Validation of joint inversion of direct current and electromagnetic measurements

One of the ways to improve the information content of a set of field data is that of combining the interpretation of disparate data sets. Electromagnetic and direct current resistivity methods suffer from inherent equivalence problem. Application of joint inversion for these measurements can overcome the problem of equivalence very well. In the present work, synthetic data from vertical electrical sounding (VES) and horizontal coplanar low-frequency induction sounding (EMHD) are inverted individually and jointly over different types of 1D earth structures. Global optimization with Monte Carlo Multistart algorithm was used in the calculations. The results obtained from the inversions of synthetic data indicate that the joint inversion significantly improves the solution reducing the ambiguity of the models.     

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.     

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.     

Pitfalls of 1D inversion of small-loop electromagnetic data for detecting man-made objects

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.     

Generalised Series Expansion (GSE) used in DC geoelectric–seismic joint inversion

Horizontally layered (1D) earth models are often assumed as a model estimate for the interpretation of geophysical data measured along 2D geological structures. In this process, the individual data sets are usually inverted independently, and it is considered only in a later phase of interpretation that these local (1D) models have common characteristic features. Taking account of these common attributes, instead of the successive independent interpretations, the lateral variations of geometrical and petrophysical parameters can be efficiently determined for the whole 2D structure by applying a series expansion. Using global basis functions, two advantages can be achieved: (i) choosing an appropriate number of basis functions helps us to restrict the complexity of the model; (ii) the integration of all the data sets measured along the profile gives rise to the application of simultaneous or joint inversion methods. This results in a decrease of the number of independent unknowns, a higher stability during the inversion and a more accurate and reliable parameter estimation.In this paper, a joint inversion algorithm is presented using DC geoelectric apparent resistivities and refraction seismic travel times measured along various layouts above a 2D geological model. To describe lateral variations series, expansions are used, and furthermore, to improve the often used approximation of a (locally) 1D forward modelling, the integral mean value of the horizontally changing model parameters (calculated along an appropriately defined interval) is introduced. We call the inversion procedure that combines series expansions and the concept of integral mean Generalised Series Expansion (GSE) inversion. The method was developed and tested for both the simultaneous (integrating data sets of one method or methods on the same physical basis) and the joint inversion (where data sets of methods on different physical bases are joined together), using synthetic and field data sets. It is also demonstrated that the equivalence problem inherent in the independent inversion of DC geoelectric data can efficiently be resolved by the use of the joint GSE inversion method in the cases of conductive and resistive equivalent geological models.     

ESTIMATION OF TEMPORAL CHANGES IN SOIL MOISTURE USING RESISTIVITY METHOD

The temporal variation in a soil moisture profile can be studied using resistivity sounding data acquired at different times. The layered earth model based estimation of soil moisture from apparent resistivity data is a two-step non-linear inversion. Firstly, the apparent resistivity data are inverted to derive the layer resistivity variations and thicknesses and, secondly, the moisture content is estimated from these layer resistivity variations using a calibration equation. The soil moisture–resistivity problem was studied using the one-dimensional formulation of resistivity problem. A generalized geoelectric earth model was considered to simulate the soil moisture distribution and its temporal variation in the unsaturated zone. An algorithm (RESMOS) for the interpretation of the apparent resistivity data in terms of soil moisture variations through this two-step inversion process is reported.     

CONTRIBUTION A L'ETUDE DE L'EQUIVALENCE EN PROSPECTION ELECTRIQUE (COURANT CONTINU ET MAGNETOTELLURIQUE)*

In all electrical methods (EM, MT, DC), a theoretical one-to-one relation links the apparent resistivity diagram at a station with the local distribution of the resistivities in a tabular earth. Unfortunately, the actual field diagrams derive from a few measurements of limited accuracy and the one-to-one relation vanishes. Calculating the distribution of the earth resistivities from the field diagrams is thus an undetermined problem, which experience has shown to be partly controlled by approximate laws of “equivalence”. The use of these rough rules can produce only a very restricted number of the resistivity distributions that correspond to calculated diagrams which do not differ from a given field curve by more than a tolerable discrepancy. On the other hand, the full set of such “equivalent” solutions is given automatically by a computer program. Tests made on field examples prove that a few geological data generally reduce the wide range of undetermination.     

