联合GNSS和InSAR观测位移反演2008年汶川大地震断层位错模型参数     

伍吉仓  宋鑫友  胡凤鸣  宋瑞庆 《中国地震》2020,36(4):767-779

利用现代空间大地测量技术,尤其是卫星合成孔径雷达干涉测量,能够获取高精度、高空间分辨率的同震和孕震形变,为地震断层形变和破裂机制研究提供了前所未有的机遇。本文介绍了利用大地测量观测数据反演地震断层位错模型参数的贝叶斯反演方法。联合运用2008汶川大地震前后GNSS和InSAR技术观测获得的同震位移,反演了地震断层的几何参数和滑动位错分布。研究结果表明,汶川地震的断层滑动主要集中在倾角较陡的浅部,同时包含逆冲和右旋走滑,其中最大逆冲6.1m,最大右旋6.5m。根据断层滑动分布正演计算得到的上盘同震位移明显小于下盘,预示该断层两侧孕震形变可能存在较大的不对称性。  相似文献   

The influence of channel morphology on bedload path lengths: Insights from a survival process model     

Conor McDowell  Marwan A. Hassan 《地球表面变化过程与地形》2020,45(12):2982-2997

Tracer studies are a commonly used tool to develop and test Einstein-type stochastic bedload transport models. The movements of these tracers are controlled by many factors including grain characteristics, hydrologic forcing, and channel morphology. Although the influence of these sediment storage zones related to morphological features (e.g., bars, pools, riffles) have long been observed to “trap” bedload particles in transport, this influence has not been adequately quantified. In this paper we explore the influence of channel morphology on particle travel distances through the development of a Bayesian survival process model. This model simulates particle path length distributions using a location-specific “trapping probability” parameter (p_i ), which is estimated using the starting and ending locations of bedload tracers. We test this model using a field tracer study from Halfmoon Creek, Colorado. We find that (1) the model is able to adequately recreate the observed multi-modal path length distributions, (2) particles tend to accumulate in trapping zones, especially during large floods, and (3) particles entrained near a trapping zone will travel a shorter distance than one that is further away. Particle starting positions can affect path lengths by as much as a factor of two, which we confirm by modelling “starting-location-specific” path length probability distributions. This study highlights the importance of considering both tracer locations and channel topography in examinations of field tracer studies. © 2020 John Wiley & Sons, Ltd.  相似文献   

Combining discrete cosine transform and convolutional neural networks to speed up the Hamiltonian Monte Carlo inversion of pre-stack seismic data     

Mattia Aleardi 《Geophysical Prospecting》2020,68(9):2738-2761

Markov chain Monte Carlo algorithms are commonly employed for accurate uncertainty appraisals in non-linear inverse problems. The downside of these algorithms is the considerable number of samples needed to achieve reliable posterior estimations, especially in high-dimensional model spaces. To overcome this issue, the Hamiltonian Monte Carlo algorithm has recently been introduced to solve geophysical inversions. Different from classical Markov chain Monte Carlo algorithms, this approach exploits the derivative information of the target posterior probability density to guide the sampling of the model space. However, its main downside is the computational cost for the derivative computation (i.e. the computation of the Jacobian matrix around each sampled model). Possible strategies to mitigate this issue are the reduction of the dimensionality of the model space and/or the use of efficient methods to compute the gradient of the target density. Here we focus the attention to the estimation of elastic properties (P-, S-wave velocities and density) from pre-stack data through a non-linear amplitude versus angle inversion in which the Hamiltonian Monte Carlo algorithm is used to sample the posterior probability. To decrease the computational cost of the inversion procedure, we employ the discrete cosine transform to reparametrize the model space, and we train a convolutional neural network to predict the Jacobian matrix around each sampled model. The training data set for the network is also parametrized in the discrete cosine transform space, thus allowing for a reduction of the number of parameters to be optimized during the learning phase. Once trained the network can be used to compute the Jacobian matrix associated with each sampled model in real time. The outcomes of the proposed approach are compared and validated with the predictions of Hamiltonian Monte Carlo inversions in which a quite computationally expensive, but accurate finite-difference scheme is used to compute the Jacobian matrix and with those obtained by replacing the Jacobian with a matrix operator derived from a linear approximation of the Zoeppritz equations. Synthetic and field inversion experiments demonstrate that the proposed approach dramatically reduces the cost of the Hamiltonian Monte Carlo inversion while preserving an accurate and efficient sampling of the posterior probability.  相似文献   

