山西地磁加卸载响应比方法短临指标研究

应用地磁加卸载响应比方法,统计分析山西地磁台网1987—1998年模拟资料、2008年以来数字化资料的加卸载响应比异常及与其周围Ms4.0以上地震之间的关系。提出适用于山西地区地磁加卸载响应比的异常判据阈值为3.0,得出地磁加卸载响应比异常的短临指标。     

2019年长宁6.0级与夏河5.7级地震前的地磁日变化异常

运用地磁低点位移、地磁加卸载响应比和地磁逐日比三种地磁日变化异常分析方法,分析了2019年6月17日长宁6.0级和10月28日夏河5.7级地震前的地磁前兆异常现象.研究发现,两次地震前三种方法分析的结果均出现了异常,两次地震均发生在异常集中交汇区域.综合分析表明,应用地磁低点位移、加卸载响应比和逐日比预测区叠加法可以提高震中位置预测的准确度.     

地磁加卸载响应比方法在上海及其邻区地震研究中的应用

本文运用2000—2010年上海佘山台和崇明台地磁场Z分量所计算得到的地磁加卸载响应比资料分析了近11年地磁加卸载响应比对上海及其邻区中小地震的预测分析效果,并对原有的预测指标体系进行了完善。分析结果表明: ① 地磁加卸载响应比值在大于3.4的异常情况下,对上海及其邻区的M_L≥4.0地震预测有一定的指示意义; ② 两个台站的地磁加卸载响应比值随时间的整体变化趋势与上海及其邻区地震活动性的变化有较好的对应关系; ③ 通过小波变换得到,地磁加卸载响应比值与该地区的地震活动性时间序列都存在4.5年的周期变化,且在该周期尺度上位相变化一致性较好。     

广平地震台地磁加卸载响应比与地震关系初探

应用曾小苹等人提出的地磁加卸载响应比方法,研究分析了广平地震台1982-2006年地磁资料加卸载响应比与河北省及邻近地区Ms≥5.0地震之间的关系,初步提出了适用于广平地震台地磁加卸载响应比异常映震的定量指标,为广平地震台今后以磁报震提供了依据。     

汶川8.0级地震前地磁日变化异常综合分析

运用地磁低点位移、地磁加卸载响应比和地磁Z分量日变幅逐日比3种地磁分析方法,分析了2008年5月12日汶川8.0级地震前的地磁前兆异常现象。研究发现,运用上述3种方法,汶川地震前出现多次异常,地震发生在异常预测线集中交汇区域。综合分析结果显示,地磁多方法综合分析可以有效提升地震预测的精确性。文章还讨论了地磁日变化畸变异常机理问题。     

地磁加卸载响应比在东北地区中强地震应震关系分析

应用地磁加卸载响应比方法,分析东北地区地磁观测台站2008-2017年地磁Z分量日变幅加卸载响应比异常高值,结合东北地区M5.0级以上地震震例资料,分析得出加卸载响应比出现异常高值对东北地区短期内发生M5.0级以上地震有效好的指示性意义。     

地磁加卸载响应比与宁强M_S5.3地震

2018年9月12日19时6分在陕西省宁强县(32.75°N,105.69°E)发生MS5.3地震,震源深度11km。以宁强县及其周边420km为研究区域,使用地磁垂直分量Z加卸载响应比的方法,对陕—川—甘地区的汉中、周至楼、乾陵、泾阳、成都、天水和兰州七个地磁台站的资料进行处理分析,发现加卸载响应比P(Z)的高值异常与此次宁强县地震有较好的对应,为今后中短期预报提供一定的依据,也进一步推广和检验了地磁加卸载响应比在地震预报方面的应用。     

辽宁地区地磁加卸载响应比方法应用研究

应用地磁加卸载响应比方法,研究分析辽宁地区2008—2010年观测资料的加卸载响应比异常与邻区M_L4.0以上地震之间的关系,提出适用于辽宁地区地震分析预报参数。     

广东及邻区地震前地磁变化和异常判别指标

应用差值,相关,地磁特征线以及地磁加卸载响应比等方法,分别计算了广东,海南,广西３个台的地磁资料,寻找适用于本区的地磁分析预报方法及地震异常判别指标,结果表明,当参量超过１．５倍均方差时为异常;异常出现半年内在异常台站附近（距离小于２５０ｋｍ范围内）发生地震．若两个台站同时出现异常则未来地震将可能大于６级,在单台分析法中,地磁特征线法和加卸载响应比法效果较好,用特征线法,当广州台特征线参数Ｋ－０．     

