共查询到20条相似文献，搜索用时 125 毫秒
1.
目前,有关伴随状态法初至波走时层析成像方法的文献,基本上都是基于面积分来定义目标函数,由此得到的伴随方程也都依赖于地表的法向量.这样,一方面会因为伴随变量计算的不准确而造成梯度的不合理,另一方面也无法合理地处理井中观测问题.本文从理论或数值试验角度指出了这些问题,并提出了不依赖地表法向量的改进的伴随状态法走时层析成像方法.主要改进包括:(1)采用体积分定义目标函数,避免了传统方法不能较好处理井中观测数据的缺陷,可以适应任意地表或井中观测系统.(2)采用摄动法得到了新的伴随方程,克服了传统方法中伴随场计算需要依赖于地表法向量的缺陷,使得检波点处的走时残差可以正确地反传播至地下,进而得到更加合理的速度修正方向,提高了速度反演的精度. 相似文献
2.
Recent advances in commodity high-performance computing technology have dramatically reduced the computational cost for solving the seismic wave equation in complex earth structure models. As a consequence, wave-equation-based seismic tomography techniques are being actively developed and gradually adopted in routine subsurface seismic imaging practices. Wave-equation travel-time tomography is a seismic tomography technique that inverts cross-correlation travel-time misfits using full-wave Fréchet kernels computed by solving the wave equation. This technique can be implemented very efficiently using the adjoint method, in which the misfits are back-propagated from the receivers (i.e., seismometers) to produce the adjoint wave-field and the interaction between the adjoint wave-field and the forward wave-field from the seismic source gives the gradient of the objective function. Once the gradient is available, a gradient-based optimization algorithm can then be adopted to produce an optimal earth structure model that minimizes the objective function. This methodology is conceptually straightforward, but its implementation in practical situations is highly complex, error-prone and computationally demanding. In this study, we demonstrate the feasibility of automating wave-equation travel-time tomography based on the adjoint method using Kepler, an open-source software package for designing, managing and executing scientific workflows. The workflow technology allows us to abstract away much of the complexity involved in the implementation in a manner that is both robust and scalable. Our automated adjoint wave-equation travel-time tomography package has been successfully applied on a real active-source seismic dataset. 相似文献
3.
The variational method of data assimilation is used to solve an inverse problem in the transport of sediment in river, which
plays an important role in the change of natural environment. The cost function is defined to measure the error between model
predictions and field observations. The adjoint model of IAP river sedimentation model is created to obtain the gradient of
the cost function with respect to control variables. The initial conditions are taken as the control variables; their optimal
values can be retrieved by minimizing the cost function with limited memory quasi-Newton method (LMQN). The results show that
the adjoint method approach can successfully make the model prediction well fit the simulated observations. And it is expected
to use this method to solve other inverse problems of river sedimentation. But some numerical problems need to be discussed
before applying to real river data.
Project partially supported by the State Key Laboratory of Numerical Modelling for Atmospheric Sciences and Geophysical Fluid
Dynamics, Institute of Atmospheric Physics, Chinese Academy of Sciences 相似文献
4.
从二维麦克斯韦方程组出发推导出反演介电常数和电导率等二维介质物性参数的反演公式.反演的步骤是: 建立初始猜测模型，利用电磁波时间域有限差分法模拟正演数据，用正演数据与观测数据之间的数据残差建立目标函数，通过引入一个由麦克斯韦方程计算的伴随场，将目标函数对介质参数的导数表示成显式形式，应用最优化理论得出对初始猜测模型的修改，用共轭梯度法迭代，最终得到反演结果.用合成数据反演具有粗糙地表的非导电介质的介电常数，用实验数据同时反演介电常数和电导率，并比较了麦克斯韦方程反演结果与声波方程反演结果、波动方程偏移剖面的差异. 相似文献
5.
