Automatic stacking‐velocity estimation using similarity‐weighted clustering          下载免费PDF全文

Guochang Liu  Chao Li  Xingye Liu  Qiang Ge  Xiaohong Chen 《Geophysical Prospecting》2018,66(4):649-663

Local seismic event slopes contain subsurface velocity information and can be used to estimate seismic stacking velocity. In this paper, we propose a novel approach to estimate the stacking velocity automatically from seismic reflection data using similarity‐weighted k‐means clustering, in which the weights are local similarity between each trace in common midpoint gather and a reference trace. Local similarity reflects the local signal‐to‐noise ratio in common midpoint gather. We select the data points with high signal‐to‐noise ratio to be used in the velocity estimation with large weights in mapped traveltime and velocity domain by similarity‐weighted k‐means clustering with thresholding. By using weighted k‐means clustering, we make clustering centroids closer to those data points with large weights, which are more reliable and have higher signal‐to‐noise ratio. The interpolation is used to obtain the whole velocity volume after we have got velocity points calculated by weighted k‐means clustering. Using the proposed method, one obtains a more accurate estimate of the stacking velocity because the similarity‐based weighting in clustering takes into account the signal‐to‐noise ratio and reliability of different data points in mapped traveltime and velocity domain. In order to demonstrate that, we apply the proposed method to synthetic and field data examples, and the resulting images are of higher quality when compared with the ones obtained using existing methods.  相似文献   

2016年8月24日意大利佩鲁贾MW 6.2级地震同震位移场估计和震源滑动模型反演     

黎朕灵  金明培  缪素秋 《地球物理学进展》2020,(1):32-39

利用改进的自动经验基线校正方法SMBLOC,对2016年8月24日意大利佩鲁贾MW 6.2级地震震中周围约60 km内的近场强震记录进行基线校正并尝试给出同震位移场,与GPS观测结果进行对比分析,分别独立和联合两种资料反演震源滑动模型,并根据震源模型进一步给出全空间预测位移场分布.研究结果表明:(1)两种不同的资料给出的水平位移场幅值均为cm级,且均表明断层的错动以正断为主.(2)两种同震位移场分别独立和联合反演所得的震源静态滑动范围基本一致,最大滑动均发生在震中东北侧,强震模型表现出明显的双事件特征,较大滑动分布在震中东北侧和东南侧,GPS模型在震中东南侧的滑动相对较小,其双事件特征不明显.两种模型的最大滑动量分别为0.96 m和0.86 m,较为一致,反演的矩震级均在MW 6.3左右.(3)根据震源滑动模型计算所得的佩鲁贾地震全空间预测的水平同震位移场中最大位移分布区域与震后报告中受灾严重的地区基本一致.表明在一定的条件下,利用SMBLOC方法解算震级较小的MW 6.0左右地震强震记录的同震位移场,并反演震源滑动模型具有一定的可行性,且其同震位移场和滑动模型可为震后灾害快速评估、救援力量分配、余震趋势判定等快速应急响应工作提供参考依据.  相似文献   

天然地震识别与震相自动拾取技术进展     

孙印  潘素珍  刘明军 《中国地震》2018,34(4):606-620

震相拾取是地震数据处理过程中最基本的步骤之一。在传统的人工拾取技术不能满足庞大的地震数据处理需求的情况下,震相自动拾取技术从产生到发展至今经历了漫长的过程。本文回顾并总结了震相自动拾取技术的发展状况,重点介绍了长短时窗法、赤池准则法、模板匹配技术、基于自相关盲搜索的FAST法、S波偏振分析法、人工智能方法等,以及近年发展起来的多频率震相识别、全波形叠加、二次方自回归模型等方法,同时分析了每种方法的优势和局限性。  相似文献   

Active Source Seismic Identification and Automatic Picking of the P-wave First Arrival Using a Convolutional Neural Network   总被引：1，自引：1，他引：0  

XU Zhen  WANG Tao  XU Shanhui  WANG Baoshan  FENG Xuping  SHI Jing  YANG Minghan 《中国地震研究》2019,33(2):288-304

