b值的稳健估计及其在地震预报中的应用

利用Ｍ估计的稳健回归方法,选取ψ函数为正态密度型函数,计算震级－频度关系中的ｂ值,并会计了稳健估计方法与最小二乘估计所得结果的差异。认为由稳健估计得到的ｂ值更加符合震级－频度关系中的大小比例,可作为可靠的背景值使用。作为应用实例对新疆地区ｂ值进行空间及时间扫描,并定义最小二乘估计ｂ值与稳健估计ｂ值的偏差,以此为中强震的前兆判定指标,对喀什－巴楚地区８０年代以来６级以上地震前的异常进行讨论,认为该指     

稳健估计b值及中强震异常特征研究

利用M估计的稳健回归方法，选取ψ函数为正态密度型函数，计算震级-频度关系中的b值，对基于随机泊松分布的模拟地震样本及天然地震样本，用稳健估计方法与最小二乘方法计算b值后进行比较得出，对于天然地震样本，稳健估计得到的b值更加符合震级-频度关系，作为应用实例，将最小二第六估计法b值与稳健估计b值更加符合震级-频度关系，作为应用实例，将最小二乘估计法b值与稳健估计b值的偏离度作为中强震的前兆判定指标，对新疆地区b值进行时间扫描，在对北天山及南天山东段Ms≥5、南天山西段Ms≥6级地震前异常特征进行讨论后，认为该指标作为中甜地震预报指标具有一定的实用性。     

地壳形变分析的抗差最小二乘配置迭代解法

利用最小二乘配置进行地壳形变分析,其结果的合理性关键在于经验协方差函数的拟合.考虑到观测数据存在粗差的情况,提出基于观测值中位数初值的抗差最小二乘配置方法和基于中位参数法的抗差最小二乘配置方法.两种方法首先分别利用观测值中位数给出观测值初始权阵以及利用中位参数法给出最小二乘配置初始解,然后均在给定协方差函数参数初始值的情况下,应用合适的等价权进行抗差估计并通过迭代计算,最终获得稳健的协方差函数参数估值及最小二乘配置解.利用本文提出的两种方法以及传统方法分别对庐山地震的GPS垂直位移数据和意大利L'Aquila地震的InSAR同震位移数据进行处理分析.结果表明:相对传统方法,基于观测值中位数初值的抗差最小二乘配置方法效果更好,更具稳健性.     

大地电磁阻抗张量的改进截断最小二乘估计

近年来,稳健性估计方法已被广泛地应用于大地电磁(MT)阻抗张量估计中.和传统的最小二乘估计相比,它能较好地改善MT阻抗估计的抗噪性.然而,这两类方法的抗干扰能力及其估计结果的置信度仍不能满足当下资源探测"攻深找盲"的需求.本文介绍了一种改进的截断最小二乘估计(LTS)方法.我们首先通过稳健的马氏距离来识别并剔除品质极差的观测数据,然后通过广义的复数截断最小二乘估计出阻抗张量初始值,最后用重加权最小二乘方法(RLS)来改进阻抗张量的统计有效性.一系列的模型数据和野外数据试算表明我们提出的这个方法是有效的.改进截断最小二乘估计方法不仅具备传统LTS崩溃点高的优点,而且因为采用了重加权最小二乘方法,能够取得较高的统计有效性.此外在LTS算法的计算过程中,我们使用了一些加速策略,表现出很高的计算效率.     

稳健统计用于扩频激电数据预处理与脉冲噪声压制

在扩频激电数据预处理中,传统的均值叠加与基于叠加后数据的数字滤波方法并不能对脉冲噪声进行有效压制.脉冲噪声的影响会保留到复电阻率频谱中,对激电参数的计算产生不利影响.本文针对现有数据处理方法压制脉冲噪声的不足,提出将稳健统计方法应用于扩频激电数据预处理,主要包括将稳健最小二乘回归用于线性趋势项消除和将稳健M估计用于周期数据叠加.通过模拟数据测试为稳健统计方法选择合适的影响函数与迭代算法,然后将其应用于实测的扩频激电数据预处理.通过对处理结果与计算误差进行对比分析,发现稳健统计方法对脉冲噪声和高斯噪声都有较好的压制作用.相比于均值叠加,稳健统计可减小数据计算误差,提高数据预处理质量;同时提高计算结果随叠加次数的收敛速度,节省观测时间.     

