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本文应用动态灰箱方法分析安丘台基线观测资料,给出了曲线正常变化形态,识别出1988年以来安丘基线的伸长反向加速现象。经计算认为安丘—莒县断裂北段年扭动量0.40毫米,主压应力轴方向N 40°W。 相似文献
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针对辽宁省数字化地电阻率观测数据的特点,找出同步高频变化干扰数据的识别及处理方法;观测资料中缺测数据的干扰识别及处理方法;无物理基础的观测量值识别及处理方法等;通过VB编程快捷、方便地剔除瞬时干扰数据,有利于地震预报人员对数字化观测干扰数据的处理,并对地下介质的动态变化做出正确的分析、判断. 相似文献
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长期过量开采地下水,使地下水位持续下降、水质发生变化,动水位观测井断流;地面沉降造成井管上窜,观测管路系统被损坏等,这些现象对地震地下流体观测地震前兆异常的正确判断带来很大困难。应用水文地质理论与方法,分析含水层的水均衡状态、应力-应变状态及其与水位动态的关系,初步探讨了超采区井水位异常性质的理论与方法。结果表明,根据井孔所在区水位下降漏斗的扩散特征,结合以上所提到的理论和方法,依据资料多年变化特征,可以较准确地判断异常的性质。研究结果有助于区分单一集中抽水与长期地下水超采对水位观测的影响,有助于正确识别超采区水位前兆异常,有助于地震分析预报水平的提高 相似文献
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潜井分布广泛,便于观测,是群测队伍宏观观测的主要手段之一.但由于潜水位干扰大,异常信息不易提取,使单井观测的有效性受到限制.本文分析了区域潜水位变量的分布特征,提出在对地震敏感地段开展群井观测,用假设检验的方法判断潜水位变量的异常显著性是可行的,有一定的实用意义. 相似文献
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观测数据质量受到诸多因素影响,为判断更改测量频率是否会对数据质量造成影响,选取江苏省4个断层形变台站水准观测场地不同观测频率下短水准测量数据,采用几种常用数据质量评价方法进行分析,结果表明,更改测量频率不会对水准数据观测质量与映震效能产生实质性影响。 相似文献
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云南地区大震前地倾斜趋势性异常的典型特征 总被引：2，自引：0，他引：2
用云南地区地倾斜观测资料,分析研究了澜沧 -耿马7.6级地震、丽江7.0级地震前的趋势性变化的典型特征,认为在云南7.0级以上地震前,云南地区地倾斜各分项测值在震前3年内普遍存在一些典型变化形态特征:东西向大多数表现为首先加速东倾,然后又反向加速西倾的典型特征;北南向有的表现首先加速南倾 ,然后又反向加速北倾的典型特征;有的表现首先加速北倾,然后又反向加速南倾的典型特征.这个过程开始加速和反向加速的时间虽不一致,开始加速一般在震前3年左右,而且似乎距离震中越近的测项,反向加速出现的越晚,其速率也较大. 相似文献
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通过对河北省4个地电场台站的观测资料全面分析判断,总结地电场干扰变化的可能因素;对"十五"新建的两个地电台站受到的干扰做出分析、判断;并结合台站实际观测环境,解决干扰源,对提高观测资料质量有一定的意义. 相似文献
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Parameter identification is an essential step in constructing a groundwater model. The process of recognizing model parameter values by conditioning on observed data of the state variable is referred to as the inverse problem. A series of inverse methods has been proposed to solve the inverse problem, ranging from trial-and-error manual calibration to the current complex automatic data assimilation algorithms. This paper does not attempt to be another overview paper on inverse models, but rather to analyze and track the evolution of the inverse methods over the last decades, mostly within the realm of hydrogeology, revealing their transformation, motivation and recent trends. Issues confronted by the inverse problem, such as dealing with multiGaussianity and whether or not to preserve the prior statistics are discussed. 相似文献
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关于区域性的地震面波层析反演方法的讨论 总被引：4，自引：0，他引：4
讨论了在地球表面局部区域进行面波层析反演时所用的各种反演方法，指出各种方法用于区域性层析反演时的优缺点，并就由面波资料对区域性的地壳和上地幔结构进行反演的方法──分块反演方法、本征函数展开法、球面雷当变换方法、Ｔａｒａｎｔｏｌａ概率方法和波形反演的方法进行了讨论。指出了各种方法的优缺点及适用范围，并对一些方法进行了数值模拟，给出了计算实例。关键词 相似文献
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Anyone working on inverse problems is aware of their ill-posed character. In the case of inverse problems, this concept (ill-posed) proposed by J. Hadamard in 1902, admits revision since it is somehow related to their ill-conditioning and the use of local optimization methods to find their solution. A more general and interesting approach regarding risk analysis and epistemological decision making would consist in analyzing the existence of families of equivalent model parameters that are compatible with the prior information and predict the observed data within the same error bounds. Otherwise said, the ill-posed character of discrete inverse problems (ill-conditioning) originates that their solution is uncertain. Traditionally nonlinear inverse problems in discrete form have been solved via local optimization methods with regularization, but linear analysis techniques failed to account for the uncertainty in the solution that it is adopted. As a result of this