Rigorous 3D inversion of marine CSEM data based on the integral equation method

Journal ArticleMarine controlled-source electromagnetic (MCSEM) surveys have become an important part of offshore petroleum exploration. However, due to enormous computational difficulties with full 3D inversion, practical interpretation of MCSEM data is still a very challenging problem. We present a new approach to 3D inversion of MCSEM data based on rigorous integral-equation (IE) forward modeling and a new IE representation of the sensitivity (Fréchet derivative matrix) of observed data to variations in sea-bottom conductivity. We develop a new form of the quasi-analytical approximation for models with variable background conductivity (QAVB) and apply this form for more efficient Fréchet derivative calculations. This approach requires just one forward modeling on every iteration of the regularized gradient-type inversion algorithm, which speeds up the computations significantly. We also use a regularized focusing inversion method, which provides a sharp boundary image of the petroleum reservoir. The methodology is tested on a 3D inversion of the synthetic EM data representing a typical MCSEM survey conducted for offshore petroleum exploration

New approach to interpretation of airborne magnetic and electromagnetic data

Journal ArticleWe present a new technique for underground imaging based on the idea of space-frequency filtering and downward continuation of the observed airborne magnetic and electromagnetic data. The technique includes two major methods. The first method is related to the downward analytical continuation and is based on the calculation of the total normalized gradient of the observed field. The second method is based on Wiener filtering and takes into account a priori information about typical AEM anomaly shape from a possible target

Novel approach to the model appraisal and resolution analysis of regularized geophysical inversion

Journal ArticleThe existing techniques for appraisal of geophysical inverse images are based on calculating the model resolution and the model covariance matrices. In some applications, however, it becomes desirable to evaluate the upper bounds of the variations in the solution of the inverse problem. It is possible to use the Cauchy inequality for the regularized least-squares inversion to quantify the ability of an experiment to discriminate between two similar models in the presence of noise in the data. We present a new method for resolution analysis based on evaluating the spatial distribution of the upper bounds of the model variations and introduce a new characteristic of geophysical inversion, resolution density, as an inverse of these upper bounds.We derive an efficient numerical technique to compute the resolution density based on the spectral Lanczos decomposition method (SLDM). The methodology was tested on 3D synthetic linear and nonlinear electromagnetic (EM) data inversions, and also to interpret the helicopter-borne EM data collected by INCO Exploration in the Voisey's Bay area of Canada

Three-dimensional quasi-linear electromagnetic modeling and inversion

Journal ArticleThe quasi-linear (QL) approximation replaces the (unknown) total field in the integral equation of electromagnetic (EM) scattering with a linear transformation of the primary field. This transformation involves the product of the primary field with a reflectivity tensor, which is assumed to vary slowly inside inhomogeneous regions and therefore can be determined numerically on a coarse grid by a simple optimization. The QL approximation predicts EM responses accurately over a wide range of frequencies for conductivity contrasts of more than 100 to 1 between the scatterer and the background medium. It also provides a fast-forward model for 3-D EM inversion. The inversion equation is linear with respect to a modified material property tensor, which is the product of the reflectivity tensor and the anomalous conductivity. We call the (regularized) solution of this equation a quasi-Born inversion. The material property tensor (obtained by inversion of the data) then is used to estimate the reflectivity tensor inside the inhomogeneous region and, in turn, the anomalous conductivity. Solution of the nonlinear inverse problem thus proceeds through a set of linear equations. In practice, we accomplish this inversion through gradient minimization of a cost function that measures the error in the equations and includes a regularization term. We use synthetic experiments with plane-wave and controlled sources to demonstrate the accuracy and speed of the method

Three-dimensional regularized focusing inversion of gravity gradient tensor component data

Journal ArticleWe develop a new method for interpretation of tensor gravity field component data, based on regularized focusing inversion. The focusing inversion makes its possible to reconstruct a sharper image of the geological target than conventional maximum smoothness inversion. This new technique can be efficiently applied for the interpretation of gravity gradiometer data, which are sensitive to local density anomalies. The numerical modeling and inversion results show that the resolution of the gravity method can be improved significantly if we use tensor gravity data for interpretation. We also apply our method for inversion of the gradient gravity data collected by BHP Billiton over the Cannington Ag-Pb-Zn orebody in Queensland, Australia. The comparison with the drilling results demonstrates a remarkable correlation between the density anomaly reconstructed by the gravity gradient data and the true structure of the orebody. This result indicates that the emerging new geophysical technology of the airborne gravity gradient observations can improve significantly the practical effectiveness of the gravity method in mineral exploration

