Determination of the regularization level of truncated singular-value decomposition inversion: The case of 1D inversion of MT data

The total mean‐square error (MSE) of the estimated model, defined as the sum of the standard model variance and the bias variance, is used to define the truncation level of the singular‐value decomposition to give a reasonable balance between model resolution and model variance. This balance is determined largely by the data and no further assumptions are necessary except that the bias terms are estimated sufficiently well. This principle has been tested on the 1D magnetotelluric inverse problem with special emphasis on high‐frequency radio magnetotelluric (RMT) data. Simulations clearly demonstrate that the method provides a good balance between resolution and variance. Starting from a homogeneous half‐space, the best solution is sought for a fixed set of singular values. The model variance is estimated from the sum of the inverse eigenvalues squared, up to a certain threshold, and the bias variance is estimated from the model projections on the remaining eigenvectors. By varying the threshold, the minimum of the MSE is found for an increasing number of fixed singular values until the number of active singular values becomes greater than or equal to the estimated number. As a side‐effect, the depth of penetration of a given set of measurements can be estimated very efficiently by simply noting at which depth the final model deviates little from the starting homogeneous half‐space model. A suite of synthetic data is inverted and an example of inversion of one site is shown to illustrate how the truncation is carried out as the non‐linear inversion process proceeds. A field example with a profile across a plume of contaminated groundwater in the Netherlands shows good agreement with the electrical resistivity obtained in a nearby borehole.     

双感应测井资料的快速近似迭代反演

本文给出一种双感应资料快速近似迭代反演技术. 首先建立Fréchet导数的快速算法,保证在反演过程中能够同时获得测井响应相对于地层电阻率和层界面的偏导数,并给出用规范化处理与奇异值分解技术进行迭代反演的具体过程. 为了对理论模拟和井场实际资料进行反演,利用综合分层技术从双感应曲线中提取层界面初始位置和地层电阻率初值,通过单独迭代反演中感应资料,修改层界面和地层电阻率实现中感应资料的最佳拟合,得到探测深度相对较浅的地层电阻率,然后固定层界面位置,再迭代反演深感应资料,得到另一组探测深度相对较深的地层电阻率. 理论和实际资料处理结果证明,两个不同探测深度的电阻率反演结果的相对大小能够准确地反映地层真实的侵入特征.此外,由于深感应仪器具有较深的探测深度,不论在高侵或低侵地层上,深感应反演结果与地层原状电阻率的差异大大小于视电阻率的差异,所以利用反演结果也能得到更好的地层原状电阻率的估计值.     

Resolution studies for Magnetic Resonance Sounding (MRS) using the singular value decomposition

We present a new approach to analyse the subsurface water content distribution obtained by inversion of MRS data in terms of resolution and penetration depth. It is based on a singular value decomposition (SVD) of the MRS forward operator to derive the model resolution matrix including regularisation parameters, i.e. including noise conditions. The approach takes loop size, subsurface resistivity distribution and noise conditions as input parameters affecting MRS into account and allows an assessment on resolution and penetration.The application of the new approach shows that the loop diameter must be carefully chosen depending on the investigation site to obtain optimal resolution and penetration. Using the introduced resolution measures the quality and reliability of the estimated model can be assessed.     

从瞬变电磁响应中提取IP信息的研究(英文)

在对浙江省某铜矿进行瞬变电磁勘查时,由于感应激发极化效应的影响,造成瞬变电磁晚期测道的数据发生倒转。采用常规的瞬变电磁数据处理方法难以处理,造成晚期测道数据不可用,影响TEM的探测深度及精度。针对这个情况,采用Cole.Cole模型分析了均匀半空问模型中直流电阻率、充电率、时间常数以及频率相关系数对磁性源瞬变电磁响应的影响规律。利用奇异值分解法(The Singular Value Decomposition,简称SVD)对实测TEM数据进行分析及反演,并且从瞬变电磁响应数据中分离出勘探区瞬变电磁测量数据Cole—Cole模型的各参数,将分离出来的参数用于探测结果的辅助解释。经过分析得出充电率和频率相关系数对瞬变电磁响应的影响较大,而直流电阻率和时间常数对其影响较小的结论。通过常规方法和奇异值分解法对实测数据分别进行处理,发现后者视电阻率断面图的异常更加突出,从而较准确的圈定了铜矿体地范围,此结论得到_『钻孔的验证,与实际地质情况吻合较好。     