一维垂直各向异性介质频率域海洋可控源电磁资料反演方法

本文提出了一维垂直各向异性(VTI)介质倾斜偶极源频率域海洋可控源电磁(CSEM)资料高斯-牛顿反演方法.在电阻率各向异性介质水平偶极源和垂直偶极源海洋CSEM正演算法的基础上,利用欧拉旋转方法,实现了各向异性介质倾斜偶极源海洋CSEM正演算法.海洋可控源电磁场关于地下介质横向电阻率(ρ_h)和垂向电阻率(ρ_v)的偏导数(即灵敏度矩阵)是解析计算的,结合垂直各向异性介质横向电阻率与垂向电阻率的关系,将各向异性率融入到正则化因子选择中,实现了正则化因子的自适应选择.理论模型合成数据和实测资料反演算例表明,我们提出的反演方法能够较准确的重构海底围岩和基岩的各向异性电阻率以及高阻薄层的埋藏深度、厚度和垂向电阻率.     

Laterally constrained inversion of helicopter-borne frequency-domain electromagnetic data

Helicopter-borne frequency-domain electromagnetic (HEM) surveys are used for fast high-resolution, three-dimensional resistivity mapping. Standard interpretation tools are often based on layered earth inversion procedures which, in general, explain the HEM data sufficiently. As a HEM system is moved while measuring, noise on the data is a common problem. Generally, noisy data will be smoothed prior to inversion using appropriate low-pass filters and consequently information may be lost.For the first time the laterally constrained inversion (LCI) technique has been applied to HEM data combined with the automatic generation of dynamic starting models. The latter is important because it takes the penetration depth of the electromagnetic fields, which can heavily vary in survey areas with different geological settings, into account. The LCI technique, which has been applied to diverse airborne and ground geophysical data sets, has proven to be able to improve the HEM inversion results of layered earth structures. Although single-site 1-D inversion is generally faster and — in case of strong lateral resistivity variations — more flexible, LCI produces resistivity — depth sections which are nearly identical to those derived from noise-free data.The LCI results are compared with standard single-site Marquardt–Levenberg inversion procedures on the basis of synthetic data as well as field data. The model chosen for the generation of synthetic data represents a layered earth structure having an inhomogeneous top layer in order to study the influence of shallow resistivity variations on the resolution of deep horizontal conductors in one-dimensional inversion results. The field data example comprises a wide resistivity range in a sedimentary as well as hard-rock environment.If a sufficient resistivity contrast between air and subsurface exists, the LCI technique is also very useful in correcting for incorrect system altitude measurements by using the altitude as a constrained inversion parameter.     

Model Fusion and Joint Inversion

Inverse problems are inherently non-unique, and regularization is needed to obtain stable and reasonable solutions. The regularization adds information to the problem and determines which solution, out of the infinitely many, is obtained. In this paper, we review and discuss the case when a priori information exists in the form of either known structure or in the form of another inverse problem for a different property. The challenge is to include such information in the inversion process. To use existing known structure, we review the concept of model fusion, where we build a regularization functional that fuses the inverted model to a known one. The fusion is achieved by four different techniques. Joint inversion of two data sets is achieved by using iterative data fusion. The paper discusses four different methods for joint inversion. We discuss the use of correspondence maps or the petrophysics of the rocks, as well as structure. In particular, we suggest to further stabilize the well-known gradient cross product and suggest a new technique, Joint Total Variation, to solve the problem. The Joint Total Variation is a convex functional for joint inversion and, as such, has favorable optimization properties. We experiment with the techniques on the DC resistivity problem and the borehole tomography and show how model fusion and joint inversion can significantly improve over existing techniques.     

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.     

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.     

航空电磁拟三维模型空间约束反演

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.     