Inversion-based deblending using migration operators     

Amr Ibrahim  Daniel Trad 《Geophysical Prospecting》2020,68(8):2459-2470

In this paper, we compare the denoising- and inversion-based deblending methods using Stolt migration operators. We use Stolt operator as a kernel to efficiently compute apex-shifted hyperbolic Radon transform. Sparsity promoting transforms, such as Radon transform, can focus seismic data into a sparse model to separate signals, remove noise or interpolate missing traces. Therefore, Radon transforms are a suitable tool for either the denoising- or the inversion-based deblending methods. The denoising-based deblending treats blending interferences as random noise by sorting the data into new gathers, such as common receiver gather. In these gathers, blending interferences exhibit random structures due to the randomization of the source firing times. Alternatively, the inversion-based deblending treats blending interferences as a signal, and the transform models this signal by incorporating the blending operator to formulate an inversion problem. We compare both methods using a robust inversion algorithm with sparse regularization. Results of synthetic and field data examples show that the inversion-based deblending can produce more accurate signal separation for highly blended data.  相似文献   

基于贝叶斯定理的地震危险性概率预测研究     

邓世广  周龙泉  马亚伟  臧阳  王月  韩颜颜 《中国地震》2019,35(1):1-13

由于地震孕育过程的复杂性和观测技术的局限性,不同地震观测资料表现出异常变化与后续较大地震的对应关系存在不确定性,因此对预测意见进行概率表达是一种科学恰当的做法。本文基于泊松分布的危险区背景地震概率预测和单项预测方法(包括测震、流体、形变、电磁等学科)的历史预测效能,采用贝叶斯定理计算得到单项预测方法的短期或年度地震危险概率预测结果,进而采用综合概率方法,给出基于多种单项预测方法的短期或年度地震危险概率预测结果。短期概率预测初步结果表明,2018年2～9月,中国大陆72%的5级以上地震都位于相对高概率预测区域。  相似文献   

基于贝叶斯方法的贵州高原百花水库水体营养盐变化及评价(2014—2018年)     

袁振辉  李秋华  何应  马欣洋  韩孟书  孙荣国  张华俊 《湖泊科学》2019,31(6):1623-1636

为了确定百花水库营养盐变化特征,选取百花水库5个监测点2014年1月-2018年7月共28个月份的水质实测数据,分析溶解氧、高锰酸盐指数、氨氮、总磷和总氮的年际变化特征.采用基于熵权法赋权的贝叶斯理论对5个监测点的水质综合状况进行评价,并结合水库的实际状况,从生态修复、工业污染源、沉积物中营养盐、水库季节性热分层及农业与生活污染源5个方面对其水质变化的影响因素进行分析.结果表明:2014-2018年水体环境波动较大;除总氮外,各污染指标浓度均有不同程度的下降;综合水质后验概率表明百花水库水质有逐渐变差的趋势;总氮和总磷治理应成为百花水库污染治理的主要方面;生态修复工程的开展和工业污染源的削减是百花水库水质转好的主要影响因素,农业与生活污染源的增加是百花水库水质转差的主要影响因素.  相似文献   

Discard management: A spatial multi-criteria approach     

《Marine Policy》2017

Discard management needs to draw on scientific research and advice, usually supported by specific statistical modeling analysis. A wide range of statistical analysis methods were applied to fishery data in an attempt to distinguish factors that influence the species discard composition. While such approaches are important, they are still incomplete for disaggregating the economic and spatial-temporal factors for analyzing of this process and obtain a whole view of this issue. Our study aims to fill this gap by identifying, describing, and quantifying factors that influence discards of trawl fisheries using a multivariate approach based on five complementary aspects: “economic”, “vessel characteristics”, “spatial”, “temporal” and “environmental”. In addition, a spatial multi-criteria approach were used to investigate discard hot-spot areas using ecological criteria such as vulnerability and resilience of the discarded species. Using these ecological criteria will concentrate conservation efforts on the most relevant sites minimizing discards of a variety of potentially vulnerable species. This approach was applied to a case study of a multi-species demersal bottom trawl fisheries in north Spain, Cantabrian Sea (ICES area VIIIc). Results showed how spatial and economic factors highly affect species discard composition, identifying specific spatial-temporal discard hot-spots to be preferentially avoided by fishers. Mitigation measures for future fisheries management strategies should be implemented at multiple stages of the discarding process, both in the selection of the fishing grounds and the economic valorization of the discarded species.  相似文献   

