基于交叉梯度约束的时间域激发极化法二维同步反演

时间域激发极化法(Time-domain induced polarization method,简称为TDIP)已有的反演算法采用的是分步反演的思路,即先由视电阻率资料反演电阻率,固定电阻率再由视极化率资料反演极化率,这样就存在极化率结果严重依赖于电阻率反演结果的问题.为了有效解决这一问题,本文实现了TDIP二维数据空间分步反演算法,提出了基于交叉梯度约束的TDIP二维同步反演策略,实现了交叉梯度约束的电阻率和极化率二维同步反演算法.分别用电阻率和极化率结构一致和不一致的二维模型合成数据进行了分步和同步反演试算,对不同模型试算结果进行了对比分析.结果表明:对于电阻率和极化率结构一致和不一致模型,同步反演结果比分步反演结果能更好地确定异常体的空间分布范围,反演得到的电阻率和极化率值更接近真值.理论模型算例表明本文提出的同步反演算法有效解决了分步反演的问题,优于分步反演算法,具有更好的实用性.     

ZTEM三维数据空间OCCAM反演研究

Z轴倾子电磁法(ZTEM)是一种极具前景的新型天然源频率域航空电磁法,具有勘探深度较大,工作效率高的特点.本文基于大地电磁法(MT)三维数据空间OCCAM反演算法,实现了三维ZTEM倾子资料的数据空间反演算法.将该算法应用到理论合成算例中进行反演,反映出ZTEM倾子反演对模型横向边界的约束优于垂向的特性,并且与MT阻抗反演结果进行对比,验证了所实现的倾子资料三维数据空间反演算法的有效性,表明ZTEM倾子反演在约束电阻率模型横向位置能力上更具优越性.该反演算法可用于ZTEM所整理得到的倾子数据进行三维定量反演,实现大区域的地质构造三维成像,获得地下地质模型的电阻率结构信息.     

直流电阻率法与大地电磁法的二维联合反演

本文对电性联合反演进行了深入研究,以减少地球物理反演的多解性.将直流电阻率(DC)与大地电磁(MT)数据加入到同一反演数据集中.引入Tikhonov正则化思想建立反演目标函数,使反演过程更加高效稳定.在解决正则化反演问题过程中,分别采用了二阶最大平滑稳定因子和改进的L-curve法,提高了反演结果的稳定性和正则化因子的求取精度;最后运用非线性共轭梯度法(NLCG)对反演目标函数实现最优化求解.经研究表明:联合反演方法与单一反演方法相比,能够更加有效的约束反演模型范围;反演算法快速稳定,提高了反演精度,减少了对地下地质结构认识的模糊性.     

地面磁共振与瞬变电磁橫向约束联合反演方法研究

大地电阻率分布信息是影响磁共振地下水探测反演结果准确性的重要因素.在众多电磁法勘探技术中,瞬变电磁法具有高分辨率、高效率和大探测深度等优势,能准确探测地下几百米范围内的电阻率分布信息.因此磁共振与瞬变电磁联合解释方法具有重要意义.然而,利用单一测点拼接的磁共振与瞬变电磁联合解释方法进行模拟二维反演时存在解释结果不唯一,容易出现错误异常体等问题,尤其在复杂地质情况下,同一测线上相邻测点探测结果连续性差,解释结果偏离实际.基于此,本文提出磁共振与瞬变电磁横向约束联合反演方法(Laterally Constrained Inversion,简称LCI),重点引入外推积分法(quadrature with extrapolation,简称QWE),解决了传统正演过程中基于直接数值积分方法引起的求解效率低的问题,保证了联合反演方法的顺利实施,进而以相邻测点地下结构应具备连续性为依据,引入横向约束反演思想,通过在联合反演目标函数中加入相邻测点间各模型参数约束矩阵,提高磁共振解释结果准确性,加强探测剖面地质结构和含水模型连续性.经过理论模型证实,本文提出的LCI方法能有效提高传统一维反演结果的稳定性和唯一性.最后,对安徽黄山野外实际探测数据进行横向约束联合反演,验证了磁共振与瞬变电磁LCI联合反演方法的实用性.本文的研究成果将为磁共振与瞬变电磁空间约束联合反演奠定基础.     