正交最小二乘法在确定台站震级偏差校正公式中的应用

经典最小二乘回归模型假设自变量没有误差而所有误差都集中于响应变量,但是许多应用领域中实际问题的自变量含有噪声数据,往往不符合这个假设,经典最小二乘回归模型不再适用。为克服这一缺陷,介绍了正交最小二乘回归模型和参数估计算法。对经典最小二乘和正交最小二乘回归系数进行了理论分析和计算机数值仿真,结果表明当自变量和响应变量都含有误差时,正交最小二乘法优于经典最小二乘法。最后将经典最小二乘法和正交最小二乘法用于蒙城地震台2001-2006年地震数据,确定了台站震级偏差校正公式,并对它们的结果进行了详细比较。     

最小二乘偏移成像方法及应用

基于反演理论的最小二乘偏移可为岩性储层估计提供更加保真的、高分辨率反射系数成像,成为当前成像方法的研究热点和发展趋势.研究讨论了实现过程中关键技术环节,包括有限差分解微分方程进行反偏移数据重构,基于数据残差逆时偏移求取梯度及共轭梯度法反演优化算法,并重点研究了最小二乘偏移用于实际处理时的数据残差求取方法,包括面向最小二乘偏移技术的观测数据预处理及能量一致性数据残差求取,探索建立了面向实际资料的最小二乘逆时偏移实现流程,模型和实际资料试处理说明了此方法技术的适用性和有效性.     

利用地形变观测量求解地壳水平应变场的方法

在前人工作基础上,初步研究建立了利用多种地形变资料联合求解地壳应变连续分布的方法途径和数学模型。包括利用多种地形变观测资料整体解算测区分单元的应变张量的最小二乘平差模型,以及借助最小二乘配置进行应变空间连续分布估计的方法,并给出了对临潼水平形变网监测资料的试算结果。     

地震震级—频度关系b值参数的稳健估计

文中依据古登堡－里克特震级－频度公式，结合实例说明了参数ｂ值的稳健估计方法，并将其与最小二乘法及最大似然法比较，结果表明，一般情况下，稳健估算结果与实际数据分布较吻合，并且可以在不剔除低震级段和大震级的偏离分布值的情况下，取得与选取合理震级上下限最小二乘法一致的结果，此外，稳健估计结果的余差分析同样也得到地震震级－频度关系不是简单的对数线性关系的结果，而原始Ｇ－Ｒ公式需加二以上的高次项才能较好地押     

地震震级－频度关系b值参数的稳健估计

文中依据古登堡－里克特（Ｇ－Ｒ）震级－频度公式，结合实例说明了参数ｂ值的稳健估计方法，并将其与最小二乘法及最大似然法比较。结果表明，一般情况下，稳健估算结果与实际数据分布较吻合，并且可以在不剔除低震级段和大震级段的偏离分布值的情况下，取得与选取合理震级上下限后最小二乘法一致的结果。此外，稳健估计结果的余差分析同样也得到地震震级－频度关系不是简单的对数线性关系的结果，而原始Ｇ－Ｒ公式需加二次以上的高次项才能较好地描述该特性。     

Joint solution of leveling and gravity data in crustal deformation monitoring

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Geoid and Sea Surface Topography Derived from ERS-1 Altimeter Data by the Adjoint Method

A method for splitting sea surface height measurements from satellite altimetry into geoid undulations and sea surface topography is presented. The method is based on a combination of the information from altimeter data and a dynamic sea surface height model. The model consists of geoid undulations and a quasi-geostrophic model for expressing the sea surface topography. The goal is the estimation of those values of the parameters of the sea surface height model that provide a least-squares fit of the model to the data. The solution is accomplished by the adjoint method which makes use of the adjoint model for computing the gradient of the cost function of the least-squares adjustment and an optimization algorithm for obtaining improved parameters. The estimation is applied to the North Atlantic. ERS-1 altimeter data of the year 1993 are used. The resulting geoid agrees well with the geoid of the EGM96 gravity model.     

