时间域航空电磁2.5维非线性共轭梯度反演

对于时间域航空电磁法二维和三维反演来说,最大的困难在于有效的算法和大的计算量需求.本文利用非线性共轭梯度法实现了时间域航空电磁法2.5维反演方法,着重解决了迭代反演过程中灵敏度矩阵计算、最佳迭代步长计算、初始模型选取等问题.在正演计算中,我们采用有限元法求解拉式傅氏域中的电磁场偏微分方程,再通过逆拉氏和逆傅氏变换高精度数值算法得到时间域电磁响应.在灵敏度矩阵计算中,采用了基于拉式傅氏双变换的伴随方程法,时间消耗只需计算两次正演,从而节约了大量计算时间.对于最佳步长计算,二次插值向后追踪法能够保证反演迭代的稳定性.设计两个理论模型,检验反演算法的有效性,并讨论了选择不同初始模型对反演结果的影响.模型算例表明:非线性共轭梯度方法应用于时间域航空电磁2.5维反演中稳定可靠,反演结果能够有效地反映地下真实电性结构.当选择的初始模型电阻率值与真实背景电阻率值接近时,能得到较好的反演结果,当初始模型电阻率远大于或远小于真实背景电阻率值时反演效果就会变差.     

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)

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。     

固定翼航空电磁系统的线圈姿态及吊舱摆动影响研究与校正

固定翼时间域航空电磁探测系统在实际飞行测量过程中,发射线圈、接收线圈姿态和吊舱摆动状态不断变化,在测量数据中引入如发射磁矩方向、接收分量方向以及系统收发距等参数的误差,影响数据反演成像效果.本文基于固定翼时间域航空电磁正演理论,利用姿态变换,引入发射线圈、接收线圈双旋转矩阵;根据发射、接收线圈相对位置的几何关系,求得摆动格林张量;推导了任意姿态角度以及任意摆动角度情况下的固定翼航空电磁响应三分量计算表达式.通过层状大地模型的仿真计算,分别研究了发射、接收线圈各姿态以及吊舱摆动状态对航空电磁响应的影响,得出发射线圈、接收线圈俯仰旋转和吊舱同向摆动对系统电磁响应影响最强;仿真分析了实际测量中,三种角度同时存在情况下,航空电磁响应的定量变化规律.在此基础上,讨论了响应系数与大地电导率的关系,同时给出基于响应系数的固定翼航空电磁系统线圈姿态和摆动状态校正方法,准二维层状大地模型反演结果表明,校正后数据的反演精度提高了33.1%.     

直升机航空瞬变电磁自适应正则化一维反演方法研究

本文以中心回线式直升机航空瞬变电磁法为例对时间域航空电磁资料的一维反演算法进行理论研究.由于时间域航空电磁反演问题是典型的不适定问题,多解性严重且稳定性能较差.为此,论文使用Tikhonov正则化反演方法进行一维解释,可以得到用最光滑模型、最平坦模型和最小构造模型约束条件下的反演结果,而正则化因子是根据各次迭代的数据目...     

时间域航空电磁三维并行反演研究（英文）

为提高复杂条件下时间域航空电磁数据解释精度,本文开展了时间域航空电磁三维并行反演算法研究。该算法中的三维正演是基于有限差分技术,并采用"移动脚印"技术来减小实际计算模型尺寸;三维反演基于Gauss-Newton反演方法,并采用显式灵敏度矩阵计算技术减少反演过程中的正演次数。为提高三维反演的效率,本文基于OpenMP并行库实现了三维反演的并行化。从理论和实测数据的三维并行反演结果可以看出本文的并行化策略明显地提高了三维反演的速度,能够胜任大数据量时间域航空电磁实测资料三维反演解释任务。     

频率域航空电磁数据的加权横向约束反演

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.     

时间域航空电磁法激电信息提取研究

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.     

