共查询到18条相似文献，搜索用时 305 毫秒
1.
为改善反演效果,获得全局最小解,减小反演结果对初始模型的依赖程度,本文将变维数贝叶斯反演应用于时间域航空电磁数据反演。变维数贝叶斯反演方法在贝叶斯方法基础上利用可逆跳跃马尔科夫链蒙特卡洛方法(RJMCMC)实现反演模型层数的变化。这种方法根据建议分布并利用蒙特卡洛方法充分搜索模型空间进行随机采样。只统计同时满足数据拟合要求和接受概率的候选模型,受初始模型影响小,收敛稳定,反演结果可靠,最终可获得反演模型的概率分布和不确定度信息。由于实际飞行中发射源高度很难精确测量,因此本文在反演过程中将发射源高度分为不变和发射源高度变化两种情况。同时本文在电阻率先验概率密度函数中引入加权系数以调整对反演模型的约束强度,可有效地解决电阻率断面中间层反演效果不理想的问题。本文通过反演中心回线装置的H型和分离装置K型、HK型断面添加高斯噪声后的仿真数据以及实测数据,验证了变维数贝叶斯方法反演时间域航空电磁数据的有效性。 相似文献
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针对常规大地电磁（Magnetotelluric，MT）反演方法对电阻率异常体边界不太敏感的问题，本文尝试基于贝叶斯理论开展二维大地电磁电阻率尖锐边界反演研究.在反演中，模型参数由边界位置及内部电阻率组成，通过贝叶斯理论将模型参数与数据相联系，采用Markov Chain Monte Carlo（MCMC）的Metropolis-Hastings（MH）方法对后验概率密度函数（Posteriori Probability Density，PDD）进行采样.采样过程中无罚值函数约束，完全以数据自身所包含的信息对模型进行约束，同时与有限约束进行比较，并考虑不同起始采样点对结果的影响.以接受率为参考，用模型算例说明MH方法中建议分布函数选择的重要性.当模型参数间相关性较弱时，使用边缘概率分布对采样结果进行分析.该方法能给出模型参数的分布范围，并给出该模型参数范围对应的数据范围.通过与已知模型的对比及数据拟合情况分析检验了该反演方法的有效性.该方法有助于提高大地电磁尖锐边界反演的分辨能力. 相似文献
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传统的一维反演技术已经被广泛应用于航空电磁数据解释中.然而,利用单点水平层状介质模型模拟地下复杂地电结构有时会遇到困难.突出表现在反演参数的横向不连续性,即使相邻测点的反演结果也会出现突变.本文针对航空电磁直升机吊舱系统可进行密集采样,相邻测点地下电性结构应具有某种程度连续性的特点,研究航空电磁数据横向约束反演理论,并提出参数加权约束方法.首先阐述频率域航空电磁正演和加权横向约束反演理论,着重介绍这种拟二维反演方法的基本原理和实施步骤,以及将该方法成功应用于频率域航空电磁数据反演处理的方法技术.最后,通过对理论和实测数据反演处理,并与传统的一维反演结果进行对比,验证加权横向约束反演方法的有效性. 相似文献
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《地球物理学进展》2020,(4)
瑞利波具有强能量和频散特性,面波勘探采集瑞利面波数据分析反演得到横波速度结构,在浅地表勘探领域得到了广泛的应用,根据面波频散反演速度结构是面波勘探的重要环节之一.面波频散与地下介质的弹性参数是非线性关系,全局优化方法是解决非线性反问题的有效办法,贝叶斯方法是一种基于统计的全局优化方法.贝叶斯公式反映了先验信息和条件概率乘积与后验概率之间的正比关系,利用马尔科夫链蒙特卡洛采样方法可以获得后验分布的采样.与其他方法相比,该方法不是给出一个模型最优解,而是统计出模型参数的平均值和方差,平均值即是反演的模型解,方差能对该反演结果的不确定性做出评价.本文采用贝叶斯方法对模拟和实测瑞利面波数据频散曲线进行反演,结果显示,该方法能获得比较精确的横波速度和厚度参数,验证了本文方法可行.在高丽营地区采集了多个单炮面波数据,对数据进行频散谱处理拾取频散曲线,通过贝叶斯反演方法获得了该测线二维横波速度剖面图,有助于划分和解释该测区地层及断层地质构造. 相似文献
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《地球物理学进展》2020,(2)
时间域航空电磁晚期道数据中常出现符号反转现象,该现象被证明是由激电效应引起.鉴于利用传统实电阻率模型的成像和反演技术处理该类数据无法得到正确的反演结果,本文提出基于Occam理论的反演方法,对层状模型电阻率和充电率参数进行同时反演.本文首先通过正演模拟极化介质中电流密度的分布情况,对时间域航空电磁信号出现多次符号反转现象做出合理解释;然后通过链式法则和波形褶积技术计算Cole-Cole模型参数灵敏度,进而探讨不同Cole-Cole模型参数灵敏度差异及其对反演结果的影响.为了提高多参数反演的稳定性和准确性,在反演过程中对参数采取上下限约束,最后对B_z、dB_z/dt响应单独反演结果和联合反演结果进行对比和分析,发现联合反演可以有效地降低反演结果的多解性. 相似文献
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基于主成分的时间域航空电磁数据神经网络反演仿真研究(英文) 总被引：5，自引：0，他引：5
传统上,时间域航空电磁数据通过拟合迭代反演计算得到大地模型,然而,由于航空电磁数据道间的较强相关性,导致病态反演,并引起超定问题;同时电磁数据的相关性使其与模型参数的映射关系复杂,增加了反演的复杂度。采用主成分分析法将航空电磁数据变换为正交的较少数量的主成分,不仅降低了数据道间的相关性,减小了数据量,同时压制了数据的不相关噪声。本文利用人工神经网络(ANN)逼近主成分与大地模型参数间的映射关系,避免了传统反演算法中雅克比矩阵的复杂计算。层状模型的主成分神经网络与数据神经网络的反演结果对比显示,主成分神经网络反演方法网络结构简单,训练步数少,反演结果好,特别是对于含噪数据。准二维模型的主成分ANN、数据ANN以及Zhody方法的反演结果显示了主成分神经网络具有更接近真实模型的反演效果,进一步证明了主成分神经网络反演方法适合海量航空电磁探测数据反演。 相似文献
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由于航空电磁具有海量数据,因此快速有效的成像和反演手段至关重要.本文针对层状介质模型推导与实现了广义模型约束条件下时间域航空电磁一维反演.从正则化反演的目标函数出发,通过改变模型约束项构造Lp范数反演和聚焦反演,进而通过改变模型求解域构造出基于小波变换的稀疏约束反演.针对不同反演方法目标函数的构建方式,本文进一步从数学原理上分析不同反演方法的预期效果,并通过理论模型和实测数据进行验证.结果表明L0.8范数反演、聚焦反演和基于小波变换的稀疏约束反演可以得到更符合地下层状介质陡变界面的反演结果. 相似文献