2.5维复电阻率反演及其应用试验

自复电阻率法被提出以来,其区分矿与非矿方面的潜力就引起了人们的广泛关注,但反演问题一直没有得到较好的解决,已经严重影响和制约了该方法的应用和发展.对此,本文提出并实现了利用多个排列视电阻率和视相位数据的2.5维SIP联合反演方法.算法利用最小二乘原理构建了反演目标函数,为提高反演的稳定性,在反演方程中加入了Occam法的光滑模型约束.通过借助电场的偏导数形式,推导出了灵敏度矩阵的解析表达式,并应用互换定理对其进行精确求取.反演算法充分利用了电磁感应和激电效应中的异常信息,能够同时反演出二维地质断面上所有单元的四种复电阻率参数.最后,利用该反演程序对安徽某地区的SIP实测数据进行了反演成像,通过与已知钻井资料及CSAMT反演结果的对比分析表明,该反演算法具有良好的应用效果.     

分层多指数磁共振弛豫信号反演方法研究

磁共振测深技术传统反演方法包括平滑反演和分块反演,通过分别获取初始振幅和平均弛豫时间构建地层含水量及有效孔隙度.然而,这些方法局限于单指数拟合方式,损失了大部分有效采集信息,受限于多孔地质环境解释,并在某些情况下无法刻画含水层清晰分界面.针对上述问题,本文建立了基于MRS全数据的多指数反演方法,依据全部采集时间下的有效信息,通过弛豫时间e指数分解,推导出新的磁共振正演核函数,结合泛函极小值方程,直接反演建立含水量,弛豫时间及地层深度三个重要参数关系,适用于复杂地质环境解释.为得到快速稳定的反演结果和更清晰的含水层分界面,本文借鉴分块反演思想,进一步构建了新的反演目标函数,利用基于不等式约束的空间信赖域算法进行优化,最终实现了一种基于分层反演与多指数结合的磁共振弛豫信号反演方法.模型数据以及实测算例表明该方法的效果和优势,并具备较高的计算效率,本研究为地面磁共振反演提供了一种新的思路与方法.     

基于最小支撑泛函模型约束的电阻率法三维聚焦反演

目前电阻率法三维反演方法大多是基于最小构造或最平缓模型约束的反演,这些反演算法能稳定收敛,但有时反演结果分辨率较差,不利于地质解释.本文在分析Zhdanov(2002)提出的基于最小支撑泛函聚焦反演方法的基础上,将最小支撑泛函引入到电阻率法三维反演的目标函数中,然后采用高斯牛顿法求解反演目标函数最优化问题,同时结合预条件共轭梯度法得到电阻率法三维聚焦反演结果.通过对几个典型模型的试算,并与传统光滑模型约束反演结果进行比较,表明本文反演方法结果与实际模型吻合的更好,分辨率更高,模型更聚焦,而且算法收敛速度较快.     

地面磁共振与瞬变电磁横向约束联合反演方法研究

大地电阻率分布信息是影响磁共振地下水探测反演结果准确性的重要因素.在众多电磁法勘探技术中,瞬变电磁法具有高分辨率、高效率和大探测深度等优势,能准确探测地下几百米范围内的电阻率分布信息.因此磁共振与瞬变电磁联合解释方法具有重要意义.然而,利用单一测点拼接的磁共振与瞬变电磁联合解释方法进行模拟二维反演时存在解释结果不唯一,容易出现错误异常体等问题,尤其在复杂地质情况下,同一测线上相邻测点探测结果连续性差,解释结果偏离实际.基于此,本文提出磁共振与瞬变电磁横向约束联合反演方法（Laterally Constrained Inversion,简称LCI）,重点引入外推积分法（quadrature with extrapolation,简称QWE）,解决了传统正演过程中基于直接数值积分方法引起的求解效率低的问题,保证了联合反演方法的顺利实施,进而以相邻测点地下结构应具备连续性为依据,引入横向约束反演思想,通过在联合反演目标函数中加入相邻测点间各模型参数约束矩阵,提高磁共振解释结果准确性,加强探测剖面地质结构和含水模型连续性.经过理论模型证实,本文提出的LCI方法能有效提高传统一维反演结果的稳定性和唯一性.最后,对安徽黄山野外实际探测数据进行横向约束联合反演,验证了磁共振与瞬变电磁LCI联合反演方法的实用性.本文的研究成果将为磁共振与瞬变电磁空间约束联合反演奠定基础.     