分段回归在剔除精河、库尔勒水平摆气象因素影响的探索

以精河、库尔勒水平摆观测数据为因变量,以地温、气温、气压为自变量进行分段回归分析,结果如下:(1)地温和气温是影响精河、库尔勒水平摆观测数据年频段信息的主要因素,它们之间具有准线性关系;(2)去掉趋势后,观测数据与地温、气温、气压之间的线性相关性明显增强,说明观测数据的趋势转折变化不是气象因素造成的,可能是观测区域的构造应力变化所致;(3)研究表明分段回归是全样本回归分析方法的一种改进,是降低时间序列数据处理难度的有效方法。     

Comparison of different mass transport calculation methods for wind erosion quantification purposes

Quantitative estimation of the material transported by the wind under field conditions is essential for the study and control of wind erosion. A critical step of this calculation is the integration of the curve that relates the variation of the amount of the material carried by the wind with height. Several mathematical procedures have been proposed for this calculation, but results are scarce and controversial. One objective of this study was to assess the efficiency of three mathematical models (a rational, an exponential, and a simplified Gaussian function) for the calculation of the mass transport, as compared to the linear spline interpolation. Another objective of this study was to compare the mass transport calculated from field measurements obtained from a minimum of three discrete sampling heights with measurements of nine sampling heights. With this purpose, wind erosion was measured under low surface roughness conditions on an Entic Haplustoll during 25 events. The rational function was found to be mathematically limited for the estimation of wind eroded sediment mass flux. The simplified Gaussian model did not fit to the vertical mass flux profile data. Linear spline interpolation generally produced higher mass transport estimates than the exponential equation, and it proved to be a very flexible and robust method. Using different sampling arrangements and different mass flux models can produce differences of more than 45% in mass transport estimates, even under similar field conditions. Under the conditions of this study, at least three points between the soil surface and 1·5 m high, including one point as closest as possible to the surface, should be sampled in order to obtain accurate mass transport estimates. Additionally, the linear spline interpolation and the non‐linear regression using an exponential model, proved to be mathematically reliable methods for calculating the mass transport. Copyright © 2010 John Wiley & Sons, Ltd.     

BAYESIAN ESTIMATION IN SEISMIC INVERSION. PART I: PRINCIPLES1

This paper gives a review of Bayesian parameter estimation. The Bayesian approach is fundamental and applicable to all kinds of inverse problems. Its basic formulation is probabilistic. Information from data is combined with a priori information on model parameters. The result is called the a posteriori probability density function and it is the solution to the inverse problem. In practice an estimate of the parameters is obtained by taking its maximum. Well-known estimation procedures like least-squares inversion or l₁ norm inversion result, depending on the type of noise and a priori information given. Due to the a priori information the maximum will be unique and the estimation procedures will be stable except (in theory) for the most pathological problems which are very unlikely to occur in practice. The approach of Tarantola and Valette can be derived within classical probability theory. The Bayesian approach allows a full resolution and uncertainty analysis which is discussed in Part II of the paper.     

