Geophysical Prospecting - Advances in Electromagnetic, Gravity and Magnetic Methods for Exploration, 2011

Gravity data were used to investigate subsurface geology in the Ariana region from the Diapir Zone in Tunisia. Our study area is located in the north‐eastern part of the Maghrebides affected by the Alpine orogeny. Despite the smooth topography and the low density of the Quaternary series, integrated geological data and gravity responses (Bouguer anomaly and derivative mapping) help decipher the geological heterogeneities beneath the Quaternary overburden. The interpretation of the gravity data points to alignments of positive anomalies delineating two major orthogonal features that are thought to characterize the subsurface deep structures: 1) a lineament striking north‐west at the emplacement of an actual horst bordered by a buried fault‐system directed N140 and 2) a second counterpart striking north‐east, and is clearly expressed in the surface outcrops. These principal structural features were described as the result of a regional tectonic, compressive phase dating the Miocene. This phase was marked by reactivation and oblique‐slip displacements of regional faults; some of which (N070) are reverse and south‐east vergent. Further faulting enhanced the ascension of Triassic evaporites in diapir structures. This tectonic evolution may be integrated in the regional tectonic scheme of Alpine orogeny induced by a collision between African and European plates.

A 3D stochastic inversion method based on a geostatistical approach is presented for three‐dimensional inversion of gravity on multiple scale parameters using borehole density and gravity and surface gravity. The algorithm has the capability of inverting data on multiple supports. The method involves four main steps: i) upscaling of borehole densities to block densities, ii) selection of block densities to use as constraints, iii) inversion of gravity data with selected block densities as constraints and iv) downscaling of inverted densities to small prisms. Two modes of application are presented: estimation and simulation. The method is first applied to a synthetic stochastic model. The results show the ability of the method to invert surface and borehole data simultaneously on multiple scale parameters. The results show the usefulness of borehole data to improve depth resolution. Finally, a case study using gravity measurements at the Perseverance mine (Quebec, Canada) is presented. The recovered 3D density model identifies well three known deposits and it provides beneficial information to analyse the geology of massive sulfide for the domain under study.

This paper presents a procedure for interpreting magnetic data over tilted basement blocks. The objective of this procedure is to estimate source parameters of a tilted basement block from first‐ order derivatives of magnetic profile data. The method uses a model consisting of two superimposed infinite contacts with opposite dip. The procedure estimates the location of the crest (intersection of the two contacts) and the susceptibility contrast of the basement block from the total gradient anomaly data using a linear least‐squares method. Dip angles of the two contacts are estimated using iterative forward modelling of the tilt derivative anomaly data. The practical utility of the proposed approach is demonstrated using theoretical data and a field example from the northern North Sea.

We present a comprehensive review of the most common gravity and magnetic interpretation methods to in depth retrieval of the geometry of geologic bodies associated with a sedimentary basin. We identify three types of bodies: 1) the sedimentary basement relief, 2) salt bodies and 3) mafic intrusions in a sedimentary section. In reconstructing basement topography through gravity and/or magnetic data we identify three groups of methods: the automatic, the spectral and the nonspectral methods. The reconstruction of salt bodies from gravity data usually uses interactive forward modelling but recently gravity inversion methods have been developed to interpret this kind of geologic environment. Finally, the problem of reconstructing intrusive bodies using magnetic and/or gravity data employs three strategies to interpret mafic or ultramafic intrusions in a sedimentary section: the automatic methods, interactive forward modelling and the inversion methods.

Magnetic surveys for geophysical interpretation will most usefully furnish estimates of the three components of the magnetic field vector. We review methods for obtaining this information based on scalar and tensor magnetic field measurements and point out the advantages of fluxgate vector measurements. Fluxgate vector magnetometers can be powerful instruments in magnetic mapping. The main problems in using fluxgate magnetometers arise from calibration errors and drift but these can be overcome using a quick and simple method of calibration. This method also has the advantage of compensating permanent and induced magnetic fields generated by the airplane. This is illustrated by a new aeromagnetic survey flown in the Vosges area (France). Measurement accuracy is shown to be similar to that obtained with scalar magnetometers. We take advantage of this accuracy to calculate in the Fourier domain other magnetic functions from the total‐field anomaly, in particular, the magnetic gradient tensor is obtained without using any superconducting quantum devices. A similar approach is used to introduce a new magnetic anomaly tensor that is the equivalent of the pseudo‐gravity tensor. Maps presented in the last sections serve as an example to illustrate the various functions, the goal of the paper being to obtain magnetic vector data from the observations without first postulating the detailed nature of the sources.

Modern geophysical interpretation requires an interdisciplinary approach and software capable of handling multiple geophysical data types such as seismic, full tensor gravity gradiometry, magnetics and magnetotellurics. We use the IGMAS+ (Interactive Gravity and Magnetic Application System) geo‐modelling software that is designed for 3D gravity, gravity gradient and magnetic modelling. This paper deals with a special aspect of potential field modelling, combining conventional triangulated model geometries (building polyhedrons) with voxel cubes.