基于交叉梯度约束的电阻率法和背景噪声法三维联合反演研究

电阻率法和背景噪声法是通过获得地下介质的电阻率和速度参数的分布来探究地球内部物质分布的非均匀性特征,联合反演可以有效地发挥两种方法的优势,减小反演多解性.本文采用有限内存拟牛顿（L-BFGS）算法实现了电阻率法和背景噪声法的单方法三维反演,然后基于电阻率和速度模型结构耦合约束,采用交替迭代方式实现了电阻率法和背景噪声法的三维联合反演.通过设计规则体组合模型和不规则体组合模型进行理论模型合成数据三维反演试算,结果表明：联合反演可以获得同时满足数据拟合差和结构更为相似的速度-电阻率模型;联合反演可以压制背景噪声单方法反演出现的假异常,获得更精细的速度结构;联合反演获得的电阻率模型对倾斜异常体、高阻覆层下方异常体、圈闭的高/低阻体等边界信息有明显的提升,有效克服电阻率法单方法反演的局限,提高深部电阻率的分辨率.     

基于物性参数梯度累加约束的电阻率法和重力勘探数据二维联合反演

对不同地球物理方法的数据进行联合反演,通过模型参数的相互约束可以减小反演的多解性.本文对电阻率法和重力勘探数据开展了基于电阻率和剩余密度梯度累加约束的二维联合反演研究.电阻率法采用数据空间Occam反演,重力勘探采用基于对数障碍法的正则化反演.通过在电阻率法和重力勘探反演的目标函数中引入电阻率和剩余密度梯度累加约束项,利用交替迭代方式实现了电阻率法和重力勘探数据的二维联合反演.对理论模型合成数据进行了单方法反演和联合反演,对比了反演效果.结果表明：联合反演结果优于单方法反演结果,联合反演结果对异常体的物性值恢复和形态刻画效果更好.     

Two-dimensional joint inversion of radiomagnetotelluric and direct current resistivity data

An algorithm for the two-dimensional (2D) joint inversion of radiomagnetotelluric and direct current resistivity data was developed. This algorithm can be used for the 2D inversion of apparent resistivity data sets collected by multi-electrode direct current resistivity systems for various classical electrode arrays (Wenner, Schlumberger, dipole-diplole, pole-dipole) and radiomagnetotelluric measurements jointly. We use a finite difference technique to solve the Helmoltz and Poisson equations for radiomagnetotelluric and direct current resistivity methods respectively. A regularized inversion with a smoothness constrained stabilizer was employed to invert both data sets. The radiomagnetotelluric method is not particularly sensitive when attempting to resolve near-surface resistivity blocks because it uses a limited range of frequencies. On the other hand, the direct current resistivity method can resolve these near-surface blocks with relatively greater accuracy. Initially, individual and joint inversions of synthetic radiomagnetotelluric and direct current resistivity data were compared and we demonstrated that the joint inversion result based on this synthetic data simulates the real model more accurately than the inversion results of each individual method. The developed 2D joint inversion algorithm was also applied on a field data set observed across an active fault located close to the city of Kerpen in Germany. The location and depth of this fault were successfully determined by the 2D joint inversion of the radiomagnetotelluric and direct current resistivity data. This inversion result from the field data further validated the synthetic data inversion results.     