时间域航空电磁数据的反演

本文用广义逆矩阵理论讨论了时间域航空电磁数据的反演方法.以水平二层大地和球体模型为例进行了计算,结果表明这种方法对时间域电磁数据的反演是行之有效的.对于理论数据,一般仅需迭代数次即可稳定地收敛到真值.通过奇异值分析,可以确定一个模型中的相对重要参数和无关紧要参数;对于求解某一特定参数,可确定哪些数据起决定性的作用.由奇异值分解而得出的信息密度矩阵、模型分辨矩阵,分别给出了模型响应拟合数据和模型参数分辨率的度量.这些信息对于时间域航空电磁系统的设计、野外测量和资料解释都具有重要的参考价值.最后给出了实例.     

1D and 2D Cole-Cole-inversion of time-domain induced-polarization data

A new method for the 2D inversion of induced polarization (IP) data in the time domain has been developed. The entire IP transients were observed and inverted into 2D Cole-Cole earth models, including resistivity, chargeability, relaxation time and the frequency constant. Firstly, a modified 1D time-domain electromagnetic algorithm was used to calculate the response of a layered polarizable ground. The transient signals were then inverted using the Marquardt method to derive the Cole-Cole parameters of each layer. However, model calculations showed that the EM effects could be neglected for the time range (>1 ms) and for the transmitter–receiver distances (<50 m) used in this study. Therefore, the induction effects were not considered for the solution of the 2D inverse problem and a DC solution was applied. An approximative forward algorithm was introduced in order to calculate the IP transients directly in the time domain and in order to speed up the inverse procedure. The approximation is highly accurate, and this is demonstrated by comparing the approximations with their exact solutions up to 3D. The inverse algorithm presented consists of two steps. The transient voltages of an array data set were inverted separately into a two-dimensional resistivity model for each time channel. The time-dependent resistivity of each cell was then interpreted as the response of a homogeneous half-space. In the 2D inversion algorithm, a 3D DC algorithm was used as a forward operator. The method only requires a standard 2D DC inversion and a homogenous half-space Cole-Cole inversion. The developed algorithm has been successfully applied to synthetic data sets and to a field data set obtained from a waste site situated close to Düren in Germany.     

Inversion for elliptically anisotropic velocity using VSP reflection traveltimes

This paper presents a traveltime inversion approach, using the reflection traveltimes from offset VSP data, to reconstruct the horizontal and vertical velocities for stratified anisotropic media. The inverse problem is reduced to a set of linear equations, and solved by the singular value decomposition (SVD) technique. The validity of this inversion scheme is verified using two sets of synthetic data simulated using a finite‐difference method, one for an isotropic model and the other for an elliptically anisotropic model. The inversion result demonstrates that our anisotropic velocity inversion scheme may be applied to both isotropic and anisotropic media. The method is finally applied to a real offset VSP data set, acquired in an oilfield in northwestern China.     