《中国科学:地球科学(英文版)》2015,(3)
Conditional nonlinear optimal perturbation(CNOP) is an extension of the linear singular vector technique in the nonlinear regime.It represents the initial perturbation that is subjected to a given physical constraint,and results in the largest nonlinear evolution at the prediction time.CNOP-type errors play an important role in the predictability of weather and climate.Generally,when calculating CNOP in a complicated numerical model,we need the gradient of the objective function with respect to the initial perturbations to provide the descent direction for searching the phase space.The adjoint technique is widely used to calculate the gradient of the objective function.However,it is difficult and cumbersome to construct the adjoint model of a complicated numerical model,which imposes a limitation on the application of CNOP.Based on previous research,this study proposes a new ensemble projection algorithm based on singular vector decomposition(SVD).The new algorithm avoids the localization procedure of previous ensemble projection algorithms,and overcomes the uncertainty caused by choosing the localization radius empirically.The new algorithm is applied to calculate the CNOP in an intermediate forecasting model.The results show that the CNOP obtained by the new ensemble-based algorithm can effectively approximate that calculated by the adjoint algorithm,and retains the general spatial characteristics of the latter.Hence,the new SVD-based ensemble projection algorithm proposed in this study is an effective method of approximating the CNOP. 相似文献
6.
A multiscale adjoint (MSADJ) method is developed to compute high-resolution sensitivity coefficients for subsurface flow in large-scale heterogeneous geologic formations. In this method, the original fine-scale problem is partitioned into a set of coupled subgrid problems, such that the global adjoint problem can be efficiently solved on a coarse grid. Then, the coarse-scale sensitivities are interpolated to the local fine grid by reconstructing the local variability of the model parameters with the aid of solving embedded adjoint subproblems. The approach employs the multiscale finite-volume (MSFV) formulation to accurately and efficiently solve the highly detailed flow problem. The MSFV method couples a global coarse-scale solution with local fine-scale reconstruction operators, hence yielding model responses that are quite accurate at both scales. The MSADJ method is equally efficient in computing the gradient of the objective function with respect to model parameters. Several examples demonstrate that the approach is accurate and computationally efficient. The accuracy of our multiscale method for inverse problems is twofold: the sensitivity coefficients computed by this approach are more accurate than the traditional finite-difference-based numerical method for computing derivatives, and the calibrated models after history matching honor the available dynamic data on the fine scale. In other words, the multiscale based adjoint scheme can be used to history match fine-scale models quite effectively. 相似文献
7.
H. F. P. van den Boogaard M. J. J. Hoogkamer A. W. Heemink 《Stochastic Environmental Research and Risk Assessment (SERRA)》1993,7(2):109-130
For the simulation of the transport of dissolved matter particle models can be used. In this paper a technique is developed for the identification of uncertain parameters in these models. This model calibration is formulated as an optimization problem and is solved with a gradient based algorithm. Here adjoint particle tracks are used for the calculation of the gradient of the cost function. The performance of the calibration method is illustrated by simulations and an application to a river Rhine water quality calamity in November 1986. 相似文献
8.
H. F. P. van den Boogaard M. J. J. Hoogkamer A. W. Heemink 《Stochastic Hydrology and Hydraulics》1993,7(2):109-130
For the simulation of the transport of dissolved matter particle models can be used. In this paper a technique is developed for the identification of uncertain parameters in these models. This model calibration is formulated as an optimization problem and is solved with a gradient based algorithm. Here adjoint particle tracks are used for the calculation of the gradient of the cost function. The performance of the calibration method is illustrated by simulations and an application to a river Rhine water quality calamity in November 1986. 相似文献
9.
A new data assimilation method called the explicit four-dimensional variational (4DVAR) method is proposed. In this method, the singular value decomposition (SVD) is used to construct the orthogonal basis vectors from a forecast ensemble in a 4D space. The basis vectors represent not only the spatial structure of the analysis variables but also the temporal evolution. After the analysis variables are ex-pressed by a truncated expansion of the basis vectors in the 4D space, the control variables in the cost function appear explicitly, so that the adjoint model, which is used to derive the gradient of cost func-tion with respect to the control variables, is no longer needed. The new technique significantly simpli-fies the data assimilation process. The advantage of the proposed method is demonstrated by several experiments using a shallow water numerical model and the results are compared with those of the conventional 4DVAR. It is shown that when the observation points are very dense, the conventional 4DVAR is better than the proposed method. However, when the observation points are sparse, the proposed method performs better. The sensitivity of the proposed method with respect to errors in the observations and the numerical model is lower than that of the conventional method. 相似文献
10.
