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1.
电磁波走时层析可用于空洞和孤石等离散块体异常的探测中.在传统电磁波走时层析中,通常采用一个低阶差分泛函来稳定反演过程,而这类泛函都具有光滑约束的性质,在成像结果中难以对此类离散块体异常进行准确的解释.本文基于Tikhonov正则化思想,提出了一种反余切泛函,该泛函具有紧凑约束的性质且无需选择一个聚焦因子.结合弯曲胖射线层析理论和重加权正则化共轭梯度反演算法,对两个理论模型进行了成像效果研究.与低阶差分泛函和最小支撑泛函的成像结果相比,该方法能够更好地突出异常的边界,成像结果中的虚假异常也要更少.同时,还分析讨论了激发电磁波的中心频率以及数据噪音对成像结果的影响.此外,针对一个地下连续墙墙体内部缺陷的现场模型,利用该方法取得了理想的成像结果,良好地揭示了缺陷的形态和位置. 相似文献
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本文基于拟微分算子理论和李代数积分法,根据程函方程和波场坐标变换,提出一种新的适于横向变速介质Kirchhoff叠前深度偏移的地震波走时算法.该算法与Kirchhoff叠前时间偏移所用李代数时间积分表达相比,差异在于增加了波数一次项,且二次项的系数在求积时亦需进行修正.针对单平方根算子象征、李代数积分、指数映射和走时多项式的求解而言,皆需对以往Kirchhoff叠前时间偏移中所用算法进行深化调整.文中数值算例对比了本文李代数积分表达与时间积分的区别,本算法计算结果与线性横向变速介质中的理论值相当吻合.通过走时多项式中各项对结果的影响分析,可知非对称项使计算精度得到了进一步提高.数值试验表明,本算法对横向变速介质中走时求取是可行的,且不需要存储海量走时表,有利于提高Kirchhof叠前深度偏移的精度和效率. 相似文献
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本文使用最小二乘线性迭代反演方法对跨孔雷达直达波初至时数据进行反演,每次迭代过程中,用有限差分法求解走时程函方程,并用高精度快速推进方法(HAFMM)进行波前扩展,通过追踪波前避免了进行射线追踪.为了验证该方案,我们对三组合成数据进行了测试,分析了单位矩阵算子、一阶差分算子和拉普拉斯算子等三种不同模型参数加权算子对模型的约束和平滑效果;讨论了FMM和HAFMM对反演精度的影响;测试了LSQR,GMRES和BICGSTAB等三种矩阵反演算法的反演效果.此外,我们还对一组野外实测数据进行了反演,对比了基于本方案以及基于平直射线追踪和弯曲射线追踪的走时层析成像反演效果.对比分析结果表明,使用拉普拉斯算子和HAFMM进行反演能较好地进行目标体重建,而三种矩阵反演方法对反演效果的影响差别不大;并且通过对波前等时线图的分析可以定性地判断异常体的性质和位置;而在对实测数据目标体的重建上,本方案能达到甚至优于弯曲射线算法的重建效果. 相似文献
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三维地震波走时计算技术是三维地震反演、层析成像、偏移成像等诸多地震数据处理技术中非常重要的正演计算工具.为了获得精度高且兼顾效率的三维走时计算方法:首先,在常规双线性插值公式推导过程中,充分利用平面波双线性假设的结论,获得了二元极小值超越方程的解析解,进而推导出了准确的局部走时计算公式,同时构造性地证明了该计算公式满足地震波的传播规律和Eikonal方程;其次,引入迎风差分的基本思想,提出迎风双线性插值的局部走时计算策略,该计算策略能简化算法、提高效率且保证无条件稳定性;然后,将上述计算公式和迎风双线性插值策略与常规快速推进法中的窄带技术结合,获得了一种新的基于快速推进迎风双线性插值法的三维地震波走时计算方法;最后,通过精度和效率分析检验了新算法的精度、效率和正确性,并通过计算实例验证了算法在面对复杂介质时的稳定性和有效性. 相似文献
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通过在频率域双程波动方程模拟算法中加入一个复数频率（实部表示频率,虚部表示衰减因子）压制地震波初至走时之后的能量,从而把初至走时及其振幅的计算问题转换为单一频率波场中最大能量走时和振幅的拾取问题,然后利用单一频率域波场的相位项和振幅项分别计算初至走时及其振幅.本文还提出利用参数分析方法求取最优的复数频率,并给出数值计算例子,将本方法的计算结果与有限差分程函方程初至走时和最大能量走时振幅进行比较,结果表明,该方法具有适应于任意复杂介质和多炮多接收点走时和振幅的计算. 相似文献
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初至波走时层析是获取近地表速度结构的一种常用方法.随着采集技术的不断发展,可使用的数据量迅速增多,传统的基于射线追踪和解方程组的地震走时层析成像方法面临着内存占用大、方程求解不稳定等问题.为了解决这些问题,本文基于前人在波形反演研究中提出的一种改进的散射积分算法,提出了一种预条件最速下降法初至波走时层析.该方法无需存储核函数矩阵与Hessian矩阵即可方便地实现目标函数梯度的计算与预条件,且该方法计算效率高、求解稳定、易于并行.数值实验结果表明,该方法可以获得与传统方法精度相当的反演结果,但所占用的内存大幅减小. 相似文献
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最短路径射线追踪算法,用预先设置的网络节点的连线表示地震波传播路径,当网络节点稀疏时,获得的射线路径呈之字形,计算的走时比实际走时系统偏大. 本文在波前扩展和反向确定射线路径的过程中,在每个矩形单元内,通过对某边界上的已知走时节点的走时进行线性插值,并利用Fermat原理即时求出从该边界到达其他边界节点的最小走时及其子震源位置和射线路径,发展了相应的动态网络算法. 从而克服了最短路径射线追踪算法的缺陷,大大提高了最小走时和射线路径的计算精度. 相似文献
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《华北地震科学》2015,(3)
利用国内大中城市震害矩阵为样本分析影响建筑物抗震能力的各个因素,提取出主要的震害影响因子。通过海明加权距离法计算出各城市震害矩阵之间的相似度权重,并通过灰色关联法得出各个样本城市震害矩阵与目标城市的关联度,得出差异化权重的关联度矩阵。使用得到的关联矩阵代替层次分析法中的专家打分矩阵,从而减少该方法的主观因素,使得改进层次分析法成为一种可以定量的计算方法。把海明加权距离法、灰色关联法、层次分析法分别根据其各自特点融合在一起,形成了一种全新的震害矩阵拟合算法,解决了3种方法在震害矩阵计算中的局限性。通过对上海市浦东区多层钢混结构房屋进行多元算法的震害预测证明了此种方法的可靠性和可行性。 相似文献
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振幅随偏移距变化是描述储层特征的重要方法之一，保幅偏移方法就是使偏移剖面能够反映出振幅随偏移距的变化.本论文中的保幅偏移是以走时为基础，主要的方法是采用走时的双曲线展开法，通过走时的二阶空间导数来确定波前曲率.该方法通过建立在大网格上的走时表来确定插值系数，将大网格插值成为较为精细的网格，这样就节省了数据的存储空间.对于相同的网格密度，通过插值来计算走时表比采用程函方程有限差分法直接计算走时要节省5至6倍的时间.走时的插值系数还可以用来计算几何扩散因子、权函数，不仅提高了成像质量，还大大节省了计算时间. 相似文献
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Based on the generalized Gauss–Newton method, a new algorithm to minimize the objective function of the penalty method in (Bentley LR. Adv Wat Res 1993;14:137–48) for inverse problems of steady-state aquifer models is proposed. Through detailed analysis of the “built-in” but irregular weighting effects of the coefficient matrix on the residuals on the discrete governing equations, a so-called scaling matrix is introduced to improve the great irregular weighting effects of these residuals adaptively in every Gauss–Newton iteration. Numerical