时间域航空电磁激发极化参数三维反演研究

时间域航空电磁中心回线(或重叠回线)装置晚期道数据受激电效应影响常出现符号反转现象.这类数据与多个激电参数相关,并且各参数之间灵敏度差异较大,导致反演存在严重的非唯一性.本文提出一种基于Pearson相关性约束和深度学习算法相结合的时间域航空电磁激发极化参数反演策略.该反演策略首先基于深度学习预测时间域航空电磁激电参数,进而给时间常数和频率相关系数一个较小的约束范围后再反演电阻率和极化率,由此大大减少反演的多解性.针对电阻率和极化率的反演,我们采用统计学中Pearson相关系数构建两种物性参数的相关性约束,进一步减少反演多解性.为验证反演策略的有效性,我们对双棱柱模型和拱形模型分别进行反演试算.理论测试结果表明,基于Pearson相关性约束的电阻率和极化率的反演结果比传统的高斯-牛顿反演结果更接近真实模型,而基于深度学习预测时间常数和频率相关系数后的电阻率和极化率反演结果与给定真实时间常数和频率相关系数后的反演结果效果相当.最后,我们对来自澳大利亚的带激电效应的航空电磁实测数据在考虑和不考虑激电效应条件下进行反演,结果表明考虑激电效应的反演无论数据拟合还是地电断面的连续性均得到明显改善...     

三维频率域航空电磁反演研究

航空电磁数据的三维解释由于数据量大需要有高效的反演算法作为支撑.本文利用两种目前主流的数值优化技术（非线性共轭梯度和有限内存的BFGS法）实现了三维频率域航空电磁反演,并进一步比较了两种方法的有效性和运算效率.在反演过程中,为了更好地反演异常体的空间位置,模型方差矩阵中的光滑系数在反演起始阶段取值较大;当数据拟合差下降趋于平缓时,再利用较小的光滑因子约束反演过程来实现聚焦和获得精确的反演结果.理论数据反演表明这两种优化策略具有相似的内存需求,但是有限内存的BFGS技术比非线性共轭梯度法在计算时间和模型反演分辨率上具有一定的优越性,因此有限内存BFGS法更适合于求解大规模三维反演问题. 模型试验进一步表明目前主流的迭代法求解技术不适合大规模航空电磁数据反演,未来移动平台多源电磁数据快速正反演可通过引入矩阵分解技术来实现.     

频率域航空电磁数据变维数贝叶斯反演研究

传统的梯度反演方法已经广泛应用于频率域航空电磁数据处理中,然而此类方法受初始模型影响较大,且容易陷入局部极小.为解决这一问题,本文采用改进的变维数贝叶斯反演方法实现航空电磁数据反演.该方法根据建议分布对反演模型进行随机采样,并依据接受概率筛选合理的候选模型,最终获得反演模型的概率分布和不确定度信息.为解决贝叶斯反演方法对深部低阻层反演效果不佳的问题,本文通过引入合理加权系数,调整对反演模型约束强度,在很大程度上改善了反演效果.通过对模型统计方法进行改进,在遵循原有模型采样方法和接受标准的基础上,将满足数据拟合要求的模型纳入统计范围,削弱不合理模型对统计结果的干扰.本文最后通过对含有高斯噪声的理论数据和实测数据进行反演,并与Occam反演结果进行对比,验证了该方法的有效性.     

An iterative method for finding small magnetic objects in the subsurface by linear and non-linear inversion1

A method to determine the position and magnetization vector of buried objects producing a magnetic anomaly is described. The data used were collected in boreholes. Since the anomaly is due to a number of objects, a ‘stripping’ procedure is employed for finding them, and therefore the process of inversion for finding all objects causing the anomaly consists of a few inversion steps. In each inversion step, two dipoles are considered as a model which approximates an object. The position and magnetic moments of the dipoles are the unknown parameters. The initial parameters are optimized by minimization of an objective function. The optimization procedure consists of a combination of linear and non-linear inversion. The solution of the linear inversion is obtained by singular value decomposition and that of the non-linear inversion by a six-dimensional simplex method (polytope algorithm). After finding one object, its effect is subtracted (‘stripped’) from the data and a new inversion step is started with new initial models and with a reduced data set. The inversion steps for finding different objects are continued until the absolute norm of the data becomes less than some adjustable value. The data will also be inverted assuming a three-dipole model in order to find the effect of using a more complex model in the inversion. The efficiency of the method is demonstrated using synthetic and real borehole data.     