Djuro Radinović 《Pure and Applied Geophysics》1972,93(1):159-176
Summary A numerical model for the quantitative precipitation forecasting has been formulated. In this model precipitation is computed as a function of the vertical velocity and humidity distribution in the atmosphere. The orographic influence on the vertical velocity was taken into consideration. Further, the relation between vertical velocity and static stability of the atmosphere has been considered and, as an important factor in the condensation process, was introduced into the equation of the model. This numerical model for the precipitation forecasting has been applied in the North Adriactic Sea region, which is characterized by a strong vertical gradient of the specific humidity and pronounced orographic influence. The results achieved show that this model could successfully be used as an objective method in the routine forecasting of the amount of precipitation. 相似文献
11.
In this paper, the four-dimensional variational data assimilation technique (4D-VAR) is presented as a tool to forecast floods. Our study is limited to purely hydrological flows and supposes that the weather, here a big rain, has been already forecasted by meteorological services. The technique consists in minimizing, in the sense of Lagrange, the cost function: a measure of the difference between calculated data and available observations, here the water level. This is done under constraints that are the equations of the physical model. In our case, we modified the shallow-water equations to include a simplified sediment transport model. The steepest descent algorithm is then used to find the minimum. This is made possible because we can compute analytically the gradient of the cost function by using the adjoint equations of the model. As an application of the 4D-VAR technique, the overflowing of the Chicoutimi River at the Chute-Garneau dam, during the 1996 flood, is investigated. It is found that the 4D-VAR method reduces the error in the water height forecast even when the erosion model is not activated. In terms of Lyapunov exponents, we estimate the predictability horizon of such an event to be about half-an-hour after a big rain. However, this limit of predictability can be increased by using more observations or by using a finer computational grid. 相似文献
12.
地下地层普遍存在各向异性,忽略介质各向异性会导致速度估计不准确,成像精度下降.基于二阶声波方程的最小二乘逆时偏移忽略了介质各向异性及密度变化的影响,致使模拟地震数据与实际观测数据不匹配,影响收敛速度和反演成像质量.VTI介质一阶速度-应力方程能较好适应各向异性变密度情况,为此,本文首先从VTI介质一阶速度-应力方程出发,进行波动方程线性化;其次推导了相应的扰动方程和伴随方程,并通过伴随状态法得到梯度更新公式;最终形成基于一阶方程的LSRTM算法理论及实现流程.在实现算法的基础上,通过数值试算及成像结果对比,验证了本文算法在处理变密度和VTI介质时的有效性和优越性.偏移速度以及各向异性Thomsen参数误差的敏感性测试及误差收敛曲线对比结果进一步表明:速度及Thomsen参数对成像结果存在明显影响,其中速度敏感性最强,参数epsilon次之,参数delta的敏感性最弱. 相似文献
13.
利用伴随算子L*,直接的偏移方法通常导致一个低分辨率或模糊的地震成像.线性化偏移反演方法需求解一个最小二乘问题.但直接的最小二乘方法的数值不稳定,为目视解译带来困难.本文建立约束正则化数学模型,研究了地震偏移反演成像问题的迭代正则化求解方法.首先对最小二乘问题施加正则化约束,接着利用梯度迭代法求解反演成像问题,特别是提出了共轭梯度方法的混合实现技巧.为了表征该方法的可实际利用性,分别对一维,二维和三维地震模型进行了数值模拟.结果表明该正则偏移反演成像方法是有效的,对于实际的地震成像问题有着良好的应用前景. 相似文献
14.
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. 相似文献
15.
The estimation of a velocity model from seismic data is a crucial step for obtaining a high‐quality image of the subsurface. Velocity estimation is usually formulated as an optimization problem where an objective function measures the mismatch between synthetic and recorded wavefields and its gradient is used to update the model. The objective function can be defined in the data‐space (as in full‐waveform inversion) or in the image space (as in migration velocity analysis). In general, the latter leads to smooth objective functions, which are monomodal in a wider basin about the global minimum compared to the objective functions defined in the data‐space. Nonetheless, migration velocity analysis requires construction of common‐image gathers at fixed spatial locations and subsampling of the image in order to assess the consistency between the trial velocity model and the observed data. We present an objective function that extracts the velocity error information directly in the image domain without analysing the information in common‐image gathers. In order to include the full complexity of the wavefield in the velocity estimation algorithm, we consider a two‐way (as opposed to one‐way) wave operator, we do not linearize the imaging operator with respect to the model parameters (as in linearized wave‐equation migration velocity analysis) and compute the gradient of the objective function using the adjoint‐state method. We illustrate our methodology with a few synthetic examples and test it on a real 2D marine streamer data set. 相似文献
16.