results demonstrate that if the scaling matrix equals the identity matrix (i.e., the irregular weighting effects of the coefficient matrix are not balanced), our algorithm does not perform well, e.g., the computation cost is higher than that of the traditional method, and what is worse is the calculations fail to converge for some initial values of the unknown parameters. This poor situation takes a favourable turn dramatically if the scaling matrix is slightly improved and a simple preconditioning technique is adopted: For naturally chosen simple diagonal forms of the scaling matrix and the preconditioner, the method performs well and gives accurate results with low computational cost just like the traditional methods, and improvements are obtained on: (1) widening the range of the initial values of the unknown parameters within which the minimizing iterations can converge, (2) reducing the computational cost in every Gauss–Newton iteration, (3) improving the irregular weighting effects of the coefficient matrix of the discrete governing equations. Consequently, the example inverse problem in Bentley (loc. cit.) is solved with the same accuracy, less computational effort and without the regularization term containing prior information on the unknown parameters. Moreover, numerical example shows that this method can solve the inverse problem of the quasilinear Boussinesq equation almost as fast as the linear one.In every Gauss–Newton iteration of our algorithm, one needs to solve a linear least-squares system about the corrections of both the parameters and the groundwater heads on all the discrete nodes only once. In comparison, every Gauss–Newton iteration of the traditional method has to solve the discrete governing equations as many times as one plus the number of unknown parameters or head observation wells (Yeh WW-G. Wat Resour Res 1986;22:95–108).All these facts demonstrate the potential of the algorithm to solve inverse problems of more complicated non-linear aquifer models naturally and quickly on the basis of finding suitable forms of the scaling matrix and the preconditioner. 相似文献
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本文发展了一种加权平均方法，用于综合考虑地震危险性分析中的专家意见。其中假定接近综合结果的专家意见具有的权系数较大，这样可以合理反映专家意见的一致性与差异性，另外，利用随机加权方法估计综合结果及权系数的不确定性，给出其统计特征量。 相似文献
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This paper presents a novel intelligent fuzzy weighted input estimation method which effiviently and robustly estimates the unknown ground motion accelerations. The new input estimation method includes the Kalman Filter (KF) and the recursive least square estimator (RLSE), which is weighted by the fuzzy weighting factor proposed based on the fuzzy logic inference system. By directly synthesizing the Kalman filter with the estimator, this work presents an efficient robust forgetting zone, which is capable of providing a reasonable compromise between the tracking capability and the flexibility against noises. The excellent performace of this inverse method is demonstrated by solving the earthquake-excitation estimation problem, and the proposed algorithm is compared by alternating between the constant and adaptive weighting factors. The results reveal that this method has the properties of better target tracking capability and more effective noise reduction. 相似文献
