起算震级与衰减不确定性校正

分析表明,起算震级Ｍ０对危险性分析结果的表现为当Ｍ０取取值不够低时,场地的危险性将被低估。此种低估影响与场地的地震危险性高低潜源距场地的距离及衰减公式的形式和标准差有关。     

基于正则化条件的地震数据局部信噪比估计方法

信噪比是衡量地震数据质量的重要指标之一,在地震数据处理和解释中有着重要的作用.目前已有的地震数据信噪比估计方法往往得到的是整个数据的全局信噪比,这种方法只能说明地震数据总体质量的好坏,无法直观细致地刻画地震信号的局部质量.本文提出一种基于正则化条件的局部信噪比估计方法.该方法的基本原理是使用正则化共轭梯度法求解局部信噪比最优解,正则化算子的参数将控制地震信号各点数据局部信噪比的平滑性.其中应用一种基于“过滤波”的级联信号估计方法来计算有效信号,该方法利用有效信号和噪声的相关性特征计算局部信噪比中的有效信号.局部信噪比估计方法利用了信号中每个数据点及其邻域各点的局部信息,避免了使用单个数据点而可能出现的信噪比不合理值,而且局部处理能够减少全局噪声对信噪比估算的影响,该方法可以更准确地表征地震资料信噪分布特征.另外,局部信噪比对去噪方法的评估也具有重要意义.理论模型测试和实际资料处理结果表明,局部信噪比估计方法能够准确反映任一给定地震信号剖面的局部信噪比特征,为非平稳地震数据质量评估提供了直观的评判标准.

     

宏观异常与地震关系的统计分析

通过对《中国震例》中所辑宏观异常的统计分析认为,随着震级的增大,震前出现宏观异常的概率逐步增大,震级大的地震震前宏观异常数量也相对较多。宏观异常大多数为短期和临震异常,多数发生在距震中100km的范围内。在时间上,宏观异常开始时数量较少;随着时间的推进,异常不断增多;越近临震,异常数量越多,直到发震达到高潮。在地域上则表现出始于震中、然后向外围发展、最后震中爆发式增多的特点。     

2013年吉林前郭M_S5.8震群序列研究

对前郭M_S5.8地震后6个月(2013年10月31日~2014年4月30日)内的地震事件进行了重新定位,并利用吉林区域地震台网提供的地震目录研究了序列活动特征。精定位结果显示,余震区呈NW走向分布,长轴约11km,短轴约6km。震源深度为5~15km。结合区域构造特征认为,该序列可能与NW走向的通榆-长春隐伏断裂活动有关,序列具有b值较低、5级地震频次高、发震时间集中的特点。序列主要起伏活动可以分为3个时段:主震后10天,余震强度衰减不明显;此后的2次起伏活动,地震活动分别表现出平静-增强(震级爬升)-发生强震和增强(震级爬升)-平静-再增强(震级爬升)-发生强震的特点;在序列早期阶段,震级-频度无法拟合成1条直线,G-R关系在低震级段和高震级段呈现2个线性段;在M_S5.8地震前h值有变小的趋势,且接近1;而M_S5.8地震后h值明显增大;M_S5.5地震后15天序列衰减比较慢,p值为0.76;M_S5.8地震后15天序列衰减较快,p值为1.17。     

基于加权一致性的蚁群算法在断层检测中的应用

突出地震数据振幅空间不连续性的断层增强属性体是断层自动解释的基础,而如何压制噪声、地层残余响应、角度不整合接触等伪断层的影响是断层自动检测的关键问题之一.在指纹图像边缘检测处理中,一致性是对指示局部方向场信息各向异性强度的一个度量,本文将其作为一种新的断层增强属性引入到地震数据处理中.为了更有效地压制噪声,本文通过对一致性进行加权处理,再结合蚁群算法,提出了新的断层自动检测方法——基于加权一致性的蚁群算法.理论地震模型和实际地震数据的处理结果表明,对于相同的断层检测过程,对比常规的基于方差属性的蚁群算法和基于C3相干属性的蚁群算法,本文所提方法不仅更有效地压制了噪声和地层残余响应产生的伪断层信息,而且更完整地展现了断层的延伸长度,同时具有更高的稳定性和计算效率.     