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大地电磁的反演问题是非线性,如果采用线性反演方法容易陷入局部极小,使得反演结果非唯一性严重.本文将人工鱼群算法引入到地球物理反演之中,提出了非线性的大地电磁人工鱼群最优化反演.该方法不需要进行偏导数的求取,可以对反演的范围进行约束,以减小反演结果的非唯一性.同时我们对搜索步长进行了改进,给出适用于大地电磁反演的人工鱼群参数.大量的理论数据试算表明,人工鱼群反演算法能够较好地寻找到全局最优解.实测数据的处理结果表明,该方法可以用来处理实际资料,并且能够取得很好的应用效果. 相似文献
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To reduce the dependence of EM inversion on the choice of initial model and to obtain the global minimum, we apply transdimensional Bayesian inversion to time-domain airborne electromagnetic data. The transdimensional Bayesian inversion uses the Monte Carlo method to search the model space and yields models that simultaneously satisfy the acceptance probability and data fitting requirements. Finally, we obtain the probability distribution and uncertainty of the model parameters as well as the maximum probability. Because it is difficult to know the height of the transmitting source during flight, we consider a fixed and a variable flight height. Furthermore, we introduce weights into the prior probability density function of the resistivity and adjust the constraint strength in the inversion model by changing the weighing coefficients. This effectively solves the problem of unsatisfactory inversion results in the middle high-resistivity layer. We validate the proposed method by inverting synthetic data with 3% Gaussian noise and field survey data. 相似文献
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In order to interpret field data from small-loop electromagnetic (EM) instruments with fixed source–receiver separation, 1D inversion method is commonly used due to its efficiency with regard to computation costs. This application of 1D inversion is based on the assumption that small-offset broadband EM signals are insensitive to lateral resistivity variation. However, this assumption can be false when isolated conductive bodies such as man-made objects are embedded in the earth. Thus, we need to clarify the applicability of the 1D inversion method for small-loop EM data. In order to systematically analyze this conventional inversion approach, we developed a 2D EM inversion algorithm and verified this algorithm with a synthetic EM data set. 1D and 2D inversions were applied to synthetic and field EM data sets. The comparison of these inversion results shows that the resistivity distribution of the subsurface constructed by the 1D inversion approach can be distorted when the earth contains man-made objects, because they induce drastic variation of the resistivity distribution. By analyzing the integrated sensitivity of the small-loop EM method, we found that this pitfall of 1D inversion may be caused by the considerable sensitivity of the small-loop EM responses to lateral resistivity variation. However, the application of our 2D inversion algorithm to synthetic and field EM data sets demonstrate that the pitfall of 1D inversion due to man-made objects can be successfully alleviated. Thus, 2D EM inversion is strongly recommended for detecting conductive isolated bodies, such as man-made objects, whereas this approach may not always be essential for interpreting the EM field data. 相似文献