Inversion of resistivity in Magnetic Resonance Sounding

Magnetic Resonance Sounding (MRS, or Surface Nuclear Magnetic Resonance - SNMR) is used for groundwater exploration and aquifer characterization. Since this is an electromagnetic method, the excitation magnetic field depends on the resistivity of the subsurface. Therefore, the resistivity has to be taken into account in the inversion: either as a priori information or as an inversion parameter during the inversion process, as introduced in the presented paper. Studies with synthetic data show that water content and resistivity can be resolved for a low resistive aquifer even using only the amplitude of the MRS signal. However, the inversion result can be significantly improved using amplitude and phase of the MRS signal. The successful implementation of the inversion for field data shows that the resistivities derived from MRS are comparable to those from conventional geoelectric methods such as DC resistivity and transient electromagnetic. By having information about both the resistivity and the water content, MRS inversions give information about the quality of the water in the aquifer. This is of utmost interest in hydrogeological studies as this specific information cannot be determined solely by geoelectric measurements, due to the nonunique dependence of resistivity on water content and salinity.     

基于交叉梯度交替结构约束的二维地震走时与全通道直流电阻率联合反演

在利用不同的地球物理勘探方法对地下复杂介质成像时,因观测系统的非完备性及数据本身对某些岩石物性的不敏感性,单独成像的结果存在较大的不确定性和不一致性.对于地震体波走时成像与直流电阻率成像,均面临着成像阴影区问题.对于地震走时成像,地震射线对低速区域覆盖较差形成阴影区,造成低速区域分辨率降低.对于电阻率成像,电场线在高阻区域分布较少,造成高阻区域分辨率较低.为了提高地下介质成像的精度,Gallado和Meju(2003)提出了基于交叉梯度结构约束的联合地球物理成像方法.在要求不同的物性模型拟合各自对应的数据同时,模型之间的结构要求一致,即交叉梯度趋于零.为了更有效地实现基于交叉梯度的结构约束,我们提出了一种新的交替结构约束的联合反演流程,即交替反演不同的数据而且在反演一种数据时要求对应的模型与另一个模型结构一致.新的算法能够更容易地把单独的反演系统耦合在一起,而且也更容易建立结构约束和数据拟合之间的平衡.基于新的联合反演流程,我们测试了基于交叉梯度结构约束的二维跨孔地震走时和直流电阻率联合成像.合成数据测试表明,我们提出的交替结构约束流程能够很好地实现基于交叉梯度结构约束的联合成像.与单独成像结果相比,地震走时和全通道电阻率联合成像更可靠地确定了速度和电阻率异常.     

Joint parameter estimation from magnetic resonance and vertical electric soundings using a multi‐objective genetic algorithm

Magnetic resonance sounding (MRS) has increasingly become an important method in hydrogeophysics because it allows for estimations of essential hydraulic properties such as porosity and hydraulic conductivity. A resistivity model is required for magnetic resonance sounding modelling and inversion. Therefore, joint interpretation or inversion is favourable to reduce the ambiguities that arise in separate magnetic resonance sounding and vertical electrical sounding (VES) inversions. A new method is suggested for the joint inversion of magnetic resonance sounding and vertical electrical sounding data. A one‐dimensional blocky model with varying layer thicknesses is used for the subsurface discretization. Instead of conventional derivative‐based inversion schemes that are strongly dependent on initial models, a global multi‐objective optimization scheme (a genetic algorithm [GA] in this case) is preferred to examine a set of possible solutions in a predefined search space. Multi‐objective joint optimization avoids the domination of one objective over the other without applying a weighting scheme. The outcome is a group of non‐dominated optimal solutions referred to as the Pareto‐optimal set. Tests conducted using synthetic data show that the multi‐objective joint optimization approximates the joint model parameters within the experimental error level and illustrates the range of trade‐off solutions, which is useful for understanding the consistency and conflicts between two models and objectives. Overall, the Levenberg‐Marquardt inversion of field data measured during a survey on a North Sea island presents similar solutions. However, the multi‐objective genetic algorithm method presents an efficient method for exploring the search space by producing a set of non‐dominated solutions. Borehole data were used to provide a verification of the inversion outcomes and indicate that the suggested genetic algorithm method is complementary for derivative‐based inversions.     

