国家环境预报中心(NCEP)模式风场资料对WindRAD反演风场进行验证。结果显示:WindRAD反演风速与浮标风速偏差约为0.2 m s^(-1),均方根误差(RMSE)在1.13~1.44 m s^(-1)之间,优于2 m s^(-1)的业务化应用的风速精度要求;两者风向偏差在1.4°~3.0°之间,RMSE在25.3°~30.1°之间。WindRAD和CSCAT风场具有较好的一致性,风速RMSE在1.37~1.6 m s^(-1)之间,风向RMSE在22.9°~25.9°之间。WindRAD和NCEP模式风速RMSE在1.87~2.23 m s^(-1)之间,风向RMSE在22.4°~27.1°之间。研究表明WindRAD散射计C和Ku波段VV/HH极化反演风场均具有较高的精度,充分显示了WindRAD载荷在全球海面风场探测方面的应用潜力和价值。