Singular value decomposition as a denoising tool for airborne time domain electromagnetic data

Airborne time domain electromagnetic (TDEM) surveys are increasingly carried out in anthropized areas as part of environmental studies. In such areas, noise arises mainly from either natural sources, such as spherics, or cultural sources, such as couplings with man-made installations. This results in various distortions on the measured decays, which make the EM noise spectrum complex and may lead to erroneous inversion and subsequent misinterpretations. Thresholding and stacking standard techniques, commonly used to filter TDEM data, are less efficient in such environment, requiring a time-consuming and subjective manual editing. The aim of this study was therefore to propose an alternative fast and efficient user-assisted filtering approach. This was achieved using the singular value decomposition (SVD). The SVD method uses the principal component analysis to extract into components the dominant shapes from a series of raw input curves. EM decays can then be reconstructed with particular components only. To do so, we had to adapt and implement the SVD, firstly, to separate clearly and so identify easily the components containing the geological signal, and then to denoise properly TDEM data.The reconstructed decays were used to detect noisy gates on their corresponding measured decays. This denoising step allowed rejecting efficiently mainly spikes and oscillations. Then, we focused on couplings with man-made installations, which may result in artifacts on the inverted models. An analysis of the map of weights of the selected “noisy components” highlighted high correlations with man-made installations localized by the flight video. We had therefore a tool to cull most likely decays biased by capacitive coupling noises. Finally, rejection of decays affected by galvanic coupling noises was also possible locating them through the analysis of specific SVD components. This SVD procedure was applied on airborne TDEM data surveyed by SkyTEM Aps. over an anthropized area, on behalf of the French geological survey (BRGM), near Courtenay in Région Centre, France. The established denoising procedure provides accurate denoising tools and makes, at least, the manual cleaning less time consuming and less subjective.     

An efficient non-linear least-squares 1D inversion scheme for resistivity and IP sounding data

Non-linear least-squares inversion operates iteratively by updating the model parameters in each step by a correction vector which is the solution of a set of normal equations. Inversion of geoelectrical data is an ill-posed problem. This and the ensuing suboptimality restrict the initial model to being in the near vicinity of the true model. The problem may be reduced by introducing damping into the system of equations. It is shown that an appropriate choice of the damping parameter obtained adaptively and the use of a conjugate-gradient algorithm to solve the normal equations make the 1D inversion scheme efficient and robust. The scheme uses an optimal damping parameter that is dependent on the noise in the data, in each iterative step. The changes in the damping and relative residual error with iteration number are illustrated. A comparison of its efficacy over the conventional Marquardt and simulated annealing methods, tested on Inman's model, is made. Inversion of induced polarization (IP) sounding is obtained by inverting twice (true and modified) DC apparent resistivity data. The inversion of IP data presented here is generic and can be applied to any of the IP observables, such as chargeability, frequency effect, phase, etc., as long as these observables are explicitly related to the DC apparent resistivity. The scheme is used successfully in inverting noise-free and noisy synthetic data and field data taken from the published literature.     

A numerical inversion scheme for geoelectrical soundings

A simple numerical inversion scheme for estimatingn-layer model parameters from observed geoelectrical resistivity data can be used in either the space or wavenumber domain. The technique utilizes Madden's Transmission Line Analogy to compute the resistivity transforms and linear filter theory to accomplish the excursions between the space and wavenumber domains. The inversion is effected by an iterative refinement scheme employing the stochastic inverse which is approximate to the generalized inverse. No singular decomposition analysis is required and the scheme is stable under ill conditions. The inversion scheme not only gives the desired estimates; it exposes redundant parameters and irrelevant data and is easily programmed on a desk-top mini computer. Examples of inverse modeling with hypothetical and field data are discussed.     