营口地震台地磁数据加卸载响应比和逐日比异常核实

针对2019年9月12日营口地震台地磁数据加卸载响应比和逐日比超阈值异常,从仪器观测系统,环境干扰等方面对异常信息进行了科学严谨的分析,结果认为这次地磁加卸载响应比和逐日比异常是地震前兆异常的可能性较大。     

The Newest Developments of Load-Unload Response Ratio (LURR)

The Load Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It is inspiring that its predictions using LURR have been improving. Since 2004 we have made a major breakthrough in intermediate-term earthquake forecasting of the strong earthquakes on the Chinese mainland using LURR and successfully predicted the Pakistan earthquake with magnitude M 7.6 on October 8, 2005. The causes for improving the prediction in terms of LURR have been discussed in the present paper.     

加卸载响应比在震后趋势估计和震前中短期预测中的应用

以加卸载响应比方法在青藏高原北部地区几次中强地震预报中的应用为例 ,讨论了天然地震序列下样本条件对加卸载响应比Y值的影响 ,探讨了该方法在震后趋势估计和震前中短期预测应用中的若干问题 ,以探索提高响应比方法预测地震的成功率 .     

赣粤闽交界及邻区近年中强地震加卸载响应比特征研究

以地震应变能作为响应因子,研究了1997至2007年赣粤闽交界及邻区4．0级（ML≥4．0）以上中强地震临震前的加卸载响应比（Y值）的基本变化特征,研究结果表明,80％以上的地震在临震前Y值呈现出高值异常形态。因而它可以作为此地区地震预测的一种手段。     

美国西部地区加卸载响应比的时空扫描及其地震趋势研究

加卸载响应比理论是近年来提出的地震预报新方法, 在中国大陆地区的实际地震预测中取得了较好的效果。 为了研究加卸载响应比理论是否适用于不同地质条件的地震, 是否具有普适性, 选择了典型的美国圣安德烈斯断层带及其周围地区的地震作为研究对象, 计算分析了美国西部地区加卸载响应比的变化情况, 并对该地区未来的地震趋势进行了研究。     

量纲分析应用于地震预测的探索

加卸载响应比(LURR)的基本思路是希望能够通过刻画震源区介质的损伤程度,反映地震孕育的进程,从而预测地震.近30年来,很多人对加卸载响应比做了大量基础研究,取得了一系列新的进展.加卸载响应比在地震预测实践中也取得了一定的效果,异常区与地震发生的位置有较好的对应性,但是预测效果仍不够理想.究其原因主要是:在实际预测中对当地的地球物理情况考虑的不够.本文采用量纲分析与加卸载响应比结合的方法,综合考虑当地的地球物理情况,例如剪应变率和平均地震波能量等因素的影响.文中选取1970年以来发生在中国大陆的34个震例资料,通过分析得到了与发震震级和时间相关的无量纲量π₁和π₃,根据对实际数据的拟合,π₁和π₃均与震级成指数关系.在应用于地震预测实践时,首先根据LURR空间扫描结果选取异常区,然后确定异常区的地球物理参数,通过π₁确定震级M,再由π₃确定发震时间T.     

2020年6月26日于田MS6.4地震前Benioff应变和地电场加卸载响应比异常研究

加卸载响应比（Load/Unload Response Ratio,LURR）是根据岩石介质本构关系的动态演化特征提出的地震预测方法。2020年6月26日新疆于田县发生6.4级地震,震前以Benioff应变为响应量观测到明显的LURR高值异常,异常出现于2019年初,持续1年后发生地震,意味着震源区介质的应力状态在2019年发生了明显改变。进一步,以地电场为响应量,计算了距震中280km的和田地电场长、短极距共6个测向的LURR异常时序曲线,结果表明：和田地电场长、短极距的NS向和NW向共4个测向在震前1~3个月出现了LURR异常逐渐增大的同步变化,这种现象可能反映了孕震区介质因微裂隙的产生和扩展导致流体在裂隙中的运移引起的动电效应。综合分析2种不同响应量的LURR异常演化特征,有助于更深入地认知地震孕育过程,更准确地评估地震活动趋势。     

Simulation of the Load-Unload Response Ratio and Critical Sensitivity in the Lattice Solid Model

