同位素地球化学在地震监测预测研究中的应用进展

随着新观测技术和理论的进一步发展,同位素地球化学方法在地震监测预测研究中发挥了越来越重要的作用。通过同位素地球化学方法确定地下流体来源,研究地下流体循环特征,分析地震前兆异常的成因,评估地质构造活动的程度,开展地震预测研究。同位素示踪技术还可以结合深源流体监测和地球物理方法,揭示地震孕育、流体与震源之间的关系。此外,同位素地球化学还可以构建断裂带流体地球化学背景特征,用于地震监测点映震效能的评估,提高地震监测预测的准确性,为地震新监测点的布设和震情跟踪提供技术支撑。通过对现今同位素在地震监测预测中所使用的方法、技术及国内外应用情况的总结分析,力图全面认识同位素地球化学在地震监测预测应用中的现状及发展趋势。     

地下流体在地震孕育中的主要作用与流体前兆形成机制研究进展

地下流体在地震孕育和前兆形成过程中起到重要作用,因此研究地下流体对地震预报至关重要。然而,由于对地震孕震环境和发震机制缺乏深入系统的认识,导致无法根据地表观察到的异常现象准确预测地震。近年来,随着地球物理、地球化学和地质学研究的不断深入,人们对地下流体有了更多新的认识,本文通过对相关研究成果的收集和总结,介绍地下流体研究的几种经典模型,分析了地下流体在地震过程中的主要作用,并探究流体前兆形成机制。研究工作对提高地震预报水平具有一定的借鉴和参考意义。     

业务模式晴雨预报能力分析及其改进方法研究

以欧洲中心全球预报模式和中国华南区域中尺度模式(GZ 3 km)为例分析了2019年中国南方逐日晴雨预报的情况,并讨论模式晴雨预报的性能。借助TS检验评估方法,在与简单外推预报等的比较中,发现模式雨量预报特点及模式晴雨预报的统计规律,如两个模式同时预报晴天,或者模式预报有雨且降水量大于某阈值等情况,其预报准确率非常高;而对于两个模式预报不一致,或模式预报有雨且雨量较小等情况,则存在较大不确定性。基于上述研究,提出利用模式预报改进观测外推和利用观测与模式的频率匹配改进模式预报等方法。     

改进的AVAZ方法在裂缝型储层预测中的应用研究

对于裂缝型油气藏,基于叠前方位角地震数据体,利用AVAZ方法进行裂缝属性预测是目前较为有效的裂缝描述手段,然而,由于地震数据通常为窄方位采集,使得不同方位角数据覆盖次数差异较大,导致各方位振幅能量分布不均,最终造成裂缝属性预测中产生趋势性误差。振幅归一化处理技术应用到现有的AVAZ方法中,该方法能够有效地降低因数据采集所造成的趋势性误差,预测结果会更为真实、可靠。在实际油田的应用中,振幅归一化技术显著改善了AVAZ方法对裂缝属性预测的准确性,取得了较好的效果。      

<Emphasis Type="Italic">M</Emphasis><Subscript>W</Subscript>9 Tohoku earthquake in 2011 in Japan: precursors uncovered by natural time analysis

This paper reviews the precursory phenomena of the 2011 M _W9 Tohoku earthquake in Japan that emerge solely when we analyze the seismicity data in a new time domain termed natural time. If we do not consider this analysis, important precursory changes cannot be identified and hence are missed. Natural time analysis has the privilege that enables the introduction of an order parameter of seismicity. In this frame, we find that the fluctuations of this parameter exhibit an unprecedented characteristic change, i.e., an evident minimum, approximately two months before Tohoku earthquake, which strikingly is almost simultaneous with unique anomalous geomagnetic field variations recorded mainly on the z component. This is consistent with our finding that such a characteristic change in seismicity appears when a seismic electric signal (SES) activity of the VAN method (from the initials of Varotsos, Alexopoulos, Nomicos) initiates, and provides a direct confirmation of the physical interconnection between SES and seismicity.     

各向异性介质的矢量波场分离与应用

针对裂缝各向异性介质,本文提出一种非正交假设下的矢量波场分离方法.本文首先对多分量地震勘探中常见的波型泄漏现象进行了数学描述,提出在纵、横波波场分离的同时应该考虑恢复纵、横波的矢量振幅.为了对裂缝方位角与各向异性系数进行定量预测,本文将矢量波场分离拆分成三个步骤来实施：第一步,用Z、R两分量的仿射坐标系变换分离ZR平面内的P波投影与SV波;第二步,用ZR平面内的P波投影与T分量的仿射坐标系变换分离P波与SH波;第三步,用纯净的SV波与SH波的成像剖面分离快慢横波,并预测裂缝发育参数.模型数据与实际数据的试验结果表明,本文提出的纵、横波波场分离方法能够获得完整的矢量振幅信息,并提供裂缝预测的精度.     