VELOCITY-STACK PROCESSING1

A conventional velocity-stack gather consists of constant-velocity CMP-stacked traces. It emphasizes the energy associated with the events that follow hyperbolic traveltime trajectories in the CMP gather. Amplitudes along a hyperbola on a CMP gather ideally map onto a point on a velocity-stack gather. Because a CMP gather only includes a cable-length portion of a hyperbolic traveltime trajectory, this mapping is not exact. The finite cable length, discrete sampling along the offset axis and the closeness of hyperbolic summation paths at near-offsets cause smearing of the stacked amplitudes along the velocity axis. Unless this smearing is removed, inverse mapping from velocity space (the plane of stacking velocity versus two-way zero-offset time) back to offset space (the plane of offset versus two-way traveltime) does not reproduce the amplitudes in the original CMP gather. The gather resulting from the inverse mapping can be considered as the model CMP gather that contains only the hyperbolic events from the actual CMP gather. A least-squares minimization of the energy contained in the difference between the actual CMP gather and the model CMP gather removes smearing of amplitudes on the velocity-stack gather and increases velocity resolution. A practical application of this procedure is in separation of multiples from primaries. A method is described to obtain proper velocity-stack gathers with reduced amplitude smearing. The method involves a t²-stretching in the offset space. This stretching maps reflection amplitudes along hyperbolic moveout curves to those along parabolic moveout curves. The CMP gather is Fourier transformed along the stretched axis. Each Fourier component is then used in the least-squares minimization to compute the corresponding Fourier component of the proper velocity-stack gather. Finally, inverse transforming and undoing the stretching yield the proper velocity-stack gather, which can then be inverse mapped back to the offset space. During this inverse mapping, multiples, primaries or all of the hyperbolic events can be modelled. An application of velocity-stack processing to multiple suppression is demonstrated with a field data example.     

河北北部2005年前强震危险性预测研究

从信息论及贝叶斯模型出发,以长期异常背景为基础,近期异常为依据,在对未来十年Ｒ度的地震趋势进行估计的条件下,预测了河北北部２００５年前强震危险性,给出了区域内强震发生和各裂度概率的空间分布。     

基于保角变换的双谱域相位谱估计方法及其在地震子波估计中的应用(英文)

地震子波估计是地震资料处理与解释中的重要环节,它的准确与否直接关系到反褶积及反演等结果的好坏。高阶谱(双谱和三谱)地震子波估计方法是一类重要的、新兴的子波估计方法,然而基于高阶谱的地震子波估计往往因为高阶相位谱卷绕的原因,导致子波相位谱求解产生偏差,进而影响了混合相位子波估计的效果。针对这一问题,本文在双谱域提出了一种基于保角变换的相位谱求解方法。通过缩小傅里叶相位谱的取值范围,有效避免了双谱相位发生卷绕的情况,从而消除了原相位谱估计中双谱相位卷绕的影响。该方法与最小二乘法相位谱估计相结合,构成了基于保角变换的最小二乘地震子波相位谱估计方法,并与最小二乘地震子波振幅谱估计方法一起,应用到了地震资料混合相位子波估计中。理论模型和实际资料验证了该方法的有效性。同时本文将双谱域地震子波相位谱估计中保角变换的思想推广到三谱域地震子波相位谱估计中。     

Viscoacoustic least-squares reverse-time migration of different-order free-surface multiples

Multiples have longer propagation paths and smaller reflection angles than primaries for the same source–receiver combination, so they cover a larger illumination area. Therefore, multiples can be used to image shadow zones of primaries. Least-squares reverse-time migration of multiples can produce high-quality images with fewer artefacts, high resolution and balanced amplitudes. However, viscoelasticity exists widely in the earth, especially in the deep-sea environment, and the influence of Q attenuation on multiples is much more serious than primaries due to multiples have longer paths. To compensate for Q attenuation of multiples, Q-compensated least-squares reverse-time migration of different-order multiples is proposed by deriving viscoacoustic Born modelling operators, adjoint operators and demigration operators for different-order multiples. Based on inversion theory, this method compensates for Q attenuation along all the propagation paths of multiples. Examples of a simple four-layer model, a modified attenuating Sigsbee2B model and a field data set suggest that the proposed method can produce better imaging results than Q-compensated least-squares reverse-time migration of primaries and regular least-squares reverse-time migration of multiples.