fact uncertainty analysis in nonlinear inverse problems has been approached in a probabilistic framework (Bayesian approach), but these methods are hindered by the curse of dimensionality and by the high computational cost needed to solve the corresponding forward problems. Global optimization techniques are very attractive, but most of the times are heuristic and have the same limitations than Monte Carlo methods. New research is needed to provide uncertainty estimates, especially in the case of high dimensional nonlinear inverse problems with very costly forward problems. After the discredit of deterministic methods and some initial years of Bayesian fever, now the pendulum seems to return back, because practitioners are aware that the uncertainty analysis in high dimensional nonlinear inverse problems cannot (and should not be) solved via random sampling methodologies. The main reason is that the uncertainty “space” of nonlinear inverse problems has a mathematical structure that is embedded in the forward physics and also in the observed data. Thus, problems with structure should be approached via linear algebra and optimization techniques. This paper provides new insights to understand uncertainty from a deterministic point of view, which is a necessary step to design more efficient methods to sample the uncertainty region(s) of equivalent solutions. 相似文献
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详细研究了一般地球物理反问题的迭代优化求解过程与物理学中原子跃迁过程的对应关系,建立了反演问题中模型空间、初始模型、局部极值模型、最优化模型等与原子的态空间、定态、激发态、基态等的对应关系. 在此基础上,模拟了物理学中原子从激发态向基态跃迁的物理过程,建立了一种与原子跃迁过程相对应的非线性随机跃迁数学模型和模型解跃迁搜索准则,导出了适用于一般地球物理资料的模拟原子跃迁的非线性反演算法. 用理论测试函数对这种新的反演方法进行了数值试验,结果表明该方法具有解不依赖于初始模型、收敛速度快等优点. 相似文献
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M. N. Berdichevsky V. I. Dmitriev M. S. Zhdanov 《Izvestiya Physics of the Solid Earth》2010,46(8):648-654
Approaches to the solution of three-dimensional inverse problems are considered in the paper. The main methods for regularization of inverse problems of electromagnetic sounding are reviewed. Basic scenarios of three-dimensional and multicriterion interpretation are considered. 相似文献
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Regularization methods are used to recover a unique and stable solution in ill-posed geophysical inverse problems. Due to the connection of homogeneous operators that arise in many geophysical inverse problems to the Fourier basis, for these operators classical regularization methods possess some limitations that one may try to circumvent by wavelet techniques.
In this paper, we introduce a two-step wavelet-based regularization method that combines classical regularization methods with wavelet transform to solve ill-posed linear inverse problems in geophysics. The power of the two-step wavelet-based regularization for linear inversion is twofold. First, regularization parameter choice is straightforward; it is obtained from a priori estimate of data variance. Second, in two-step wavelet-based regularization the basis can simultaneously diagonalize both the operator and the prior information about the model to be recovered. The latter is performed by wavelet-vaguelette decomposition using orthogonal symmetric fractional B-spline wavelets.
In the two-step wavelet-based regularization method, at the first step where fully classical tools are used, data is inverted for the Moore-Penrose solution of the problem, which is subsequently used as a preliminary input model for the second step. Also in this step, a model-independent estimate of data variance is made using nonparametric estimation and L-curve analysis. At the second step, wavelet-based regularization is used to partially recover the smoothness properties of the exact model from the oscillatory preliminary model.