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为了克服时间域航空电磁数据单点反演结果中常见的电阻率或层厚度横向突变造成数据难以解释的问题，通过引入双向约束实现航空电磁拟三维空间约束反演.除考虑沿测线方向相邻测点之间的横向约束外，同时还考虑了垂直测线方向测点在空间上的相互约束.为此，首先设计拟三维模型中固定层厚和可变层厚两种空间约束反演方案，然后通过在目标函数中引入沿测线和垂直测线方向上的模型参数约束矩阵，并使用L-BFGS算法使目标函数最小化，获得最优拟三维模型空间反演解.基于理论模型和实测数据反演，对单点反演与两种空间约束反演方案的有效性进行比较，证明本文空间约束反演算法对于噪声的压制效果好，反演的界面连续光滑，同时内存需求和反演时间少，是一种快速有效的反演策略. 相似文献
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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
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We propose a Bayesian fusion approach to integrate multiple geophysical datasets with different coverage and sensitivity. The fusion strategy is based on the capability of various geophysical methods to provide enough resolution to identify either subsurface material parameters or subsurface structure, or both. We focus on electrical resistivity as the target material parameter and electrical resistivity tomography (ERT), electromagnetic induction (EMI), and ground penetrating radar (GPR) as the set of geophysical methods. However, extending the approach to different sets of geophysical parameters and methods is straightforward. Different geophysical datasets are entered into a trans-dimensional Markov chain Monte Carlo (McMC) search-based joint inversion algorithm. The trans-dimensional property of the McMC algorithm allows dynamic parameterisation of the model space, which in turn helps to avoid bias of the post-inversion results towards a particular model. Given that we are attempting to develop an approach that has practical potential, we discretize the subsurface into an array of one-dimensional earth-models. Accordingly, the ERT data that are collected by using two-dimensional acquisition geometry are re-casted to a set of equivalent vertical electric soundings. Different data are inverted either individually or jointly to estimate one-dimensional subsurface models at discrete locations. We use Shannon's information measure to quantify the information obtained from the inversion of different combinations of geophysical datasets. Information from multiple methods is brought together via introducing joint likelihood function and/or constraining the prior information. A Bayesian maximum entropy approach is used for spatial fusion of spatially dispersed estimated one-dimensional models and mapping of the target parameter. We illustrate the approach with a synthetic dataset and then apply it to a field dataset. We show that the proposed fusion strategy is successful not only in enhancing the subsurface information but also as a survey design tool to identify the appropriate combination of the geophysical tools and show whether application of an individual method for further investigation of a specific site is beneficial. 相似文献
