利用多分辨率小波网络方法进行伪井反演

利用小波网络,对地震资料和小波多尺度分解属性资料,进行了虚井声波时差反演.讨论了利用地震信号的小波分解和网络学习、训练的理论方法.为了提高反演分辨率和精度，研究了信号分段相似小波时—频分析技术方法.在对对这些技术方法综合研究和算法的实现设计以后，对实际资料进行了反演计算，并对反演结果进行验证.取得了很好的效果.     

一种小波综合阈值地震信号降噪方法

小波阈值方法中硬、软阈值方法是地震信号降噪常用方法,但容易造成信号中高频信息丢失导致地震误判和漏判情况发生。小波综合阈值方法继承和发展了硬、软阈值降噪方法的优点,对信号高频部分用硬阈值方法,以提高高频信号能量,对信号低频部分用软阈值方法,提高信号降噪能力的同时保证信号连续性和光滑性。利用噪声信号小波系数小和地震信号小波系数大的特征,进行雷克子波降噪仿真实验和实际地震信号降噪实验。仿真实验表明,小波综合阈值方法降噪后波形MSE值最小,且降噪后与原信号波形最近似,降噪后波形高频部分能量增强且抑制低频部分能量。最后,对实际采集的地震信号进行降噪处理,处理后信号中能量增强被压制,利用处理后的信号可得到地震的初至时间。     

测井声波时差反演重构技术研究及应用

利用测井声波时差、自然电位和伽玛重构声波时差,分析了以上3种曲线结果对地质体响应方面的机制差异,给出了这些曲线的深度相对移动校正的方法。研究了多条测井曲线去噪的协方差矩阵特征向量滤波方法。在此基础上,利用小波多尺度分解技术进行声波时差曲线重构。在分析这3种测井曲线不同尺度小波分解结果的信号和噪音特点后,利用相邻分解尺度相关滤波技术,对各种曲线的小尺度(高频)分解结果进行滤波处理。为保证重构声波曲线的真实性,深入分析了多曲线、多尺度分解结果的冗余性(相关性)问题;利用特征值技术,对高频多尺度分解分量进行了非相关(正交)分析,最后实现了声波时差曲线的重构,并对重构结果与钻井岩心录井资料进行了对比验证,重构后的声波曲线在区分砂、泥岩性分辨率方面具有明显的提高     

基于小波多分辨率分析的地磁脉动信号提取

2003年10月29日,云南通海地磁台记录到一次K=9的特大磁暴。运用本次强磁暴的数字化记录资料,探讨了用小波多分辫率分解Mallat塔式率算法在强磁暴信号水平上提取地磁脉动弱信号的方法。结果表明,该算法提取的地磁脉动信号频率成分清晰、基线平整、波型完好。     

基于EWT和Meyer自适应阈值的微震降噪

露天矿采场边坡的微震信号具有振幅弱、噪声多、信噪比低的特征,基于经验小波变换(EWT)及Meyer自适应阈值提出分频降噪方法.首先,针对微震信号的频谱特征,设计一种频谱分割策略,将信号和噪声分解为不同的模态;其次,分析模态的频谱和能量,采用Meyer阈值函数自适应降噪,提高有效信号振幅;最后,借助阈值函数处理包含较少有用信号的模态,重构微震信号以保持其连续性,结果表明,降噪后微震信号信噪比(SNR)高、有效信息多,噪声少;通过多种方法对比,并用信噪比与均方根误差(RMSE)对本次降噪效果进行评价,本文方法较好的保留了微震信号有效信息,降噪效果显著.     

