合肥台地电阻率NS向趋势异常变化原因分析

合肥台NS测向地电阻率自2015年以来出现趋势下降异常,经核实2015—2016年降雨量增多和地下水位抬升与地电阻率趋势下降异常变化显著相关。通过褶积滤波法和相关分析法分别消除降雨和水位影响后,趋势下降变化不明显,从而认为此变化为干扰所致,非地震前兆异常,并探讨了这种干扰影响机制,为今后判断引起地电测值变化的原因提供了科学依据。     

Assessing shipping water vertical loads on a fixed structure by convolution model and wet dam-break tests

Estimation of loads derived from shipping water events in naval and offshore structures is of importance to improve their structural design or to predict changes in their dynamics. For the case of vertical loads on deck of a fixed structure, it is possible to estimate analytically their evolution in time by considering the distribution of shipping water elevations. However, the classical approach to estimate this distribution (i.e., dam-break method) tends to overestimate the amount of water on deck and does not follow the generated decay trends observed experimentally. In the present work, the time evolution of the vertical loads due to shipping water events was studied analytically and experimentally. The validation of the use of a convolution model to estimate the time evolution of vertical loads is presented, aiming to improve the results obtained with classical approaches. A systematic experimental study has been conducted using the wet dam-break method to generate isolated shipping water events, measuring the slow-varying vertical loads on a rectangular fixed structure. A force balance and a high-speed camera have been used at the same sampling rate to monitor the vertical loads and the shipping water evolution on the deck. Results demonstrated that the use of the convolution model improved the representation of the time series of loads compared with the traditional dam-break approach. With this new method, it was possible to capture the peaks and the decay tendencies observed in the experimental data in an approximated way.     

Analytic modeling of groundwater dynamics with an approximate impulse response function for areal recharge

An analytic approach is presented for the simulation of variations in the groundwater level due to temporal variations of recharge in surficial aquifers. Such variations, called groundwater dynamics, are computed through convolution of the response function due to an impulse of recharge with a measured time series of recharge. It is proposed to approximate the impulse response function with an exponential function of time which has two parameters that are functions of space only. These parameters are computed by setting the zeroth and first temporal moments of the approximate impulse response function equal to the corresponding moments of the true impulse response function. The zeroth and first moments are modeled with the analytic element method. The zeroth moment may be modeled with existing analytic elements, while new analytic elements are derived for the modeling of the first moment. Moment matching may be applied in the same fashion with other approximate impulse response functions. It is shown that the proposed approach gives accurate results for a circular island through comparison with an exact solution; both a step recharge function and a measured series of 10 years of recharge were used. The presented approach is specifically useful for modeling groundwater dynamics in aquifers with shallow groundwater tables as is demonstrated in a practical application. The analytic element method is a gridless method that allows for the precise placement of ditches and streams that regulate groundwater levels in such aquifers; heads may be computed analytically at any point and at any time. The presented approach may be extended to simulate the effect of other transient stresses (such as fluctuating surface water levels or pumping rates), and to simulate transient effects in multi-aquifer systems.     

State-space representation of radiation forces in time-domain vessel models

The paper presents a method for generating a new and efficient time-domain formulation of the equations of motion for a vessel with frequency-dependent hydrodynamic coefficients. Previous work on this topic has relied on the use of convolution terms, whereas in this work state-space models are used. This leads to a model formulation that is well suited for controller design and simulation.     

降雨对昌黎台地电阻率的干扰分析

昌黎台地电阻率受降雨影响明显, 降雨量越大, 地电阻率下降幅度越大, 两者存在良好的线性关系。 基于昌黎台电测深资料反演的水平层状均匀介质结果, 建立地表薄层电性结构变化模型, 通过影响系数理论定性分析降雨对地电阻率的即时效应, 研究结果显示降雨主要是通过改变地表介质含水量和电性结构造成地电阻率变化的。 利用褶积滤波法定量模拟降雨对地电阻率的短期影响过程, 可以较好去除降雨对地电阻率的即时影响和滞后响应。     