— The Load-Unload Response Ratio (LURR) method is an intermediate-term earthquake prediction approach that has shown considerable promise. It involves calculating the ratio of a specified energy release measure during loading and unloading where loading and unloading periods are determined from the earth tide induced perturbations in the Coulomb Failure Stress on optimally oriented faults. In the lead-up to large earthquakes, high LURR values are frequently observed a few months or years prior to the event. These signals may have a similar origin to the observed accelerating seismic moment release (AMR) prior to many large earthquakes or may be due to critical sensitivity of the crust when a large earthquake is imminent. As a first step towards studying the underlying physical mechanism for the LURR observations, numerical studies are conducted using the particle based lattice solid model (LSM) to determine whether LURR observations can be reproduced. The model is initialized as a heterogeneous 2-D block made up of random-sized particles bonded by elastic-brittle links. The system is subjected to uniaxial compression from rigid driving plates on the upper and lower edges of the model. Experiments are conducted using both strain and stress control to load the plates. A sinusoidal stress perturbation is added to the gradual compressional loading to simulate loading and unloading cycles and LURR is calculated. The results reproduce signals similar to those observed in earthquake prediction practice with a high LURR value followed by a sudden drop prior to macroscopic failure of the sample. The results suggest that LURR provides a good predictor for catastrophic failure in elastic-brittle systems and motivate further research to study the underlying physical mechanisms and statistical properties of high LURR values. The results provide encouragement for earthquake prediction research and the use of advanced simulation models to probe the physics of earthquakes.     

Load-Unload Response Ratio and Accelerating Moment/Energy Release Critical Region Scaling and Earthquake Prediction

-- The main idea of the Load-Unload Response Ratio (LURR) is that when a system is stable, its response to loading corresponds to its response to unloading, whereas when the system is approaching an unstable state, the response to loading and unloading becomes quite different. High LURR values and observations of Accelerating Moment/Energy Release (AMR/AER) prior to large earthquakes have led different research groups to suggest intermediate-term earthquake prediction is possible and imply that the LURR and AMR/AER observations may have a similar physical origin. To study this possibility, we conducted a retrospective examination of several Australian and Chinese earthquakes with magnitudes ranging from 5.0 to 7.9, including Australia's deadly Newcastle earthquake and the devastating Tangshan earthquake. Both LURR values and best-fit power-law time-to-failure functions were computed using data within a range of distances from the epicenter. Like the best-fit power-law fits in AMR/AER, the LURR value was optimal using data within a certain epicentral distance implying a critical region for LURR. Furthermore, LURR critical region size scales with mainshock magnitude and is similar to the AMR/AER critical region size. These results suggest a common physical origin for both the AMR/AER and LURR observations. Further research may provide clues that yield an understanding of this mechanism and help lead to a solid foundation for intermediate-term earthquake prediction.     

Comparison Between LURR and State Vector Analysis Before Strong Earthquakes in Southern California Since 1980

There are seven strong earthquakes with M ≥ 6.5 that occurred in southern California during the period from 1980 to 2005. In this paper, these earthquakes were studied by the LURR (Load/Unload Response Ratio) method and the State Vector method to detect if there are anomalies before them. The results show that LURR anomalies appeared before 6 earthquakes out of 7 and State Vector anomalies appeared before all 7 earthquakes. For the LURR method, the interval between maximum LURR value and the forthcoming earthquake is 1 to 19 months, and the dominant mean interval is about 10.7 months. For the State Vector method, the interval between the maximum modulus of increment State Vector and the forthcoming earthquake is from 3 to 27 months, but the dominant mean interval between the occurrence time of the maximum State Vector anomaly and the forthcoming earthquake is about 4.7 months. The results also show that the minimum valid space window scale for the LURR and the State Vector is a circle with a radius of 100 km and a square of 3°×3°, respectively. These results imply that the State Vector method is more effective for short-term earthquake prediction than the LURR method, however the LURR method is more effective for location prediction than the State Vector method.     

一种将GPS观测应用于地震中短期预测的简单尝试

本文尝试采用一种类似于加卸载响应比的简单算法将GPS观测应用于地震中短期预测.算法根据孕震区域在不同阶段的加卸载响应比变化判断未来地震的发生趋势:当地壳处于稳定状态时,得到的时间序列在1.0附近波动;而在临近地震之前会出现明显的异常高值.以2004年美国南加州的Parkfield地震为例对方法的有效性进行了研究,发现在地震发生前半年左右震中附近GPS台站得到加卸载响应比时间序列都发生了比较明显的异常变化;而一些距离震中较远台站却没有观察到类似的异常变化.这可能反映了孕震区地壳介质稳定性的变化,表明通过处理GPS观测资料可能获得新的地震前兆异常.