用小波变换能量线性度方法识别天然地震与爆破或塌方

为了提取天然地震和爆破或塌方记录波形在震源深度、震源尺度、震源破裂机制、地震波传播途径、地震波衰减等方面的差异特征信息,本对山东数字化台网记录的天然地震和爆破或塌方波形进行了小波多分辨率的能量线性度特征分析,提出了用小波变换能量线性度方法识别天然地震与爆破或塌方事件．结果表明：在精细结构小波分解信号“能量”线性度方面,天然地震主要集中在-2．0～1．0之间,爆破或塌方主要集中在2．0～3．4之间;在精细结构小波分解信号“能量”最大值对应的小波分解尺度方面,爆破或塌方主要集中在4～5,频段集中在0．7～3．1Hz之间,而天然地震主要集中在1～2,频段集中在6．25～25Hz之间．     

基于Daubechies小波分析的南京数字化钻孔形变震前变化特征研究

应用小波分析理论及其时频分析方法,阐述了高低频信息的识别和小波基的选取,并对南京地区2006—2012年数字化应变观测整点值资料进行了小波多分辨率分析。结果表明,六合台体应变小波分解7—9阶是频率最低的部分,异常信号的周期在24—30天左右,持续时间在1—2个月之间,具有明显的短期、临震异常特征;江宁台四分量应变的整点观测值的第9阶小波分解表明,在发生2次地震前,四分量中至少有3个方向的分量出现了明显的异常情况,这种异常周期通常在20—30天左右,其与高淳台的异常周期时间相当,它可能是地震的前兆信号。     

基于小波变换与小波包变换的降噪方法比较

在模拟地震记录信号中加入信噪比为17的高斯白噪声,然后分别采用小波降噪和小波包降噪方法,对含噪信号进行降噪处理。在不同降噪阈值下,比较降噪后信号的信噪比。结果表明:在同一降噪阈值下,小波包降噪后信号的信噪比高于小波降噪后信号的信噪比,而且采用wbmpen方法给定的阈值明显可以提高降噪后信号的信噪比。     

利用多分辨率小波网络进行地震资料反演

在讨论小波网络理论方法的基础上,研究了利用地震纪录小波多尺度分解属性资料进行虚井声波时差反演的技术方法。分析了利用地震信号进行小波分解和网络学习、训练的理论方法。研究中发现:对于相邻的地震道,较小一段的相似性比整个地震道的相似性要好。据此,利用小波时-频分析技术方法,可以把相邻道的信息外推到其它地震道上。通过以上综合研究及对实际资料进行反演计算、分析,认为小波网络与人工神经网络相比其网络结构要容易选定,并且收敛速度快。同时,利用地震资料分段时-频分析的相似性较好和小波网络学习、训练及记忆能力较强的特点,可以较好地把井旁道的高、低频信息转换到相邻道上。这样在提高分辨率的同时,又增加了反演结果的真实可靠性     

基于经验模态分解及独立成分分析的微震信号降噪方法

针对微震信号具有高噪声、突变快、随机性强等特点,基于经验模态分解(EMD)及独立成分分析(ICA)提出一种微震信号降噪方法.首先,对含噪信号进行EMD分解,获得一系列按频率从高到低的内蕴模态函数(IMF),利用原信号与各IMF之间的互相关系数辨识出噪声与信号的分界,将分界之上的高频噪声滤除;其次,为有效去除分界IMF中的模态混叠噪声,基于ICA算法对分界IMF进行盲源分离,提取其中的微震有效信号,并将其与剩余的IMF累加重构,从而得到降噪后的微震信号;最后,利用快速傅里叶变换(FFT)时频谱对比分析降噪前后的信号特征,定性说明本文方法的有效性;引入信噪比和降噪后信号占原信号的能量百分比两个参数,定量说明本文方法能充分保留微震信号的瞬态非平稳特征,降噪效果明显.     