In seismic data processing, picking of the P-wave first arrivals takes up plenty of time and labor, and its accuracy plays a key role in imaging seismic structures. Based on the convolution neural network (CNN), we propose a new method to pick up the P-wave first arrivals automatically. Emitted from MINI28 vibroseis in the Jingdezhen seismic experiment, the vertical component of seismic waveforms recorded by EPS 32-bit portable seismometers are used for manually picking up the first arrivals (a total of 7242). Based on these arrivals, we establish the training and testing sets, including 25,290 event samples and 710,616 noise samples (length of each sample:2s). After 3,000 steps of training, we obtain a convergent CNN model, which can automatically classify seismic events and noise samples with high accuracy (> 99%). With the trained CNN model, we scan continuous seismic records and take the maximum output (probability of a seismic event) as the P-wave first arrival time. Compared with STA/LTA (short time average/long time average), our method shows higher precision and stronger anti-noise ability, especially with the low SNR seismic data. This CNN method is of great significance for promoting the intellectualization of seismic data processing, improving the resolution of seismic imaging, and promoting the joint inversion of active and passive sources.  相似文献   

基于S变换和瞬时旅行时属性的自动初至拾取方法研究     

陈常乐  刘财  胡婷  刘洋 《世界地质》2015,34(1):219-225

地震波走时拾取是地震资料前期处理过程中的一个重要步骤,同时也是后期层析成像方法中计算速度的重要依据。本文提出了一种新的自动初至拾取的方法,利用地震信号的瞬时旅行时属性进行地震波自动初至拾取,瞬时旅行时属性的计算包括两个独立但相关联的部分,首先通过S变换将地震信号转换到时频域,然后利用映射算子将时频域表征映像回时间域得到瞬时旅行时,从而实现自动拾取初至。理论模型和实际地震资料处理的结果表明,该方法可以有效地拾取地震波初至时间。  相似文献   

江苏省能见度的人工与自动观测差异分析   总被引：1，自引：1，他引：0  

王瑞  周学东  李崇志  许小川  于清平  王佳 《气象科学》2015,35(2):183-188

对江苏省2011年全年逐时能见度的自动、人工观测数据进行了统计分析,结果表明:二者具有相当一致的统计特征,全省总相关系数0.73,一致率95.03%;但亦存在一定差异,整体上人工较自动观测数据偏大数公里,偏大程度在17%~55%,且空间差异显著;对不同条件下能见度的对比分析显示,自动与人工观测在低能见度条件下最为接近,且二者差异存在着明显的日变化特征;对能见度自动与人工观测偏差长序列的初步分析,显示统计订正是可能的,但对于不同级别的能见度,自动观测相对与人工有不同的倾向。  相似文献   

Semi-automated stand delineation in Mediterranean Pinus sylvestris plantations through segmentation of LiDAR data: The influence of pulse density     

《International Journal of Applied Earth Observation and Geoinformation》2017

Traditionally, forest-stand delineation has been assessed based on orthophotography. The application of LiDAR has improved forest management by providing high-spatial-resolution data on the vertical structure of the forest. The aim of this study was to develop and test a semi-automated algorithm for stands delineation in a plantation of Pinus sylvestris L. using LiDAR data. Three specific objectives were evaluated, i) to assess two complementary LiDAR metrics, Assmann dominant height and basal area, for the characterization of the structure of P. sylvestris Mediterranean forests based on object-oriented segmentation, ii) to evaluate the influence of the LiDAR pulse density on forest-stand delineation accuracy, and iii) to investigate the algorithmś effectiveness in the delineation of P. sylvestris stands for map prediction of Assmann dominant height and basal area. Our results show that it is possible to generate accurate P. sylvestris forest-stand segmentations using multiresolution or mean shift segmentation methods, even with low-pulse-density LiDAR − which is an important economic advantage for forest management. However, eCognition multiresolution methods provided better results than the OTB (Orfeo Tool Box) for stand delineation based on dominant height and basal area estimations. Furthermore, the influence of pulse density on the results was not statistically significant in the basal area calculations. However, there was a significant effect of pulse density on Assmann dominant height [F_2,9595 = 5.69, p = 0.003].for low pulse density. We propose that the approach shown here should be considered for stand delineation in other large Pinus plantations in Mediterranean regions with similar characteristics.  相似文献   