STATISTICAL EVALUATION OF MT AND AMT METHODS APPLIED TO A BASALT-COVERED AREA IN SOUTHEASTERN ANATOLIA,TURKEY*

The efficacy of the magnetotelluric and audiomagnetotelluric (MT/AMT) methods for detailing the structure of a hypothetical geological section is investigated by using the singular value decomposition (SVD) technique. The section is representative of southeastern Turkey, which is mostly covered by basalt and is a prime area for oil exploration. One of the geological units, the Germav shale at a depth of 600 m, is a problem layer for electromagnetic surveys because of its very low resistivity (on average 3 Ωm) and highly variable thickness across the area (200–900 m). In the MT frequency range (0.0004–40 Hz) its total conductance—or, since its resistivity is known from resistivity log information, its thickness—is the best resolved model parameter. The total depth to the Germav shale and the resistivity of the Cambrian/Precambrian basement are the marginally resolved parameters. In the AMT frequency range (4–10000 Hz) the resistivity of the surface basalt layer strongly affects the resolution of the other, less important, model parameters which are the total depth to the Germav shale and the total conductance of the Germav shale. The errors in the measurements determine the number of model parameters resolvable, and are also important for interpretation of the geological model parameters to within a desired accuracy. It is shown that statistical evaluation of the MT and/or AMT interpretations by using an SVD factorization of the sensitivity matrix can be helpful to define the importance of some particular stage of the interpretation, and also provides a priori knowledge to plan a proposed survey. Arrangements of MT and AMT observations, together with some Schlumberger resistivity soundings, on a large grid will certainly provide three-dimensional detailed information of the deep geoelectric structure of the area.     

基于非结构网格的电阻率三维带地形反演

地表起伏地形在野外矿产资源勘察中不可避免,其对直流电阻率法勘探影响巨大.近年来,电阻率三维正演取得诸多进展,特别是应用非结构网格我们能够进行任意复杂地形和几何模型的电阻率三维数值模拟,但面向实际应用的起伏地形下电阻率三维反演依然困难.本文基于非结构化四面体网格,并考虑到应用GPS/GNSS时,区域地球物理调查中可非规则布设测网的实际特点,实现了任意地形(平坦或起伏)条件下、任意布设的偶极-偶极视电阻率数据的不完全Gauss-Newton三维反演.合成数据的反演结果表明了方法的有效性,可应用于复杂野外环境下的三维电法勘探.     

Use of VFSA for resolution, sensitivity and uncertainty analysis in 1D DC resistivity and IP inversion

We present results from the resolution and sensitivity analysis of 1D DC resistivity and IP sounding data using a non-linear inversion. The inversion scheme uses a theoretically correct Metropolis–Gibbs' sampling technique and an approximate method using numerous models sampled by a global optimization algorithm called very fast simulated annealing (VFSA). VFSA has recently been found to be computationally efficient in several geophysical parameter estimation problems. Unlike conventional simulated annealing (SA), in VFSA the perturbations are generated from the model parameters according to a Cauchy-like distribution whose shape changes with each iteration. This results in an algorithm that converges much faster than a standard SA. In the course of finding the optimal solution, VFSA samples several models from the search space. All these models can be used to obtain estimates of uncertainty in the derived solution. This method makes no assumptions about the shape of an a posteriori probability density function in the model space. Here, we carry out a VFSA-based sensitivity analysis with several synthetic and field sounding data sets for resistivity and IP. The resolution capability of the VFSA algorithm as seen from the sensitivity analysis is satisfactory. The interpretation of VES and IP sounding data by VFSA, incorporating resolution, sensitivity and uncertainty of layer parameters, would generally be more useful than the conventional best-fit techniques.     

利用Cole-Cole模型组合得到SIP真参数的联合频谱最优化反演

利用Cole-Cole模型组合和稀释系数理论，可以描述测量得到的视复电阻率频谱与地下多个电性体SIP真参数之间的正演关系。本利用此正演关系进行反演试算，并比较了几种Cole-Cole模型反演方案的效果；提出固定极化目标体和围岩体的极化率同时反演其它各SIP真参数的反演方案。结果表明在固定极化率为真值时，利用此反演方案可以稳定、准确、快速地得出地下电性体SIP真参数。     

飞行高度同时反演的固定翼航空瞬变电磁-维反演

航空电磁测量记录中,不仅感生电动势测量数据有观测误差,而且高度计测量数据也有误差,直接进行常规反演往往导致反演结果不可靠,研究飞行高度数据有误差下的反演算法具有实际意义.本文以层状模型的固定翼时间域航空电磁多分量理论响应数据为例,提出了两种针对飞行高度计记录数据有误差时的正则化反演算法,一个是自适应正则化反演方法,另一...     