利用限制性最大似然方法和贝叶斯方法估计大菱鲆生长性状的遗传参数。   总被引：1，自引：0，他引：1  

官健涛  王伟继  胡玉龙  王陌桑  田涛  孔杰 《海洋学报(英文版)》2017,36(6):47-51

Bayesian and restricted maximum likelihood(REML) approaches were used to estimate the genetic parameters in a cultured turbot Scophthalmus maximus stock. The data set consisted of harvest body weight from 2 462progenies(17 months old) from 28 families that were produced through artificial insemination using 39 parent fish. An animal model was applied to partition each weight value into a fixed effect, an additive genetic effect, and a residual effect. The average body weight of each family, which was measured at 110 days post-hatching, was considered as a covariate. For Bayesian analysis, heritability and breeding values were estimated using both the posterior mean and mode from the joint posterior conditional distribution. The results revealed that for additive genetic variance, the posterior mean estimate( δ_a~2=9 320) was highest but with the smallest residual variance,REML estimates( δ_a~2=8 088) came second and the posterior mode estimate( δ_a~2=7 849) was lowest. The corresponding three heritability estimates followed the same trend as additive genetic variance and they were all high. The Pearson correlations between each pair of the three estimates of breeding values were all high,particularly that between the posterior mean and REML estimates(0.996 9). These results reveal that the differences between Bayesian and REML methods in terms of estimation of heritability and breeding values were small. This study provides another feasible method of genetic parameter estimation in selective breeding programs of turbot.  相似文献   

Learning soil parameters and updating geotechnical reliability estimates under spatial variability – theory and application to shallow foundations     

Iason Papaioannou  Daniel Straub 《Georisk: Assessment and Management of Risk for Engineered Systems and Geohazards》2017,11(1):116-128

ABSTRACT

Field data is commonly used to determine soil parameters for geotechnical analysis. Bayesian analysis allows combining field data with other information on soil parameters in a consistent manner. We show that the spatial variability of the soil properties and the associated measurements can be captured through two different modelling approaches. In the first approach, a single random variable (RV) represents the soil property within the area of interest, while the second approach models the spatial variability explicitly with a random field (RF). We apply the Bayesian concept exemplarily to the reliability assessment of a shallow foundation in a silty soil with spatially variable data. We show that the simpler RV approach is applicable in cases where the measurements do not influence the correlation structure of the soil property at the vicinity of the foundation. In other cases, it is expected to underestimate the reliability, and a RF model is required to obtain accurate results.  相似文献   

基于数据规则化和稀疏反演的三维表面多次波压制方法          下载免费PDF全文

方云峰  聂红梅  张丽梅  唐博文  王增波 《地球物理学报》2016,59(2):673-681

表面多次波是海洋地震勘探中的主要问题.目前,二维数据驱动的表面多次波压制技术(SRME)已经比较成熟,并且已经成为工业界压制海洋表面多次波的主流方法.但是由于二维SRME算法没有考虑横测线方向上多次波的贡献,导致在处理实际三维海洋资料时存在比较大的误差.将二维SRME算法扩展到三维空间后可以得到三维SRME算法,但是由于目前实际采集的三维海洋资料的观测系统存在拖缆漂移,而且横测线方向采样过于稀疏,直接应用三维SRME算法无法准确预测表面多次波.本文提出的通过数据规则化配合稀疏反演的三维表面多次波压制方法能够解决这种实际资料和三维SRME算法之间的矛盾.本文通过研究数据规则化与反规则化技术,使得数据分布满足三维SRME的要求;通过研究稀疏反演技术,有效解决了横测线方向采样稀疏对于多次波预测的影响,三维实际海洋资料的应用结果验证了方法的有效性和可行性.  相似文献