The hybrid modelling combines the advantages of both the vector and raster modelling system: both may be used alone (polyhedrons without voxels, voxels without polyhedrons) or simultaneously by superposition of both effects, which provides flexibility towards full interoperability. The key idea of our approach is, on the one hand to use two different, completely independent geometries (vector and raster) and give on the other hand the possibility to link both on demand for either editing the voxel model or to combine a large number of voxel cells under a common physical parameter function – which results in more reliable parameter inversion results.

The geological interpretation of gravity gradiometry data is a very challenging problem. While maps of different gravity gradients may be correlated with geological structures present, maps alone cannot quantify 3D density distributions related to geological structures. 3D inversion represents the only practical tool for the quantitative interpretation of gravity gradiometry data. However, 3D inversion is a complicated and time‐consuming procedure that is very dependent on the a priori model and constraints used. To overcome these difficulties for the initial stages of an interpretation workflow, we introduce the concept of potential field migration, and demonstrate how it can be applied for rapid 3D imaging of entire gravity gradiometry surveys. This method is based on a direct integral transformation of the observed gravity gradients into a subsurface density distribution that can be used for interpretation or as an a priori model for subsequent 3D regularized inversion. For large‐scale surveys, we show how migration runs on the order of minutes compared to hours for 3D regularized inversion. Moreover, the results obtained from potential field migration are comparable to those obtained from regularized inversion with smooth stabilizers. We present a case study for the 3D imaging of FALCON airborne gravity gradiometry data from Broken Hill, Australia. We observe good agreement between results obtained from potential field migration and those generated by 3D regularized inversion.

This paper interprets aeromagnetic data for a deep basin section of the Karroo rift in south‐east Tanzania. We use a novel integrated approach involving the application of advanced derivatives to define structure and the tilt‐depth method to determine and map the depth to basement. In the latter case we use the result of both reduced to pole and reduced to equator data to help constrain the shape and depth of the basin. We show that for a reduced to pole aeromagnetic data set, the generalized form of the local phase, called the tilt derivative, is an effective means of providing an initial (first pass) mapping of a sedimentary basin in terms of its fault structure, dip direction of faults and depth to basement. Since the amplitude of the tilt derivative does not contain information on the strength of the geomagnetic field nor magnetization (other than inclination) of the causative body, the susceptibility contrast across faults/contacts is derived from the analytic signal derivative. We also investigate how effective the tilt derivative and tilt‐depth method are for structural and depth to basement mapping in regions close to the magnetic equator, where the reduction to pole transform is often unstable; this is done using the same Tanzania data set transformed to the pole and the equator. We find that the tilt derivative applied to the reduction to equator data cannot be used to map the structure because of the effects of magnetic anisotropy, which results in the magnetic response of structures varying with strike azimuth. To overcome this anisotropy problem the analytic signal and/or local wavenumber derivatives, which are for all practical purposes independent of inclination, provide the best means of defining the major structural trends. We also find that the tilt‐depth method provides coherent depth to basement estimates for both reduced to pole and reduced to equator data. For the deep basin sections of the Karroo rift, there is a sparsity of tilt‐depth results from both the reduced to pole and reduced to equator data sets. However, each set of results has a different spatial coverage, so when combined they provide a better spatial sampling of the long wavelength magnetic character of the basin and thus improve the constraints on the minimum curvature gridding method to map the shape and depth of the basin.

Downward continuation is a useful transformation, mainly used to enhance measured gravity or magnetic field anomalies. It is known to be an unstable transformation that should be strictly used only in the harmonic region, apparently preventing any meaningful application to continuations inside the source volume. Despite these well‐known theoretical and practical limitations it has been used to recover source parameters by different methods, here referred to as normalized full gradient methods. Such methods show that downward continuation may be extended to the source volume, which is assumed to contain one‐point, isolated singularities, which is a quasi‐harmonic region. We modify the normalized full gradient method focusing our attention to the way the downward continuation is normalized. Differently from normalized full gradient methods, we study the effect of the normalization not only on the analytical signal modulus of the downward continued field but also on the downward continuation of the gravity or magnetic fields themselves. With our method, called normalized downward continuation, several statistically meaningful normalizations are considered, some of them yielding improved, more resolved depth estimations for synthetic as well as measured total‐field anomalies. From a statistical point of view, the downward continued field tends to have right‐skewed histograms at shallow depths, while becoming symmetrically distributed at greater depths. This occurs because, as the depth of continuation increases, the intrinsic error propagation of the downward continuation allows the error to dominate with respect to the source‐related signal. For non‐isolated anomalies, consistent results are also obtained but the normalizing factors must be computed within windows centred to the studied anomaly.