Inversion of surface gravity data for 3-D density modeling of geologic structures using total variation regularization

We develop an inversion procedure using the total variation (TV) regularization method as a stabilizing function to invert surface gravity data to retrieve 3-D density models of geologic structures with sharp boundaries. The developed inversion procedure combines several effective algorithms to solve the TV regularized problem. First, a matrix form of the gradient vector is designed using the Kronecker product to numerically approximate the 3-D TV function. The piecewise polynomial truncated singular value decomposition (PP-TSVD) algorithm is then used to solve the TV regularized inverse problem. To obtain a density model with depth resolution, we use a sensitivity-based depth weighting function. Finally, we apply the Genetic Algorithm (GA) to select the best combination of the PP-TSVD algorithm and the depth weighting function parameters. 3-D simulations conducted with synthetic data show that this approach produces sub-surface images in which the structures are well separated in terms of sharp boundaries, without the need of a priori detailed density model. The method applied to a real dataset from a micro-gravimetry survey of Gotvand Dam, southwestern Iran, clearly delineates subsurface cavities starting from a depth of 40 m within the area of the dam reservoir.     

1D inversion of DC resistivity data using a quality-based truncated SVD

Many DC resistivity inversion schemes use a combination of standard iterative least-squares and truncated singular value decomposition (SVD) to optimize the solution to the inverse problem. However, until quite recently, the truncation was done arbitrarily or by a trial-and-error procedure, due to the lack of workable guidance criteria for discarding small singular values. In this paper we present an inversion scheme which adopts a truncation criterion based on the optimization of the total model variance. This consists of two terms: (i) the term associated with the variance of statistically significant principal components, i.e. the standard model estimate variance, and (ii) the term associated with statistically insignificant principal components of the solution, i.e. the variance of the bias term. As an initial model for the start of iterations, we use a multilayered homogeneous half-space whose layer thicknesses increase logarithmically with depth to take into account the decrease of the resolution of the DC resistivity technique with depth. The present inversion scheme has been tested on synthetic and field data. The results of the tests show that the procedure works well and the convergence process is stable even in the most complicated cases. The fact that the truncation level in the SVD is determined intrinsically in the course of inversion proves to be a major advantage over other inversion schemes where it is set by the user.     

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.     

利用地震记录反演震源非均匀特征的一些问题

利用地震记录反演震源非均匀特征是目前强震地震学研究中的一个重要的课题。本文在总结现有文献的基础上，对与震源反演相关联的六个环节即震源模型及模型参数、格林函数计算、观测数据、反演准则与目标函数、初始模型与迭代方式、反演精度与分辨率等进行了初步阐述和分析，同时对地震源反演中存在的问题也进行了相应的讨论。     

(T2,D)二维核磁共振测井混合反演方法与参数影响分析

一维核磁共振(1D NMR)测井技术在流体识别中具有一定的局限性.二维核磁共振(2D NMR)测井能同时测量到多孔介质中横向弛豫时间(T₂)和扩散系数(D)等信息,利用这两个参数区分流体性质,较一维核磁共振测井技术具有明显的优越性.针对梯度场下的2D NMR测井弛豫机理和数学模型,提出了适用于求解大型稀疏矩阵方程的反演方法-基于非负最小二乘法(LSQR)和截断奇异值分解(TSVD)法的混合算法.为验证方法的有效性,先根据多回波观测模式合成回波串数据,然后再用混合反演算法进行反演,反演得到横向弛豫时间(T₂)和扩散系数(D),并构建T₂-D二维谱图.结果对比表明,该混合反演算法得到的T₂-D二维谱与流体模型一致性好,计算精度均比单一反演方法有较大改善,表明该混合反演方法可用于油气储集层2D NMR测井的反演和流体识别.此外,分别对油水同层和气水同层模型进行了正演模拟和反演实验, 系统考察了不同磁场梯度、不同回波间隔组合对反演效果的影响,为2D NMR参数设计提供依据.     