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.     

基于不等式约束的三维电阻率探测混合反演方法

三维电阻率探测的线性反演和非线性反演中均存在着多解性的固有难题.电阻率线性反演方法的效率较高,但反演结果对初始模型的依赖性较强,易陷入局部极小;而非线性反演方法不依赖初始模型,但搜索效率极低,尚未见到关于三维电阻率非线性反演的文献.针对上述问题,融合线性与非线性反演方法的互补优势,提出了最小二乘法(线性方法)与改进遗传算法(非线性方法)相结合的混合反演方法的概念和思想.首先,提出了将介质电阻率变化范围作为不等式约束引入反演方程的思路,以实现压制多解性、提高可靠性的目标.提出了宽松不等式约束和基于钻孔推断的局部严格不等式约束的获取及定义方法.在此基础上,分别提出了基于不等式约束的最小二乘线性反演方法和遗传算法非线性反演方法.其次,对于遗传算法在变异搜索方向控制、初始群体产生等方面进行了改进,优化了其搜索方向和初始群体多样性.然后,提出了混合反演方法及其实现方案,利用改进遗传算法进行第一阶段反演,发挥其对初始模型的依赖程度低的优势,搜索到最优解附近的空间,输出当前最优个体;利用最小二乘法进行第二阶段反演,将遗传算法得到的当前最优个体作为初始模型,在最优解附近空间执行高效率的局部线性搜索,最终实现地电结构的三维成像.最后,开展了合成数据与实际工程算例验证,与传统最小二乘方法进行了对比,发现混合反演方法在压制多解性、摆脱初始模型依赖和提高反演效果方面有较好效果.     

基于交叉梯度约束的重力、磁法和大地电磁三维联合反演

为了降低单一地球物理方法反演的多解性及受噪声的影响程度,本文围绕重力、磁法和大地电磁法开展了三维联合反演的研究.重、磁采用基于对数障碍法的正则化反演算法,大地电磁使用limited-memory BroydenFletcher-Goldfarb-Shanno(L-BFGS)反演算法,引入交叉梯度函数实现了三种物性结构的相互耦合,最终开发出一套重磁电三维联合反演算法,并实现MPI并行加速计算.通过理论模型算例验证了算法的准确性,结果表明:不论是单棱柱体模型还是组合棱柱体模型,联合反演结果相较单独反演对于异常体的空间形态刻画以及物性数值恢复具有较好的提升;单棱柱体模型算例使得异常体的物性参数(密度、磁化率和电阻率)更加接近于真实的物性参数;组合棱柱体模型的联合反演结果不仅仅消除了围岩物性参数的假异常,而且还增强了异常体边界结构的恢复程度.     

一种高效的基于交叉梯度结构约束的三维地震走时与直流电阻率联合反演策略

基于交叉梯度结构约束的不同数据的联合反演可以提高地球物理成像的可靠度,但是由于不同观测数据对地下介质的灵敏度不同以及不同反演系统灵敏度矩阵元素的数值可能存在较大的差异,导致构建和求解联合反演系统存在很大的挑战.针对以上问题,本文提出一种新的基于单独反演模型更新量与交叉梯度结构约束相结合的联合反演策略.该策略利用单独反演系统分别确定出各个模型的更新量,然后利用它们约束交叉梯度系统的反演,得出新的模型更新量.通过这样的方式,有效实现了数据拟合与结构约束的平衡,实现了基于交叉梯度联合反演的目标.新的联合反演策略不需要对原来单独反演程序修改即可实现联合反演,减小了联合反演实现的难度,极大地提高了联合反演的易实现性,而且避免了联合反演矩阵存储及结构过于复杂难以求解的问题.基于新的策略,本文首次实现了基于交叉梯度结构约束的三维地震走时与直流电阻率联合反演.合成模型测试表明,与单一成像相比,联合成像减少了地震走时反演中出现的干扰异常并提高了电阻率反演的分辨率.