SCIENCE CHINA Earth Sciences SUBJECT INDEX TO VOLUME 57(2014)

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Distribution of throughfall and stemflow in multi‐strata agroforestry,perennial monoculture,fallow and primary forest in central Amazonia,Brazil

The partitioning of rain water into throughfall, stemflow and interception loss when passing through plant canopies depends on properties of the respective plant species, such as leaf area and branch angles. In heterogeneous vegetation, such as tropical forest or polycultural systems, the presence of different plant species may consequently result in a mosaic of situations with respect to quantity and quality of water inputs into the soil. As these processes influence not only the water availability for the plants, but also water infiltration and nutrient leaching, the understanding of plant effects on the repartitioning of rain water may help in the optimization of land use systems and management practices. We measured throughfall and stemflow in a perennial polyculture (multi‐strata agroforestry), monocultures of peach palm (Bactris gasipaes) for fruit and for palmito, a monoculture of cupuaçu (Theobroma grandiflorum), spontaneous fallow and primary forest during one year in central Amazonia, Brazil. The effect on rain water partitioning was measured separately for four useful tree species in the polyculture and for two tree species in the primary forest. Throughfall at two stem distances, and stemflow, differed significantly between tree species, resulting in pronounced spatial patterns of water input into the soil in the polyculture system. For two tree species, peach palm for fruit (Bactris gasipaes) and Brazil nut trees (Bertholletia excelsa), the water input into the soil near the stem was significantly higher than the open‐area rainfall. This could lead to increased nutrient leaching when fertilizer is applied close to the stem of these trees. In the primary forest, such spatial patterns could also be detected, with significantly higher water input near a palm (Oenocarpus bacaba) than near a dicotyledonous tree species (Eschweilera sp.). Interception losses were 6·4% in the polyculture, 13·9 and 12·3% in the peach palm monocultures for fruit and for palmito, respectively, 0·5% in the cupuaçu monoculture and 3·1% in the fallow. With more than 20% of the open‐area rainfall, the highest stemflow contributions to the water input into the soil were measured in the palm monocultures and in the fallow. Copyright © 1999 John Wiley & Sons, Ltd.     

A Monte Carlo study of rainfall forecasting with a stochastic model

A procedure for short-term rainfall forecasting in real-time is developed and a study of the role of sampling on forecast ability is conducted. Ground level rainfall fields are forecasted using a stochastic space-time rainfall model in state-space form. Updating of the rainfall field in real-time is accomplished using a distributed parameter Kalman filter to optimally combine measurement information and forecast model estimates. The influence of sampling density on forecast accuracy is evaluated using a series of a simulated rainfall events generated with the same stochastic rainfall model. Sampling was conducted at five different network spatial densities. The results quantify the influence of sampling network density on real-time rainfall field forecasting. Statistical analyses of the rainfall field residuals illustrate improvement in one hour lead time forecasts at higher measurement densities.     

Anthropogenic Eutrophication and Red Tide Outbreak in Lacustrine Systems of the Kashmir Himalaya

Red tide, a recurrent phenomenon has become conspicuous in several Kashmir lake ecosystems since 1991. The responsible organism (Euglena pedunculata), a rare flagellate rediscovered in the Kashmir Himalaya (Khan 1993) caused first and unprecedented red tide outbreak, constituting a maximum of 96% of resident numerical phytoplankton density in Dal Lake. At present, conflicting hypotheses exist on the generation of causal assemblage(s) imparting redness to waters: Jeeji Bai (1991) linked its origin to acid precipitation – a fallout of burning oil‐fields during the Gulf War – whilst Khan (1993) holds local factor(s) responsible. Field/experimental studies support the latter contention that the influx of untreated sewage, in unison with warm temperatures, high levels of PhAR, iron and interruption to hydrological flow‐pattern together with absence/or reduction in grazing activity created conducive environmental milieu for red tide outbreak. Dal Lake “red tide” drifted the bloom‐inoculum to other waters, including Lake Wular, where additional ecological niches were carved out, threatening the aesthetic value and biological diversity of Kashmir lakes. Ecological monitoring indicates frequent seasonal red tide occurrence in Dal Lake (including summer‐autumn event of 1998) which testifies its unabated eutrophication status. Further studies are needed on ecological adaptability and biogeographic distribution of this rare and unique red tide‐causing flagellate.