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To improve the inversion accuracy of time-domain airborne electromagnetic data, we propose a parallel 3D inversion algorithm for airborne EM data based on the direct Gauss–Newton optimization. Forward modeling is performed in the frequency domain based on the scattered secondary electrical field. Then, the inverse Fourier transform and convolution of the transmitting waveform are used to calculate the EM responses and the sensitivity matrix in the time domain for arbitrary transmitting waves. To optimize the computational time and memory requirements, we use the EM “footprint” concept to reduce the model size and obtain the sparse sensitivity matrix. To improve the 3D inversion, we use the OpenMP library and parallel computing. We test the proposed 3D parallel inversion code using two synthetic datasets and a field dataset. The time-domain airborne EM inversion results suggest that the proposed algorithm is effective, efficient, and practical. 相似文献
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为了提高AVO(amplitude versus offset)反演结果的精度和横向连续性,本文提出了一种新的AVO反演约束方法,该方法结合贝叶斯原理和卡尔曼滤波算法实现了对反演参数纵向和横向的同时约束.文章首先结合反演参数的纵向贝叶斯先验概率约束和反演参数的横向连续性假设建立了与卡尔曼滤波算法对应的AVO反演系统的数学模型,然后将该数学模型代入卡尔曼滤波算法框架,利用卡尔曼滤波算法实现了双向约束AVO反演.二维模型测试和实际数据测试结果表明,相对于单纯的纵向贝叶斯先验概率约束,双向约束能更准确地刻画参数的横向变化,得到更准确、横向连续性更好的反演结果. 相似文献
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THE DISPERSION RELATION, OF EARTH''S ELECTROMAGNETIC RESPONSE FUNCTIONS AND THE JOINT INVERSION OF DATA 下载免费PDF全文
下载免费PDF全文 On the basis of the dispersion relations of MT field, the necessity and applied prospects of the joint inversions using a pair of MT response functions which are correlative with the dispersion relations, are infered. A filter coefficient algorithm is made, with which the corresponding impedance phase data can be estimated using a set of apparent resistivities. The tests for the observed MT data show that when comparing the impedance phase estimated using the dispersion relation with the ob served phase, it can be checked whether the dispersion relation between observed apparent resistivity and phase data is satisfied or not, and that the use of the phase data corrected using the dispersion relation in the joint inversion is advantageous to obtain more confident results. It is shown that joint inversions are more advantageous than single parameter inversions, and that in the most case the joint inversion using the apparent resistivities of impedance real and imaginary parts is more advantageous than the jointinversion using the normal apparent resistivity and impedance phase. The existence of the dipersion relations between the ratio apparent resistivity and corresponding impedance phase of the orthogonal electric and magnetic field horizontal Components in the frequency EM sounding with horizontal electric dipole(FEMS) are discussed, the better effect of the joint inversion using the pair of EM response functions is obtained. The problems on the one-dimensional joint inversion for the MT and FEMS apparent resistivities, for which the observed frequency bands partly overlape each other, are studied. It is shown that this joint inversion is applicable and effective:the joint inversions of the practical data for two kinds of EM methods at two sites give the results well corresponding to the drilling data. The simulated MT inversions for the data of two kinds of EM methods are made, and more confident results also are obtained. 相似文献