煤岩变形破裂电磁辐射的实验研究

对受载煤体变形破裂产生电磁辐射进行了实验研究及规律分析,并对煤岩变形破裂电磁辐射的机理进行了探讨分析．研究结果表明,煤体变形破裂时能够产生电磁辐射,电磁辐射信号与声发射信号并非严格同步,电磁辐射信号较声发射信号丰富,电磁辐射与煤岩体的变形破裂过程密切相关．煤岩电磁辐射技术在揭示煤岩变形破裂机理,预测、预报地震,矿山煤岩灾害动力现象及岩石混凝土建筑稳定性方面有着非常广泛的应用前景．     

地电阻率中短期异常与地震的关系

研究了196次Ms3.2～7.9地震（94％以上为Ms4.0地震）前1139次（道次）地电阻率中短期异常,得到以下结果:① 异常时间与震级之间为非线性增长关系,大致分为３个阶段:Ms5.0地震,异常时间随震级增大基本上是快速的线性增长;5.0＜Ms＜6.5地震,增长速度逐步变小;Ms6.5地震,增长速度很小．② 异常幅度与震级之间为非线性的指数式增长关系,也大致分为３个阶段:Ms5.0地震,随震级增大异常幅度增长很小;5.0＜Ms＜6.5地震,逐步趋于加速增长;Ms6.5地震,加速增长．定性解释、并利用流变介质模型探讨了异常时间、幅度与震级之间非线性关系的物理机制．      

由静中动判据对1996年2月3日丽江7级大震的中长期预测

历史地震活动有高低潮之分．低潮中6级以上地震活动的地方,暗示当地地下有较多的能量或是积能较快,下次大区域大震高潮来临时,这些６级左右地震发生地区往往会发生7级和7级以上大震．我们把上述预报大震的判据称为静中动判据．这种判据对预报大震发生地方比较有效,一般震中误差不到100km．我们按此判据对1996年云南丽江7级大震作了较成功的中期预报,地点误差约50km．另外,1994年台湾海峡7.3级大震、1995年滇缅接壤地区的7.2级大震,以及1997年北玛尼7.9级大震,也符合静中动判据的回顾性预报．我们在1992年的统计发现静中动窗口是1940～1945年、1958～1961年和1979～1986年．静中动判据在用于中国大陆内部时,静中动地震为6级左右;在喜马拉雅地震带和太平洋地震带以及新疆西北边缘地震带,则静中动地震可达7级,它们对应未来比7级更大的地震．对中国大陆从构造和几千年历史地震活动上看,无7级大震可能的地区则不宜用静中动判据．      

前兆场稳定度Dk在中强地震前兆资料分析中的应用

提出了前兆场稳定度的概念,利用前兆场稳定度的方法对中强地震前豫鲁冀交界区不同台站和不同手段的前兆观测数据进行分析。结果表明,在１９８３年１１月７日山东菏泽Ｍs５ ．９级和１９８５年１１月３０日河北任县Ｍs５．０级地震前１４个月内,前兆场稳定度有低值异常显示,并且异常幅度越来越大,地震后恢复到正常值。     

形变有震短临异常的演化特征

分析了７个形迹有震异常的震例,通过分析归纳出了形迹有震短临异常的五个基本形态特征：（１）异常初期快速突变;（２）异常在发震前一般都恢复,在突变期间一般不发震;（３）发震时间一般在异常出现恢复一个月以内;（４）震级与异常幅度之间无明显数量关系;（５）异常范围一般为２００ｋｍ左右。在特征分析的基础上,进一步探讨了形迹短临前兆异常上述特征的物理机制。     

华北水氡异常与地震关系的Bayes判别分析

选取华北地区１９９０￣１９９８年８月较完整的水氡观测资料,笔者采用ｘ＾２统计检验法识别前兆异常,利用笔者建立的Ｂａｙｅｓ判别分析方法,对该地区水氡异常与中强震活动性的关系进行了内符检验和外推预测。在风险代价比Ｋｄｎ取４的情况下,内符检验的有震报准率ｃ为０．７１,预报占时率ｂ为０．３３,Ｒ值可达０．３８;外推有震报效率ｃ为０．５,时空占有率０．０５,Ｒ值为０．４５,能够正确预测１９９８年１月１０日张     

岫岩—海城5.6级地震前的水化学异常

岫岩－海城５．６级地震前辽宁省一些井孔水化学出现了明显的中趋势异常和短临异常。本文就异常情况作了全面介绍,并对异常形态、特征等作了初步分析研究。这些异常井孔在时间上与地震活动、其它前兆异常基本同步,为统一应力作用的结果。     

对流项处理对厦门湾流态数值模拟结果的影响研究

<正>确处理流体力学方程中的对流项对环流的数值模拟起着重要作用。采用数值实验的方式,采用不同的对流项处理方法,模拟了厦门湾潮流场,并将数模结果与物模模拟结果进行对比,分析不同对流项处理方式对厦门湾区域流态模拟结果的影响,以此为依据提出适合港湾的对流项处理方法。     

Deformation bands formed during soft-sediment deformation: Observations from SE Utah

Several types of syndepositional deformation structures contain strain localization structures known as disaggregation bands. Abundant field examples from Utah show that such bands can be related to vertical movements linked to loading and fluid expulsion, forming a pre-tectonic set of strain localization structures in deformed sandstones that can easily be overlooked or misinterpreted as tectonic structures in petroleum reservoirs. Plug measurements and thin-section investigations show that they have little or no influence on fluid flow. In contrast, disaggregation bands formed as a response to tectonic stress at higher confining pressures (depths) in the same lithology show up to 3–4 orders of magnitude reduction in permeability. This makes it important to distinguish between synsedimentary and tectonic deformation bands. They should also be separated because only bands formed in relation to tectonic stress can be used to predict nearness to important faults and to assess the extent of faulting in a reservoir.     

A seafloor experiment to monitor vertical deformation at the Lucky Strike volcano, Mid-Atlantic Ridge

Decades of cruise-based exploration have provided excellent snapshots of the structure of mid-ocean ridges and have revealed that accretion is a mixture of steady-state and quantum events. Observatory-type studies are now needed to quantify the temporal evolution of these systems. A multi-disciplinary seafloor observatory site is currently being set up at the Lucky Strike volcano, in the axial valley of the slow spreading Mid-Atlantic ridge as a part of the MoMAR (monitoring of the Mid-Atlantic Ridge) initiative. The aim of this observatory is to better understand the dynamics of the volcano and the hydrothermal vents hosted at its summit as well as their plumbing systems. In August 2006, the GRAVILUCK cruise initiated an experiment to monitor the deformation of Lucky Strike volcano. A geodetic network was installed, and seafloor pressure, gravity and magnetic data were collected. In this paper, we present the method used to monitor volcanic deformation, which involves measuring relative depth difference between points within a seafloor geodesy network. We show that, taking into account oceanographic variability and measurement noise, the network should be able to detect vertical deformations of the order of 1 cm.