南黄海北部5.3级地震前青岛地电的短临异常

多年来的观测表明,青岛地电的主要干扰因素是地下水位和温度。它们对地电的影响并不是简单的线性关系,而是带有滞后记忆效应的非线性关系。为了较好地消除地下水位和温度的影响,我们采用了非线性的褶积滤波方法,同时采用多元回归法。对地电资料进行综合处理。处理后的地电3个分向的资料都在震前11～12天开始出现明显的短临异常,3个分向的资料的一阶差分曲线也在震前11～12天出现明显的短临异常。     

基于卷积神经网络的速度大脉冲识别方法研究

含速度大脉冲的强地震动具有复杂的特性,人工提取速度大脉冲特征的方法较繁琐,故利用卷积神经网络（CNN）在图像特征自动提取方面的优势,提出基于卷积神经网络图像识别的速度大脉冲识别方法。基于美国太平洋地震工程研究中心NGA-West1数据库提供的强地震动记录,筛选出6 000条非脉冲记录和91条含有速度大脉冲的强地震动记录。采用在原始记录中加入高斯噪声和过采样的方法,使2类记录样本数量达到均衡。利用本文建立的卷积神经网络模型对2类记录速度时程图进行特征自动提取和分类识别,结果显示测试集准确率为99%,表明本文卷积神经网络模型能够自动提取速度大脉冲特征,进而复现已有结果。将本文方法与传统方法进行了对比,结果表明,对含有多个速度脉冲的强地震动记录的识别,本文方法优于传统方法,具有较高的可靠性、鲁棒性、灵活性。     

多波地震深度学习的油气储层分布预测案例

有机并有效利用纵波与转换横波在油气储层敏感度上存在的差异,有助于突出地震油气储层特征,有助于提高地震油气储层分布边界刻画的精度.基于此,本文设计了一种卷积神经网络与支持向量机方法相结合的多波地震油气储层分布预测的深度学习法（Deep Learning Method）.首先,利用莱特准则剔除所生成的多波地震属性中可能存在的异常值降低网络变体数量.然后,通过能突出多波地震油气储层特征的聚类算法和无监督学习算法构建隐藏层,用于增加网络共享,提取油气特征.最后,将增加网络罚值后的井点样本作为支持向量机预测的输入样本,以降采样后的C3卷积层属性作为学习集,进行从已知到未知的地震油气储层的预测.本方案应用于HG地区晚三叠统HGR组的碳酸盐岩油气储层预测,所预测的地震油气储层边界更加清晰,预测结果与实际情况基本吻合.应用结果表明：本论文方案不仅具有可行性,且具有有效性.     

基于卷积神经网络的地震偏移剖面中散射体的定位和成像

本文提出了一种基于深度学习卷积神经网络(CNN)的全波形反演方法,可对地震散射波场中的散射体进行成像和定位.本文的灵感来自如下猜想:在散射波场剖面上的每个点附近的局部波场与该点到各散射体之间的最小距离有关系,并且这个关系可以被CNN网络所识别.我们将该最小距离定义为散射距离场,并将散射距离场的类别(即大小等级)作为CNN网络的预期输出,而输入就是该点附近的局部波场.最后用上述CNN网络对散射波场进行逐点训练和识别.计算结果证实了我们的灵感猜想,即上述CNN网络能够在复杂散射波场中对散射体进行成像.只通过一个训练模型的学习,CNN网络即可反演多种散射模型的偏移剖面,最后得到"类别函数预测值"和"滤波剖面"两种成像结果,由此可以辨识出在复杂的偏移剖面中各散射体的位置.     

Deconvolution with wavelets and vaguelettes

The use of wavelets for the solution of convolution equations is studied as a possible alternative to the well-established Fast Fourier Transform (FFT) technique. Two possible solution strategies are investigated: (1) The use of wavelets for the representation of both the given data and the unknown solution. This leads to an algorithm with good de-noising and data-compression properties. In terms of computational efficiency this algorithm is inferior to FFT. (2) The use of wavelets for the representation of the unknown solution and of so-called vaguelettes for the representations of the given data. This leads to an algorithm which is even faster than FFT. Received: 14 October 1998 / Accepted: 30 November 1999