Solutions of the inherent problem of the equivalence in direct current resistivity and electromagnetic methods through global optimization and joint inversion by successive refinement of model space

The problem of equivalence in direct current (DC) resistivity and electromagnetic methods for a thin resistive and conducting layer is well‐known. Attempts have been made in the past to resolve this problem through joint inversion. However, equivalence still remains an unresolved problem. In the present study, an effort is made to reduce non‐uniqueness due to equivalence using global optimization and joint inversion by successive refinement of the model space. A number of solutions derived for DC resistivity data using very fast simulated annealing global inversion that fits the observations equally well, follow the equivalence principle and show a definite trend. For a thin conductive layer, the quotient between resistivity and thickness is constant, while for a resistive one, the product between these magnitudes is constant. Three approaches to obtain very fast simulated annealing solutions are tested. In the first one, layer resistivities and thicknesses are optimized in a linear domain. In the second, layer resistivities are optimized in the logarithmic domain and thicknesses in the linear domain. Lastly, both layer resistivities and thicknesses are optimized in the logarithmic domain. Only model data from the mean models, corresponding to very fast simulated annealing solutions obtained for approach three, always fit the observations. The mean model defined by multiple very fast simulated annealing solutions shows extremely large uncertainty (almost 100%) in the final solution after inversion of individual DC resistivity or electromagnetic (EM) data sets. Uncertainty associated with the intermediate resistive and conducting layers after global optimization and joint inversion is still large. In order to reduce the large uncertainty associated with the intermediate layer, global optimization is performed over several iterations by reducing and redefining the search limits of model parameters according to the uncertainty in the solution. The new minimum and maximum limits are obtained from the uncertainty in the previous iteration. Though the misfit error reduces in the solution after successive refinement of the model space in individual inversion, it is observed that the mean model drifts away from the actual model. However, successive refinement of the model space using global optimization and joint inversion reduces uncertainty to a very low level in 4–5 iterations. This approach works very well in resolving the problem of equivalence for resistive as well as for conducting layers. The efficacy of the approach has been demonstrated using DC resistivity and EM data, however, it can be applied to any geophysical data to solve the inherent ambiguities in the interpretations.     

基于非结构双网格的2D RMT双参数同步反演研究

Radio-magnetotelluric(RMT)是以无线电发射机为信号源的一种地球物理勘探方法,近年来被广泛应用于数米至数十米内的近地表工程和环境地球物理勘探.目前,各类电磁资料的反演均是以寻求满足目标拟合差的地下介质电阻率分布为目的.然而,对于勘探频率为10~300kHz的RMT数据,由介电常数所引起的波动场在总场中的比例可达20%以上,在这种情况下,忽略介电常数,仅通过电阻率参数的反演来进行数据拟合势必降低反演资料解释的准确性.为解决这一问题,本文研究了基于电阻率-介电常数的双参数同步反演算法.构建了一个全新的双参数目标函数,并推导了双参数反演迭代方程组;通过灵敏度分析,研究了电阻率和介电常数对正演响应的影响,并据此提出相对电导率的概念,统一了反演参数的灵敏度;通过理论模型分析了参考频率、双参数正则化因子对反演结果的影响,并给出了一般性的参数优选方案.此外,为了能够灵活处理复杂地形,本文采用非结构的正反演双网格进行模型离散,并通过局部加密技术保证反演的速度和精度.最后,对一带地形的理论模型分别进行了单参数和双参数反演,结果表明单参数反演无法正确反映出地电信息,而双参数反演能够准确得到异常的分布,验证了本文所开发的双参数反演程序的有效性.     