The key to deriving a reliable quantitative interpretation from marine controlled‐source electromagnetic data is through the integration of shared earth modeling and robust 3D electromagnetic inversion. Subsurface uncertainty is minimized through efficient workflows that use all available subsurface data as a priori information and which permit multiple resistivity models to explain the same observed data. To this end, we present our implementation of an iterative migration method for controlled‐source electromagnetic data that is equivalent to rigorous 3D inversion. Our iterative migration method is based on the 3D integral equation method with inhomogeneous background conductivity and focusing regularization with a priori terms. We will show that focusing stabilizers recover more geologically realistic models with sharper resistivity contrasts and boundaries than traditional smooth stabilizers. Additionally, focusing stabilizers have better convergence properties than smooth stabilizers. Finally, inhomogeneous background information described as a priori resistivity models can improve the fidelity of the final models. Our method is implemented in a fully parallelized code. This makes it practical to run large‐scale 3D iterative migration on multicomponent, multifrequency and multiline controlled‐source electromagnetic surveys for 3D models with millions of cells. We present a suite of interpretations obtained from different iterative migration scenarios for a 3D controlled‐source electromagnetic feasibility study computed from a detailed model of stacked anticline structures and reservoir units of the Shtokman gasfield in the Russian sector of the Barents Sea.

We discuss the problem of source control in controlled‐source electromagnetic (CSEM) surveying and compare and contrast equal energy transient square‐wave and transient pseudo‐random binary sequence source signatures for the same towed‐streamer electromagnetic survey line over the Peon gasfield in the Norwegian sector of the North Sea. The received response of the transient square‐wave data was 11 dB greater than that of the pseudo‐random binary sequence data, due to diffusive attenuation of higher frequencies present in the more broadband pseudo‐random binary sequence signature. Deconvolution of the pseudo‐random binary sequence data recovers the total impulse response function, increases the signal‐to‐noise ratio by 32.6 dB and separates most of the air wave from the earth impulse response by the causality principle. The recovered impulse responses have more detailed information in the frequency domain than the transient square‐wave data. The pseudo‐random binary sequence data were acquired with a 10 Hz source bit rate but contain no information about the Peon gasfield at frequencies above 2 Hz. The bit rate could have been reduced to 4 Hz, increasing the signal energy below 2 Hz by 150% and thus, potentially, increasing the signal‐to‐noise ratio by a further 4 dB.

Because the total earth impulse response can be recovered from the broad‐bandwidth pseudo‐random binary sequence data, further time‐domain processing may be applied, including correlated noise removal, which can increase the signal‐to‐noise ratio by as much as 20 dB, and air wave removal using the causality principle. The information in the arrival time of the peak of the earth response provides the potential for traveltime to resistivity mapping to provide a starting model for inversion.

Airborne transient electromagnetic (TEM) is a cost‐effective method to image the distribution of electrical conductivity in the ground. We consider layered earth inversion to interpret large data sets of hundreds of kilometres. Different strategies can be used to solve this inverse problem. This consists in managing the a priori information to avoid the mathematical instability and provide the most plausible model of conductivity in depth.

In order to obtain fast and realistic inversion program, we tested three kinds of regularization: two are based on standard Tikhonov procedure which consist in minimizing not only the data misfit function but a balanced optimization function with additional terms constraining the lateral and the vertical smoothness of the conductivity; another kind of regularization is based on reducing the condition number of the kernel by changing the layout of layers before minimizing the data misfit function. Finally, in order to get a more realistic distribution of conductivity, notably by removing negative conductivity values, we suggest an additional recursive filter based upon the inversion of the logarithm of the conductivity.

All these methods are tested on synthetic and real data sets. Synthetic data have been calculated by 2.5D modelling; they are used to demonstrate that these methods provide equivalent quality in terms of data misfit and accuracy of the resulting image; the limit essentially comes on special targets with sharp 2D geometries. The real data case is from Helicopter‐borne TEM data acquired in the basin of Franceville (Gabon) where borehole conductivity loggings are used to show the good accuracy of the inverted models in most areas, and some biased depths in areas where strong lateral changes may occur.

Well‐log data are processed in order to derive subsurface physical parameters, namely rock porosity, fluid saturations and permeability. This step involves the selection and inversion of experimental constitutive equations, which are the link between the rock parameters and geophysical measurements. In this paper we investigate the rock parameter observability and the reliability of well‐log data processing. We present a visual analysis of the constitutive equations and of the inverse problem conditioning, when using independently, or jointly, log data from different domains. The existence of a common set of rock properties (cross‐properties) that influence different measurements, makes it possible to reduce the ambiguities of the interpretation. We select a test case in a reservoir scenario and we explore how to determine rock porosity and fluid saturation from sonic, conductivity and density logs. We propose a Bayesian joint inversion procedure, which is able to control the conditioning problems, to efficiently take into account input data and model uncertainty and to provide a confidence interval for the solution. The inversion procedure is validated on a real well‐log data set.

Different geophysical methods were used to determine the characteristics of a highly conductive structure in Northern Sweden, first discovered on airborne data. Airborne electromagnetic (very low frequency) data indicate a high conductivity structure coincident with low magnetic patterns. The airborne data were processed in different ways to enhance various structures/features. In particular we introduce a new transformation to current density that is suitable for delineating conductive structures. Ground measurements of the total magnetic field, radiomagnetotelluric measurements and resistivity imaging provided valuable information that was used in the compilation of a new bedrock map over the area. The results of our measurements indicate that the conducting structure consists of metasedimentary rocks containing thin horizons of pyrrhotite and graphite.