The role of hydrologic information in reservoir operation – Learning from historical releases

Closing the gap between theoretical reservoir operation and the real-world implementation remains a challenge in contemporary reservoir operations. Past research has focused on optimization algorithms and establishing optimal policies for reservoir operations. In this study, we attempt to understand operators’ release decisions by investigating historical release data from 79 reservoirs in California and the Great Plains, using a data-mining approach. The 79 reservoirs are classified by hydrological regions, intra-annual seasons, average annual precipitation (climate), ratio of maximum reservoir capacity to average annual inflow (size ratio), hydrologic uncertainty associated with inflows, and reservoirs’ main usage. We use information theory – specifically, mutual information – to measure the quality of inference between a set of classic indicators and observed releases at the monthly and weekly timescales. Several general trends are found to explain which sources of hydrologic information dictate reservoir release decisions under different conditions. Current inflow is the most important indicator during wet seasons, while previous releases are more relevant during dry seasons and in weekly data (as compared with monthly data). Inflow forecasting is the least important indicator in release decision making, but its importance increases linearly with hydrologic uncertainty and decreases logarithmically with reservoir size. No single hydrologic indicator is dominant across all reservoirs in either of the two regions.     

A comparative overview of weathering intensity and HCO3 flux in the world's major rivers with emphasis on the Changjiang,Huanghe, Zhujiang (Pearl) and Mississippi Rivers

In this paper, general relationships of riverine bicarbonate concentrations and fluxes as a function of drainage basin mineral content and runoff are examined using a database of the 25 largest rivers in the world. Specific HCO₃⁻ flux normalized to unit basin area, which peaks in the mid latitudes, was found to be strongly correlated with the carbonate mineral content of river basins, while river HCO₃⁻ concentration was related to the balance of precipitation and evaporation. Within this global context, the weathering patterns of CO₂ in a few large rivers (Changjiang, Huanghe, Pearl, and Mississippi rivers) were examined in further detail. The Zhujiang (Pearl River), especially its largest branch (Xijiang), was characterized by the highest specific weathering rate among all the world's large rivers due to an exceptionally high carbonate mineral content (over 80%) in its drainage basin and its warm and wet environment. It has a moderate level of HCO₃⁻ concentration, however, due to dilution by relatively high precipitation in the watershed. In stark contrast, the Huanghe (Yellow River) has one of the lowest specific weathering rates because of low carbonate mineral content and a dry climate. However, it has a high HCO₃⁻ concentration due largely to the concentrating effects of high evaporative water loss, as a result of arid weather and the agricultural use of water through irrigation systems, as well as carbonate-containing surficial deposits (i.e., loess). The strong correlation between specific HCO₃⁻ fluxes and discharge in all four rivers with different discharge seasonality suggests that higher precipitation in drainage basins promotes higher weathering rates.     

模糊嵌套多级中值滤波方法及其在地震数据处理中的应用

多级中值滤波器在地震数据处理应用中,其滤波长度越大,消噪效果越好,但同时也会破坏有效信息. 如果为了保护有效信息而减少滤波长度,又会造成大量的噪声不能消除. 本文提出一种新的模糊嵌套多级中值滤波器,设计一个阀值作为判断参数,使滤波器能够在消除随机噪声时采用长滤波器滤波,而在保留有效信息时采用短滤波器滤波,从而既能很好地消除随机噪声,又能最大限度地保护有效信息,保留有效信息的细节结构. 经过模型分析和实际资料处理都取得了很好的效果.     

2D地震数据规则化中随机稀疏采样方案

地震数据规则化是地震信号处理中一个重要步骤,近年来受到广泛关注的压缩感知技术已经被应用到地震数据规则化中。压缩感知技术突破了传统的Shannon-Nyqiust采样定理的限制,可以用采集的少量地震数据重构完整数据。基于压缩感知技术的地震数据规则化质量主要受三个因素影响,除了受地震信号在不同变换域的稀疏表达和11范数重构算法的影响外,极大地取决于地震道随机稀疏采样方式。尽管已有学者开展了2D地震数据离散均匀分布随机采样方式研究,但设计新的稀疏采样方案仍然很有必要。在本文中,我们提出满足Bernoulli分布规律的Bernoulli随机稀疏采样方式和它的抖动形式。对2D数值模拟数据进行四种随机稀疏采样方案和两种变换（Fourier变换和Curvelet变换）实验,对获取的不完整数据应用11范数谱投影梯度算法（SPGL1）进行重构。考虑到不同随机种子点产生不同约束矩阵R会有不同的规则化质量,对每种方案和每个稀疏采样因子进行10次规则化实验,并计算出相应信噪比（SNR）的平均值和标准偏差。实验结果表明,我们提出的新方案好于或等于已有的离散均匀分布采样方案。