浙江省梅汛期洪涝灾情分析和预测

通过所构设的雨涝强度、雨涝影响面积等统计量来估计灾情，有较高的正确率，能估计出极端情况，为灾害评估工作提供了新的思路。     

体应变地震波最大振幅与地震震级和震中距的统计关系探讨

Based on the body strain record of Tiantanghe station from 2008 to 2014,we make a statistical analysis of the relationship between the maximum amplitude of the body strain record and the surface-wave magnitude,epicenter distance of the earthquakes,which occurred in the Chinese mainland and its surrounding areas with MS≥6. 0 and the rest of the world with MS≥7. 0. According to statistical results,we propose a statistical formula between the surface-wave magnitude of earthquake and the maximum amplitude of the body strain record,the epicenter distance: M_S~*= 0. 37 ln A_max+ 0. 57 ln D + 0. 07. We can also derive a theoretical estimation formula for the maximum amplitude: A_max=e~(2. 7(M_S~*-0. 07))D~(-1. 54). This demonstrates that the maximum amplitude of the body strain record increases exponentially with the increase of the surface-wave magnitude, and decreases with the increase of the epicenter distance,and shows a negative correlation with their product. We further discuss the necessity of adding instruments with high frequency sampling to earthquake monitoring, and dicuss the prospects for precise earthquake prediction in future.     

Nonlinear FE model updating and reconstruction of the response of an instrumented seismic isolated bridge to the 2010 Maule Chile earthquake

Nonlinear finite element (FE) modeling has been widely used to investigate the effects of seismic isolation on the response of bridges to earthquakes. However, most FE models of seismic isolated bridges (SIB) have used seismic isolator models calibrated from component test data, while the prediction accuracy of nonlinear FE models of SIB is rarely addressed by using data recorded from instrumented bridges. In this paper, the accuracy of a state‐of‐the‐art FE model is studied through nonlinear FE model updating (FEMU) of an existing instrumented SIB, the Marga‐Marga Bridge located in Viña del Mar, Chile. The seismic isolator models are updated in 2 phases: component‐wise and system‐wise FEMU. The isolator model parameters obtained from 23 isolator component tests show large scatter, and poor goodness of fit of the FE‐predicted bridge response to the 2010 Mw 8.8 Maule, Chile Earthquake is obtained when most of those parameter sets are used for the isolator elements of the bridge model. In contrast, good agreement is obtained between the FE‐predicted and measured bridge response when the isolator model parameters are calibrated using the bridge response data recorded during the mega‐earthquake. Nonlinear FEMU is conducted by solving single‐ and multiobjective optimization problems using high‐throughput cloud computing. The updated FE model is then used to reconstruct response quantities not recorded during the earthquake, gaining more insight into the effects of seismic isolation on the response of the bridge during the strong earthquake.     

Basin‐scale methods for predicting salmonid spawning habitat via grain size and riffle spacing,tested in a California coastal drainage

Basin‐scale predictive geomorphic models for river characteristics, particularly grain size, can aid in salmonid habitat identification. However, these basin‐scale methods are largely untested with actual habitat usage data. Here, we develop and test an approach for predicting grain size distributions from high resolution LiDAR (Light Detection and Ranging)‐derived topographic data for a 77 km² watershed along the central California Coast. This approach improves on previous efforts in that it predicts the full grain size distribution and incorporates an empirically calibrated shear stress partitioning factor. The predicted grain size distributions are used to calculate the fraction of the bed area movable by spawning fish. We then compare the ‘movable fraction’ with 7 years of observed spawning data. We find that predicted movable fraction explains the paucity of spawning in the upper reaches of the study drainage, but does not explain variation along the mainstem. In search of another morphologic characteristic that may help explain the variation within the mainstem, we measure riffle density, a proxy for physical habitat complexity. We find that field surveys of riffle density explain 64% of the variation in spawning in these mainstem reaches, suggesting that within reaches of appropriate sized gravel, spawning density is related to riffle density. Because riffle density varies systematically with channel width, predicting riffle spacing is straightforward with LiDAR data. Taken together, these findings demonstrate the efficacy of basin‐scale spawning habitat predictions made using high‐resolution digital elevation models. Copyright © 2016 John Wiley & Sons, Ltd.