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Total least squares (TLS) can solve the issue of parameter estimation in the errors-invariables (EIV) model, however, the estimated parameters are affected or even severely distorted when the observation vector and coefficient matrix are contaminated by gross errors. Currently, the use of existing robust TLS (RTLS) methods for the EIV model is unreasonable. Original residuals are directly used in most studies to construct the weight factor function, thus the robustness for the structure space is not considered. In this study, a robust weighted total least squares (RWTLS) algorithm for the partial EIV model is proposed based on Newton-Gauss method and the equivalent weight principle of general robust estimation. The algorithm utilizes the standardized residuals to construct the weight factor function and employs the median method to obtain a robust estimator of the variance component. Therefore, the algorithm possesses good robustness in both the observation and structure spaces. To obtain standardized residuals, we use the linearly approximate cofactor propagation law for deriving the expression of the cofactor matrix of WTLS residuals. The iterative procedure and precision assessment approach for RWTLS are presented. Finally, the robustness of RWTLS method is verified by two experiments involving line fitting and plane coordinate transformation. The results show that RWTLS algorithm possesses better robustness than the general robust estimation and the robust total least squares algorithm directly constructed with original residuals. 相似文献
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Spherical harmonic coefficients (SHCs) for the daily magnetic variation fields (solar and lunar) and the main field of the earth are usually estimated by the method of least squares applied to a truncated spherical harmonic series. In this paper, an integral method for computing the SHCs for the solar quiet daily magnetic variation fieldSq is described and applied toSq data for May and June 1965. TheSq SHCs thus derived are then compared with the results obtained using both unweighted and weighted versions of the least squares method. The weighting used tends to orthogonalize the least squares terms. The integral and weighted least squares results agree closely for terms up to order 4 and degree 30, but both disagree considerably for the higher degree terms with the results of the unweighted least squares. Errors introduced by the numerical integration can be shown to be small, hence the disagreement between integral and unweighted least squares coefficient sets arises from improper weighting. Also, it is concluded that discrepancies between the geomagnetic northward and eastward component-derived coefficient sets arise from either time-dependent external sources that produce non-local-time, based fields or nonpotential sources and not from truncation of the spherical harmonic series as has previously been suggested.Deceased. 相似文献
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P波初动符号物理图像明确,是稳定的地震波信息.在资料充分时,可以较好地确定震源机制解.网格搜索法是目前流行的利用P波初动符号求解地震震源机制解的方法.不过,在实际观测资料不充分时,虽然较迭代算法优越,但网格搜索法依然有较大的不确定性.到目前为止,人们还没有找到合理的解决方案,极大地制约了这一类方法的应用.针对这一现状,本文在许忠淮提出的格点尝试法的基础上对网格搜索法进行了几个方面的改进.首先,采用新的加权方法计算加权矛盾比：权重因子包括反映初动符号质量的权重以体现资料质量的影响;不包括反映观测点与节面距离的权重以避免因节面附近资料权重的双重减小带来的系统偏差;通过减小震源球上密集资料点的权重以部分地抵消震源球上P波初动符号资料分布不均匀对可能解的影响.在通过加权矛盾比筛选可能的震源机制解时,把震源球分为面积相对均匀的网格进行解的搜索,避免了因网格划分不均匀所导致的平均解的计算偏差.针对资料不足情况下震源机制解会受控于个别观测点P波初动符号的情况,我们借鉴杰克刀（jackknife）技术,在可选解中增加了那些一个观测点被去除后的可选解,既对解的质量有了更好的把握,又增加了找到真解的可能性.进一步地,针对可选解存在多个解簇的情况,本文提出了通过聚类提供多组可选解的做法.最后,针对目前缺乏对解的合理评价体系的现状,提出了主要基于解的离散度并参考加权最小矛盾比对震源机制解质量进行评价的新方案. 相似文献
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This paper describes application of a fast inversion method to recover a 3D susceptibility model from magnetic anomalies. For this purpose, the survey area is divided into a large number of rectangular prisms in a mesh with unknown susceptibilities. Solving the full set of equations is substantially time consuming, and applying an algorithm to solve it approximately can reduce the time significantly. It is shown that the Lanczos bidiagonalization method can be an appropriate algorithm to solve a Tikhonov cost function for this purpose. Running time of the inverse modeling significantly decreases by replacing the forward operator matrix with a matrix of lower dimension. A weighted generalized