基于优化参数的地震P、S波震相到时自动拾取及质量评估   总被引：2，自引：0，他引：2       下载免费PDF全文

杨旭  李永华  苏伟  孙莲 《地球物理学报》2019,62(11):4290-4299

准确拾取P、S波震相到时是深入开展地震波研究工作的基础，本文改进了自动拾取参数优化函数算法和质量评估方案，引入了拾取到时优化方案，使用基于参数优化的频带-带宽拾取算法、AICD拾取算法和峰度拾取算法对腾冲地区7个宽频带地震台站记录的地震资料开展了地震P、S波到时自动拾取，对拾取结果进行了优化和质量判定.结果表明：经参数优化、拾取优化后，采用3种方法自动拾取的P、S波到时与人工拾取到时的时差在0.1 s内的记录占比分别达到74.66%、70.98%.这些参数值均优于算法改进前的同类参数，证明了优化方法的可靠性.  相似文献   

基于稀疏反演理论的自动叠加速度反演方法          下载免费PDF全文

徐文君  殷俊锋  王华忠  冯波 《地球物理学报》2017,60(7):2791-2800

叠加速度分析技术是常规地震资料处理中的重要环节,也是经典的时间域速度建模方法.叠加速度分析技术主要包括速度谱计算和拾取两个步骤.至今为止,多数研究工作通过提高速度谱的分辨率以及抗噪声能力,获得高质量的速度谱从而有利于拾取.本文的目标是将叠加速度分析技术转为一个全自动化的处理流程.从参数估计的角度出发,将叠加速度估计转化为稀疏反演框架下的模型参数估计问题,并通过稀疏反演算法自动反演叠加速度,进而提高叠加速度建模的效率.为实现这一目标,首先给出了正问题的定义,即层状介质中CMP道集的预测模型,利用叠加速度、垂向双程走时(t_0)以及反射子波以及CMP道集时距关系(如双曲时距关系)可以预测CMP道集.接着,速度分析反问题可以描述为已知观测的CMP道集,估计模型参数(叠加速度及t_0时间等).利用模型参数的稀疏性作为约束条件并用L_0范数作为模型稀疏性的度量准则,叠加速度分析可以转化为L_0范数约束下的稀疏反演问题.本文提出了一种基于预测校正思想的匹配追踪算法求解上述反问题,实现了自动叠加速度建模并为后续的高精度速度反演方法提供较好的初始模型.理论和实际资料的测试结果证明了本文方法的有效性.  相似文献   

基于雷达三维组网数据的对流性地面大风自动识别   总被引：4，自引：1，他引：3  

李国翠  刘黎平  张秉祥  于楠  常山英 《气象学报》2013,71(6):1160-1171

应用雷达三维组网数据和地面加密自动站风场资料,统计分析了对流性地面大风的6个主要雷达识别指标：风暴最大反射率因子、风暴最大垂直积分液态水含量、垂直积分液态水含量随时间变率、风暴最大反射率因子下降高度、风暴体移动速度和垂直积分液态水含量密度等参数。根据雷达识别指标和地面大风的相关程度,给出了识别指标的隶属函数和权重系数;采用不等权重法,建立了具有模糊逻辑的对流性地面大风识别方法。并将对流性地面大风的出现概率分为3级：当识别风暴单体的判据小于0.3时,出现对流性地面大风的概率小;当判据在0.3—0.5时,产生对流性地面大风的概率较大;当判据大于0.5时,出现对流性地面大风的概率很大。通过对河北省2012年6月21日线状风暴和2009年7月23日孤立单体风暴引发的灾害大风典型个例的识别效果检验,证明这种方法识别到的风暴单体跟踪效果良好,识别出的大风范围与实况风场基本吻合,命中率、虚警率和临界成功指数分别达81.8%、25.0%和64.3%,利用模糊逻辑原理建立对流性大风的识别算法是切实可行的。  相似文献