Joint inversion of Rayleigh‐wave dispersion data and vertical electric sounding data: synthetic tests on characteristic sub‐surface models

In the traditional inversion of the Rayleigh dispersion curve, layer thickness, which is the second most sensitive parameter of modelling the Rayleigh dispersion curve, is usually assumed as correct and is used as fixed a priori information. Because the knowledge of the layer thickness is typically not precise, the use of such a priori information may result in the traditional Rayleigh dispersion curve inversions getting trapped in some local minima and may show results that are far from the real solution. In this study, we try to avoid this issue by using a joint inversion of the Rayleigh dispersion curve data with vertical electric sounding data, where we use the common‐layer thickness to couple the two methods. The key idea of the proposed joint inversion scheme is to combine methods in one joint Jacobian matrix and to invert for layer S‐wave velocity, resistivity, and layer thickness as an additional parameter, in contrast with a traditional Rayleigh dispersion curve inversion. The proposed joint inversion approach is tested with noise‐free and Gaussian noise data on six characteristic, synthetic sub‐surface models: a model with a typical dispersion; a low‐velocity, half‐space model; a model with particularly stiff and soft layers, respectively; and a model reproduced from the stiff and soft layers for different layer‐resistivity propagation. In the joint inversion process, the non‐linear damped least squares method is used together with the singular value decomposition approach to find a proper damping value for each iteration. The proposed joint inversion scheme tests many damping values, and it chooses the one that best approximates the observed data in the current iteration. The quality of the joint inversion is checked with the relative distance measure. In addition, a sensitivity analysis is performed for the typical dispersive sub‐surface model to illustrate the benefits of the proposed joint scheme. The results of synthetic models revealed that the combination of the Rayleigh dispersion curve and vertical electric sounding methods in a joint scheme allows to provide reliable sub‐surface models even in complex and challenging situations and without using any a priori information.     

Discrete cosine transform for parameter space reduction in Bayesian electrical resistivity tomography

Electrical resistivity tomography is a non-linear and ill-posed geophysical inverse problem that is usually solved through gradient-descent methods. This strategy is computationally fast and easy to implement but impedes accurate uncertainty appraisals. We present a probabilistic approach to two-dimensional electrical resistivity tomography in which a Markov chain Monte Carlo algorithm is used to numerically evaluate the posterior probability density function that fully quantifies the uncertainty affecting the recovered solution. The main drawback of Markov chain Monte Carlo approaches is related to the considerable number of sampled models needed to achieve accurate posterior assessments in high-dimensional parameter spaces. Therefore, to reduce the computational burden of the inversion process, we employ the differential evolution Markov chain, a hybrid method between non-linear optimization and Markov chain Monte Carlo sampling, which exploits multiple and interactive chains to speed up the probabilistic sampling. Moreover, the discrete cosine transform reparameterization is employed to reduce the dimensionality of the parameter space removing the high-frequency components of the resistivity model which are not sensitive to data. In this framework, the unknown parameters become the series of coefficients associated with the retained discrete cosine transform basis functions. First, synthetic data inversions are used to validate the proposed method and to demonstrate the benefits provided by the discrete cosine transform compression. To this end, we compare the outcomes of the implemented approach with those provided by a differential evolution Markov chain algorithm running in the full, un-reduced model space. Then, we apply the method to invert field data acquired along a river embankment. The results yielded by the implemented approach are also benchmarked against a standard local inversion algorithm. The proposed Bayesian inversion provides posterior mean models in agreement with the predictions achieved by the gradient-based inversion, but it also provides model uncertainties, which can be used for penetration depth and resolution limit identification.     

横向各向同性介质紧致交错网格有限差分波场模拟(英文)

针对有限差分数值模拟的频散问题,本文将交错网格技术和紧致差分格式相结合,推导了横向各向同性介质一阶速度一应力波动方程的紧致交错网格差分格式;对比分析了紧致交错网格差分格式、交错网格差分格式以及紧致差分格式的截断误差主项,并利用Fourier误差分析方法分析了上述三种差分格式的近似精度;在此基础上,分别采用上述三种差分格式进行了波场数值模拟。结果表明,当差分方程阶数相同时,紧致交错网格差分格式截断误差最小,数值频散最弱,差分精度最高,证实了该方法的有效性。