Problems of the variational data assimilation for the primitive equation ocean model constructed at the Institute of Numerical
Mathematics, Russian Academy of Sciences are considered. The model has a flexible computational structure and consists of
two parts: a forward prognostic model, and its adjoint analog. The numerical algorithm for the forward and adjoint models
is constructed based on the method of multicomponent splitting. The method includes splitting with respect to physical processes
and space coordinates. Numerical experiments are performed with the use of the Indian Ocean and the World Ocean as examples.
These numerical examples support the theoretical conclusions and demonstrate the rationality of the approach using an ocean
dynamics model with an observed data assimilation procedure. 相似文献
17.
This paper describes least‐squares reverse‐time migration. The method provides the exact adjoint operator pair for solving the linear inverse problem, thereby enhancing the convergence of gradient‐based iterative linear inversion methods. In this formulation, modified source wavelets are used to correct the source signature imprint in the predicted data. Moreover, a roughness constraint is applied to stabilise the inversion and reduce high‐wavenumber artefacts. It is also shown that least‐squares migration implicitly applies a deconvolution imaging condition. Three numerical experiments illustrate that this method is able to produce seismic reflectivity images with higher resolution, more accurate amplitudes, and fewer artefacts than conventional reverse‐time migration. The methodology is currently feasible in 2‐D and can naturally be extended to 3‐D when computational resources become more powerful. 相似文献
18.
本文讨论了“虚点”和“虚微商”概念带来的矛盾和困难后,摒弃了电导率突变界面的模型,改用电导率渐变的模型去研究三维电磁感应的近似计算方法。在基本方程中考虑了电导率梯度项▽σ, ▽2B+1/σ（▽σ）×（▽×B）=i（4πσω）B. 文章的主要内容是给出有限差分法求解三维电磁感应问题的一般方程组。同时也作了一个简单的实例计算,以检验方程组运算的可行性。 相似文献
19.
Numerical implementation of a backward probabilistic model of ground water contamination 总被引：4，自引：0，他引：4
Backward location and travel time probabilities can be used to characterize known and unknown sources or prior positions of ground water contamination. Backward location probability describes the position of the observed contamination at some time in the past; backward travel time probability describes the amount of time prior to observation that the contamination was released from its source or was at a particular upgradient location. The governing equation for backward probabilities is the adjoint of the governing equation for contaminant transport, but with new load terms. Numerical codes that have been written to solve the forward equations of contaminant transport, e.g., the advection-dispersion equation, can also be used to solve the adjoint equation for location and travel time probabilities; however, the interpretation of the results is different and some new approximations must be made for the load terms. We present the governing equations for backward location and travel time probabilities, and provide appropriate numerical approximations for these load terms using the cell-centered finite difference method, one of the most popular numerical methods in ground water hydrology. We discuss some additional numerical considerations for the backward model including boundary conditions, reversal of the flow field, and interpretation of the results. We illustrate the implementation of the backward probability model using hypothetical examples in one- and two-dimensional domains. We also present a three-dimensional application of a pump-and-treat remediation capture zone delineation at the Massachusetts Military Reservation. The illustrations are performed using MODFLOW-96 for flow simulations and MT3DMS for transport simulations. 相似文献
20.
One of the problems in signal processing is estimating the impulse response function of an unknown system. The well-known Wiener filter theory has been a powerful method in attacking this problem. In comparison, the use of stochastic approximation method as an adaptive signal processor is relatively new. This adaptive scheme can often be described by a recursive equation in which the estimated impulse response parameters are adjusted according to the gradient of a predetermined error function. This paper illustrates by means of simple examples the application of stochastic approximation method as a single-channel adaptive processor. Under some conditions the expected value of its weight sequence converges to the corresponding Wiener optimum filter when the least-mean-square error criterion is used. 相似文献