Two-dimensional, regularised inversion of VLF data

Very low frequency electromagnetic (EM) methods using VLF transmitters have found many applications in subsurface geophysical investigations. Surface measurements involving both the vertical component of the magnetic field (VLF-EM or VLF-Z) and of the apparent resistivity (VLF-R) are increasingly common. Although extensive VLF data sets have been successfully used for mapping purposes, modelling and interpretation techniques which asess the third (i.e. depth) dimension appear limited.Given a profile of VLF-R measurements the main purpose of the present study is to demonstrate an automatic method for the construction of a resistivity cross-section. The technique used is one of a new generation of regularised inversion methods. These techniques attempt to overcome the problem of equivalence/non-uniqueness in EM sounding data by constructing the resistivity distribution with the minimum amount of structure that fits the data.VLF data represent a special case of plane-wave EM sounding in that they conform, in practice, to a single-frequency technique. This fact imposes a limitation in the amount of vertical resolution that we can expect using such data. In the case of two-dimensional modelling and inversion, resolution through the cross-section is a resultant attribute from both vertical and lateral resistivity gradients within the subsurface. In order to provide insight into the practical application of regularised inversion techniques to VLF data, both synthetic and field examples are considered. Both sets of examples are primarily concerned with VLF data applied to near-surface fault mapping where the main aim is to assess the location, dip and depth extent of conductive subsurface features.     

The effect of the electrical anisotropy on the response of helicopter-borne frequency-domain electromagnetic systems

Helicopter electromagnetic (HEM) systems are commonly used for conductivity mapping and the data are often interpreted using an isotropic horizontally layered earth model. However, in regions with distinct dipping stratification, it is useful to extend the model to a layered earth with general anisotropy by assigning each layer a symmetrical 3 × 3 resistivity tensor. The electromagnetic (EM) field is represented by two scalar potentials, which describe the poloidal and toroidal parts of the magnetic field. Via a 2D Fourier transform, we obtain two coupled ordinary differential equations in the vertical coordinate. To stabilize the numerical calculation, the wavenumber domain is divided into two parts associated with small and large wavenumbers. The EM field for small wavenumbers is continued from layer to layer with the continuity conditions. For large wavenumbers, the EM field behaves like a DC field and therefore cannot be sensed by airborne EM systems. Thus, the contribution from the large wavenumbers is simply ignored. The magnetic fields are calculated for the vertical coaxial (VCX), horizontal coplanar (HCP) and vertical coplanar (VCP) coil configurations for a helicopter EM system. The apparent resistivities defined from the VCX, VCP and HCP coil responses, when plotted in polar coordinates, clearly identify the principal anisotropic axes of an anisotropic earth. The field example from the Edwards Aquifer recharge area in Texas confirms that the polar plots of the apparent resistivities identify the principal anisotropic axes that coincide well with the direction of the underground structures.     

APPLICATION OF THE MULTIFREQUENCY HORIZONTAL-LOOP EM METHOD IN OVERBURDEN INVESTIGATIONS1

In recent years, geophysical methods (shallow seismic, electromagnetic, resistivity, ground penetrating radar) have been increasingly applied to overburden investigations. Their effectiveness has been found to depend significantly on local geological conditions. Compared with advanced seismic techniques, EM methods are faster and hence more cost-effective, but they have not been considered sufficiently accurate. Analysis is carried out of data obtained with the multifrequency horizontal-loop method (HLEM) in northeastern Ontario, where the overburden consists of Quaternary glacial and glaciolacustrine sediments. Surveying along 1-6 km long profiles permitted recognition of bedrock inhomogeneities and selection of sites suitable for HLEM data interpretation using the layered model. Phasor diagrams and computer inversion based on the ridge regression technique were used to interpret HLEM soundings obtained at eight frequencies. Interpreted layer resistivities and thicknesses were correlated with the results of Rotasonic drilling at 70 sites. Relatively accurate estimates of overburden thickness (within 10%) could be obtained in about 80% of the cases. Nine examples of HLEM soundings are given and discussed: three each of one-, two- and three-layer situations. An appropriate interpretation model cannot be selected simply by minimizing the rms error or by analysing the parameter resolution matrix. Frequently, the most effective way of evaluating a solution is to consider whether resistivity values determined by inversion fit any of the ranges determined by statistical analyses of sediment resistivities. A previously published study of electrical properties of Quaternary sediments indicated that resistivities of clay, till and sand are stable within a fairly large area, such as the one under investigation. While the application of HLEM methods to mapping of Quaternary sediments can be considered a success, interpretation of EM data in regions covered by glacial sediments is more difficult than in weathered terrains, where near-surface layering is more predictable. The problem of equivalence causes non-uniqueness in interpretation. Thickness equivalence, which results in poor resistivity estimates, was found to affect areas convered by sand and till. Conductance equivalence caused poor resolution of thickness and resistivity for thin clay layers (less than 10 m).     