We illustrated the efficiency of the method by applying on a synthetic vertical seismic profiling data. The results indicate that a simple non-linear operation of weighting and thresholding of wavelet coefficients can consistently outperform classical linear inverse methods. 相似文献
In this paper, we introduce a two-step wavelet-based regularization method that combines classical regularization methods with wavelet transform to solve ill-posed linear inverse problems in geophysics. The power of the two-step wavelet-based regularization for linear inversion is twofold. First, regularization parameter choice is straightforward; it is obtained from a priori estimate of data variance. Second, in two-step wavelet-based regularization the basis can simultaneously diagonalize both the operator and the prior information about the model to be recovered. The latter is performed by wavelet-vaguelette decomposition using orthogonal symmetric fractional B-spline wavelets.
In the two-step wavelet-based regularization method, at the first step where fully classical tools are used, data is inverted for the Moore-Penrose solution of the problem, which is subsequently used as a preliminary input model for the second step. Also in this step, a model-independent estimate of data variance is made using nonparametric estimation and L-curve analysis. At the second step, wavelet-based regularization is used to partially recover the smoothness properties of the exact model from the oscillatory preliminary model.
We illustrated the efficiency of the method by applying on a synthetic vertical seismic profiling data. The results indicate that a simple non-linear operation of weighting and thresholding of wavelet coefficients can consistently outperform classical linear inverse methods. 相似文献
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Doug Oldenburg 《Surveys in Geophysics》1990,11(2-3):231-270
This paper explores some of the newer techniques for acquiring and inverting electromagnetic data. Attention is confined primarily to the 2d magnetotelluric (MT) problem but the inverse methods are applicable to all areas of EM induction. The basis of the EMAP technique of Bostick is presented along with examples to illustrate the efficacy of that method in structural imaging and in overcoming the deleterious effects of near-surface distortions of the electric field. Reflectivity imaging methods and the application of seismic migration techniques to EM problems are also explored as imaging tools. Two new approaches to the solution of the inverse problem are presented. The AIM (Approximate Inverse Mapping) inversion of Oldenburg and Ellis uses a new way to estimate a perturbation in an iterative solution which does not involve linearization of the equations. The RRI (Rapid Relaxation Inverse) of Smith and Booker shows how approximate Fréchet derivatives and sequences of 1d inversions can be used to develop a practical inversion algorithm. The overview is structured to provide insight about the latest inversion techniques and also to touch upon most areas of the inverse problem that must be considered to carry out a practical inversion. These include model parameterization, methods of calculating first order sensitivities, and methods for setting up a linearized inversion. 相似文献
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作为全局非线性优化的新方法之一的遗传算法,近年来已从生物工程流行到大地电磁测深资料解释中.然而,大地电磁反演问题具有不适定性,解的非唯一性.通过结合求解不适定问题的Tikhonov正则化方法,本文采用实数编码遗传算法求解大地电磁二维反演问题.此算法在构建目标函数时引入正则化的思想,利用遗传算法求解最优化问题.常规的基于局部线性化的最优化反演方法易使解陷入局部极小值,而且严重的依赖初始模型的选择.与传统线性化的迭代反演方法相比,实数编码遗传算法能够克服传统方法的不足且能获得更好的反演结果.通过对大地电磁测深理论模型进行计算,结果表明:该算法具有收敛速度快、解的精度高和避免出现早熟等优点,可用于大地电磁资料解释. 相似文献
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对于迭代方式的参数化反演方法,如何使反演结果稳定地收敛到整体极小仍是目前大地电磁（MT）反演中急需解决的问题．本文利用小波变换理论中的多尺度分析方法将大地电磁反问题分解为依赖于尺度变量的反问题序列,然后按尺度从大到小的次序依次求解,求解过程中前一个尺度反问题的解作为下一个尺度反问题的初始模型,直到来出对应于尺度为0的原反问题的解为止．该方法称为多尺度反演方法．数值试验和实际资料的反演结果表明,该方法可有效改善传统广义逆反演方法易陷入局部极小的弊端． 相似文献