Parameter estimation for 3-D geoelectromagnetic inverse problems

Journal ArticleParameter estimation in geoelectromagnetics aims to obtain the most important parameters of a well-defined conductivity model of the Earth. These parameters are features of typical geological structures, such as depth and size of conductive or resistive targets, angle of dike inclination and its length, and conductivity of anomalous bodies. We develop this approach through regularized nonlinear optimization. We use finite differences of forward computations and Broyden's updating formula to compute sensitivities (Frechet or partial derivatives) for each parameter. To estimate the optimal step length, we apply line search, with a simple and fast parabolic correction. Our inversion also includes Tikhonov's regularization procedure. We use our method to study measurements of the magnetic fields from a conductive body excited by a loop source at the surface. Keeping the depth of the body constant, we estimate the horizontal coordinates of the body from three components of the magnetic field measured in a borehole. These measurements accurately determine the direction to the conductive target

Localized S-inversion of time-domain electromagnetic data

Journal ArticleInterpretation of time-domain electromagnetic (TDEM) data over inhomogeneous geological structures is a challenging problem of geophysical exploration. The most widely used approach of interpreting TDEM data is based on the smooth 1-D layered resistivity inversion. We have developed an effective technique of fast TDEM inversion based on thin-sheet conductance approximation that we call S-inversion. In this paper we extend the S-inversion technique, approximating the conductivity cross-section by adding a local inhomogeneous disk with an excess conductance 1S to the horizontal conductive thin sheet used in S-inversion. Localized S-inversion determines the distribution of this excess conductance as a function of a depth and a horizontal coordinate. This new method takes into account the limited horizontal extent of the inhomogeneities, localizing inversion. The numerical modeling results and inversion of practical TDEM data demonstrate that the method resolves local geological targets better than traditional 1-D inversion and original S-inversion. The method can be applied to interpret both ground and airborne TDEM data sets

3-D magnetic inversion with data compression and image focusing

Journal ArticleWe develop a method of 3-D magnetic anomaly inversion based on traditional Tikhonov regularization theory. We use a minimum support stabilizing functional to generate a sharp, focused inverse image. An iterative inversion process is constructed in the space of weighted model parameters that accelerates the convergence and robustness of the method. The weighting functions are selected based on sensitivity analysis. To speed up the computations and to decrease the size of memory required, we use a compression technique based on cubic interpolation. Our method is designed for inversion of total magnetic anomalies, assuming the anomalous field is caused by induced magnetization only. The method is applied to synthetic data for typical models of magnetic anomalies and is tested on real airborne data provided by Exxon-Mobil Upstream Research Company

Focusing geophysical inversion images

Journal ArticleA critical problem in inversion of geophysical data is developing a stable inverse problem solution that can simultaneously resolve complicated geological structures. The traditional way to obtain a stable solution is based on maximum smoothness criteria. This approach, however, provides smoothed unfocused images of real geoelectrical structures. Recently, a new approach to reconstruction of images has been developed based on a total variational stabilizing functional. However, in geophysical applications it still produces distorted images. In this paper we develop a new technique to solve this problem which we call focusing inversion images. It is based on specially selected stabilizing functionals, called minimum gradient support (MGS) functionals, which minimize the area where strong model parameter variations and discontinuity occur. We demonstrate that the MGS functional, in combination with the penalization function, helps to generate clearer and more focused images for geological structures than conventional maximum smoothness or total variation functionals. The method has been successfully tested on synthetic models and applied to real gravity data

Electromagnetic inversion using quasi-linear approximation

Journal ArticleThree-dimensional electromagnetic inversion continues to be a challenging problem in electrical exploration. We have recently developed a new approach to the solution of this problem based on quasi-linear approximation of a forward modeling operator. It generates a linear equation with respect to the modified conductivity tensor, which is proportional to the reflectivity tensor and the complex anomalous conductivity. We solved this linear equation by using the regularized conjugate gradient method. After determining a modified conductivity tensor, we used the electrical reflectivity tensor to evaluate the anomalous conductivity. Thus, the developed inversion scheme reduces the original nonlinear inverse problem to a set of linear inverse problems. The developed algorithm has been realized in computer code and tested on synthetic 3-D EM data. The case histories include interpretation of a 3-D magnetotelluric survey conducted in Hokkaido, Japan, and the 3-D inversion of the tensor controlled-source audio magnetotelluric data over the Sulphur Springs thermal area, Valles Caldera, New Mexico, U.S.A