A Trade-Off Solution between Model Resolution and Covariance in Surface-Wave Inversion

Regularization is necessary for inversion of ill-posed geophysical problems. Appraisal of inverse models is essential for meaningful interpretation of these models. Because uncertainties are associated with regularization parameters, extra conditions are usually required to determine proper parameters for assessing inverse models. Commonly used techniques for assessment of a geophysical inverse model derived (generally iteratively) from a linear system are based on calculating the model resolution and the model covariance matrices. Because the model resolution and the model covariance matrices of the regularized solutions are controlled by the regularization parameter, direct assessment of inverse models using only the covariance matrix may provide incorrect results. To assess an inverted model, we use the concept of a trade-off between model resolution and covariance to find a proper regularization parameter with singular values calculated in the last iteration. We plot the singular values from large to small to form a singular value plot. A proper regularization parameter is normally the first singular value that approaches zero in the plot. With this regularization parameter, we obtain a trade-off solution between model resolution and model covariance in the vicinity of a regularized solution. The unit covariance matrix can then be used to calculate error bars of the inverse model at a resolution level determined by the regularization parameter. We demonstrate this approach with both synthetic and real surface-wave data.     

基于逆算子估计的AVO反演方法研究

传统反演算法以优化算法为主,而基于逆算子估计的AVO反演算法则利用了直接求逆的思路.算法的关键在于寻找存在逆函数的子域,进而可以在子域内直接求逆,这种解决反问题的思路不同于一般的优化类算法所采用的直接搜索解的方式,具有更高的效率.AVO反演利用了振幅随着偏移距的变化特征,反演的精度受到地震资料质量的影响,通过加入L1范数约束以及合理的初始模型有助于提高反演的稳定性以及准确度.模型测算和实际应用表明,基于逆算子估计的AVO反演方法具有较高的精确程度和可靠性.     

Global Optimisation of Time Domain Electromagnetic Data Using Very Fast Simulated Annealing

--Efficacy of the global optimisation technique is demonstrated in the inversion of time domain electromagnetic data. Transient EM responses observed using a coincident loops system along several profiles and different time channels over a plate like conducting body are inverted, using very fast simulated annealing (VFSA) as an optimisation tool. Three time channels for each profile are considered in the inversion. Study reveals that only one run of global inversion considering a single multi-channel profile is not enough to resolve all the nine model parameters of a plate-like conducting body. However, the global inversion of a single multi-channel profile with several runs yields a mean model that is quite close to the true model. Considering many profiles and time channels together in the global inversion can yield reliable estimates of all the parameters. Computationally, this is not an efficient procedure. Analysis of the results shows, however, that two distant profiles are enough to yield all the model parameters reliably, even after one run of the global inversion. Both noise-free and noisy synthetic data are used in the inversion. Finally, field data are also inverted to study the performance of the global inversion.     

Some elements of mathematical information theory and total inversion algorithm applied to travel time inversion

The total inversion algorithm and some elements of Mathematical Information Theory are used in the treatment of travel-time data belonging to a seismic refraction experiment from the southern segment (Sardinia Channel) of the European Geotraverse Project. The inversion algorithm allows us to improve a preliminary propagating model obtained by means of usual trial and error procedure and to quantify the resolution degree of parameters defining the crust and upper mantle of such a model. Concepts related to Mathematical Information Theory detect some seismic profiles of the refraction experiment which give the most homogeneous coverage of the model in terms of number of trajectories crossing it. Finally, the efficiency of the inversion procedure is quantified and the uncertainties regarding knowledge of different parts of the model are also evaluated.