cross validation method is implemented to choose an optimum value of a regularization parameter. To avoid the natural tendency of magnetic structures to concentrate at shallow depth, a depth weighting is applied. This study assumes that there is no remanent magnetization. The method is applied on a noise-corrupted synthetic data to demonstrate its suitability for 3D inversion. A case study including ground based measurement of magnetic anomalies over a porphyry-Cu deposit located in Kerman providence of Iran, Now Chun deposit, is provided to show the performance of the new algorithm on real data. 3D distribution of Cu concentration is used to evaluate the obtained results. The intermediate susceptibility values in the constructed model coincide with the known location of copper mineralization. 相似文献
18.
Application of Large‐Scale Inversion Algorithms to Hydraulic Tomography in an Alluvial Aquifer 
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下载免费PDF全文 P. Fischer A. Jardani A. Soueid Ahmed M. Abbas X. Wang H. Jourde N. Lecoq 《Ground water》2017,55(2):208-218
Large‐scale inversion methods have been recently developed and permitted now to considerably reduce the computation time and memory needed for inversions of models with a large amount of parameters and data. In this work, we have applied a deterministic geostatistical inversion algorithm to a hydraulic tomography investigation conducted in an experimental field site situated within an alluvial aquifer in Southern France. This application aims to achieve a 2‐D large‐scale modeling of the spatial transmissivity distribution of the site. The inversion algorithm uses a quasi‐Newton iterative process based on a Bayesian approach. We compared the results obtained by using three different methodologies for sensitivity analysis: an adjoint‐state method, a finite‐difference method, and a principal component geostatistical approach (PCGA). The PCGA is a large‐scale adapted method which was developed for inversions with a large number of parameters by using an approximation of the covariance matrix, and by avoiding the calculation of the full Jacobian sensitivity matrix. We reconstructed high‐resolution transmissivity fields (composed of up to 25,600 cells) which generated good correlations between the measured and computed hydraulic heads. In particular, we show that, by combining the PCGA inversion method and the hydraulic tomography method, we are able to substantially reduce the computation time of the inversions, while still producing high‐quality inversion results as those obtained from the other sensitivity analysis methodologies. 相似文献
19.
ABSTRACTA new deep extreme learning machine (ELM) model is developed to predict water temperature and conductivity at a virtual monitoring station. Based on previous research, a modified ELM auto-encoder is developed to extract more robust invariance among the water quality data. A weighted ELM that takes seasonal variation as the basis of weighting is used to predict the actual value of water quality parameters at sites which only have historical data and no longer generate new data. The performance of the proposed model is validated against the monthly data from eight monitoring stations on the Zengwen River, Taiwan (2002–2017). Based on root mean square error, mean absolute error, mean absolute percentage error and correlation coefficient, the experimental results show that the new model is better than the other classical spatial interpolation methods. 相似文献
20.
基于稀疏反演的地震插值方法是一种重要的插值方法,然而大多数这类方法只针对无噪声数据或者高信噪比数据插值.实际上,地震数据含有各种噪声,使得插值问题变得更加困难.凸集投影方法是一种高效的插值算法,但是对于含噪声数据的插值效果不理想,针对含噪声数据提出的加权凸集投影方法能够实现同时插值和去噪,但是除了最小阈值需要认真选取外,增加一个权重因子来实现去噪功能.本文由迭代阈值算法推导出加权凸集投影方法,证明其是解无约束优化问题的一种方法,加权因子可以看作拟合误差项的系数.本文还提出了一种改进的凸集投影方法,与原始凸集投影方法相比该方法不需要增加任何计算量,只要通过阈值的选择来进行插值和去噪.数值模拟证明了该算法的计算效率,并且对含噪声数据能够实现较好的插值效果;先插值后去噪的结果证明了同时去噪和插值算法的可靠性和稳定性. 相似文献