Stochastic joint inversion of hydrogeophysical data for salt tracer test monitoring and hydraulic conductivity imaging

The assessment of hydraulic conductivity of heterogeneous aquifers is a difficult task using traditional hydrogeological methods (e.g., steady state or transient pumping tests) due to their low spatial resolution. Geophysical measurements performed at the ground surface and in boreholes provide additional information for increasing the resolution and accuracy of the inverted hydraulic conductivity field. We used a stochastic joint inversion of Direct Current (DC) resistivity and self-potential (SP) data plus in situ measurement of the salinity in a downstream well during a synthetic salt tracer experiment to reconstruct the hydraulic conductivity field between two wells. The pilot point parameterization was used to avoid over-parameterization of the inverse problem. Bounds on the model parameters were used to promote a consistent Markov chain Monte Carlo sampling of the model parameters. To evaluate the effectiveness of the joint inversion process, we compared eight cases in which the geophysical data are coupled or not to the in situ sampling of the salinity to map the hydraulic conductivity. We first tested the effectiveness of the inversion of each type of data alone (concentration sampling, self-potential, and DC resistivity), and then we combined the data two by two. We finally combined all the data together to show the value of each type of geophysical data in the joint inversion process because of their different sensitivity map. We also investigated a case in which the data were contaminated with noise and the variogram unknown and inverted stochastically. The results of the inversion revealed that incorporating the self-potential data improves the estimate of hydraulic conductivity field especially when the self-potential data were combined to the salt concentration measurement in the second well or to the time-lapse cross-well electrical resistivity data. Various tests were also performed to quantify the uncertainty in the inverted hydraulic conductivity field.     

Three-dimensional imaging of subsurface structures using resistivity data

We have developed a three-dimensional inverse scheme for carrying out DC resistivity surveys, incorporating complicated topography as well as arbitrary electrode arrays. The algorithm is based on the finite-element approximation to the forward problem, so that the effect of topographic variation on the resistivity data is effectively evaluated and incorporated in the inversion. Furthermore, we have enhanced the resolving power of the inversion using the active constraint balancing method. Numerical verifications show that a correct earth image can be derived even when complicated topographic variation exists. By inverting the real field data acquired at a site for an underground sewage disposal plant, we obtained a reasonable image of the subsurface structures, which correlates well with the surface geology and drill log data.     

Forward modeling of marine DC resistivity method for a layered anisotropic earth

Since the ocean bottom is a sedimentary environment wherein stratification is well developed, the use of an anisotropic model is best for studying its geology. Beginning with Maxwell’s equations for an anisotropic model, we introduce scalar potentials based on the divergence-free characteristic of the electric and magnetic (EM) fields. We then continue the EM fields down into the deep earth and upward into the seawater and couple them at the ocean bottom to the transmitting source. By studying both the DC apparent resistivity curves and their polar plots, we can resolve the anisotropy of the ocean bottom. Forward modeling of a high-resistivity thin layer in an anisotropic half-space demonstrates that the marine DC resistivity method in shallow water is very sensitive to the resistive reservoir but is not influenced by airwaves. As such, it is very suitable for oil and gas exploration in shallowwater areas but, to date, most modeling algorithms for studying marine DC resistivity are based on isotropic models. In this paper, we investigate one-dimensional anisotropic forward modeling for marine DC resistivity method, prove the algorithm to have high accuracy, and thus provide a theoretical basis for 2D and 3D forward modeling.     

ELRIS2D: A MATLAB Package for the 2D Inversion of DC Resistivity/IP Data

ELRIS2D is an open source code written in MATLAB for the two-dimensional inversion of direct current resistivity (DCR) and time domain induced polarization (IP) data. The user interface of the program is designed for functionality and ease of use. All available settings of the program can be reached from the main window. The subsurface is discre-tized using a hybrid mesh generated by the combination of structured and unstructured meshes, which reduces the computational cost of the whole inversion procedure. The inversion routine is based on the smoothness constrained least squares method. In order to verify the program, responses of two test models and field data sets were inverted. The models inverted from the synthetic data sets are consistent with the original test models in both DC resistivity and IP cases. A field data set acquired in an archaeological site is also used for the verification of outcomes of the program in comparison with the excavation results.