Full Tensor Gravity Gradiometry Research Articles

Joint inversion of full-tensor gravity gradiometry data based on source growing

Joint inversion of full-tensor gravity gradiometry data based on source growing

Joint focusing inversion of marine controlled-source electromagnetic and full tensor gravity gradiometry data

We have developed an approach for integrating the interdependent information of different geophysical methods to obtain a self-consistent geophysical model in offshore exploration. Electromagnetic (EM) and gravity data complement seismic data by providing information about the physical properties of prospective reservoir rocks. We have combined marine EM and gravity gradiometry geophysical data in joint inversion using a joint focusing stabilizer. The method enforces coupling between different physical models and simultaneously promotes focused images of the targets. We also consider the importance of using robust norms to analyze data collected by marine controlled-source EM surveys. The practical effectiveness of the developed method is illustrated by a case study of integrating and imaging marine multiphysics data collected in the Nordkapp Basin, Barents Sea, Norway.

Joint Nonlinear Inversion of Full Tensor Gravity Gradiometry Data and Its Parallel Algorithm

Geophysical joint inversion is more frequently applied to deep crust probes. For the potential field data, it requires the introduction of large-scale observed data and sensitivity matrices. Massive matrix-vector multiplications occur during iterations, and the obtained data cannot be effectively interpreted by merely using desktop computers. To improve the resolution and the computing ability of inversion, we here propose the parallel joint nonlinear inversion of full tensor gravity gradiometry data. As the inversion is affected by linear searches, it is associated with certain classical computing performance issues. Hence, we addressed the memory and efficiency limitations, which are caused by very large calculation volumes. Also, we performed a quantitative and comprehensive feasibility analysis of parallel computing. Then, we identified the main factor influencing the inversion performance and clarified the correspondence between the cell number and the memory. A parallel inversion solution was proposed via graphics processing unit (GPU) based on the sensitivity matrix compression. The data tests demonstrated that inversion has antinoise property and that it can obtain accurate underground density distributions. Also, the parallel solution was found to be suitable for inverting cells at the million cell scale and greater because of its ability of acceleration and matrix compression. A design pattern was applied for gravity or magnetic anomaly inversion of 100 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times 100\times20$ </tex-math></inline-formula> cells, and the run time was less than 1 min. Overall, we believe that the proposed solution can help implement massive potential field data inversions and promote the application of the parallel technique in other inversion research.

Shallow velocity modelling – the application of high-resolution Full Tensor Gravity Gradiometry data and seismic tomography: a Permian Basin case study

Subsurface imaging from surface seismic reflection data is often complex as a result of issues related to the surface and the near surface including noise (ambient or otherwise), differing coupling of the geophones/geophone arrays and different coupling between the sources and mixed sources and the ground. With the diversity in land seismic exploration and increasingly complex near-surface conditions advanced modelling capabilities are being used for velocity model generation in processing. In this article the use of a multi-physics approach that does not suffer from velocity-depth ambiguity and provides a robust shallow velocity model is presented. This case study is taken from a project in the Permian Basin, USA. It presents the integration of Airborne Full Tensor Gravity Gradiometry (FTG) with tomography and the unique approach applied by the authors for modelling the near surface velocity structure integrated with surface seismic data.

Structural interpretation of the Beetaloo Sub-basin, NT from nonseismic geophysical data

The Beetaloo Sub-basin is known for its vast unconventional hydrocarbon resources even though it is relatively underexplored. There is reasonably good coverage of 2D seismic within the sub-basin which is used as the basis for most structural interpretations. However, seismic quality varies, and it is occasionally deteriorated by the presence of basalts from the Kalkarindji suite and the karstic nature of the Gum Ridge formation. Aeromagnetic data, constrained by petrophysical logs are used, to map faults in the basalts of the Kalkarindji suite and their lateral extent to the South and the East of the sub-basin. The same structural elements are identified in the full tensor gravity gradiometry data. The top of this unit is observed in the electrical conductivity profiles, derived from Tempest data, in the NW part of the eastern sub-basin.

The Bathurst Mining Camp, New Brunswick: data integration, geophysical modelling, and implications for exploration

The Bathurst Mining Camp (BMC) is one of Canada’s oldest mining districts for volcanogenic massive sulphide (VMS) deposits. Most of the 46 known deposits were discovered in the 1950s using a combination of geological and geophysical methods. However, renewed exploration efforts over the past 15 years have not been as successful as one would expect given the level of expenditure of the camp. Nevertheless, this has created a large database of high resolution airborne geophysical data (magnetics, electromagnetics, radiometrics, and full tensor gravity gradiometry) which makes Bathurst a unique case. We show data compilation and map view interpretation, followed by two-and-a-half-dimensional (2.5D) gravity and magnetic modelling. From this, we provide constraints on the folded structure of the mafic and felsic volcanic units, and we interpret a large gravity anomaly in the southeast as a possible ophiolite or a dense thick package of basaltic rocks. Finally, we show an example of 3D modelling in the northwestern part of the camp, where we combine map view interpretation with section-based modelling and 3D geophysical inversion.

Applying laterally varying density corrections to ground gravity and airborne gravity gradiometry data: a case study from the Bathurst Mining Camp

The influence of topography on gravity and gravity gradiometry measurements is profound and should be minimized prior to geological interpretation. The standard way of minimizing these effects is through the computation of a terrain correction. Terrain corrections require two inputs: topography and density. Often, geology and topography are inextricably intertwined: topography is caused by a change in geology. In geologic environments where there is a structural and (or) stratigraphic control on the near-surface mass distribution, using a single density value in the corrections leads to removal of the topographic effect of rocks having the chosen density. Any remaining gravity signal that correlates with topography is providing geological information. If the objective is to produce a gravity map with minimal topographic signal, then a regionally variable density correction is a means of compensating for this effect. In this paper, we demonstrate how to apply a spatially variable density correction using ground gravity and airborne gravity gradiometry data for the geologically complex Bathurst Mining Camp, northern New Brunswick, Canada. Ground gravity and airborne full tensor gravity gradiometry measurements are subdivided into a series of domains on the basis of the underlying tectonostratigraphic group. Terrain and Bouguer corrections are calculated for each domain using representative density values obtained from drill core and surface sampling throughout the Bathurst Mining Camp. The output from the spatially variable density correction is then compared with previous maps. Overall, the differences are subtle, but the spatially variably density allows for isolated anomalies to be better resolved.

Adaptive multinary inversion of gravity and gravity gradiometry data

We have developed a novel approach for inversion of gravity and gravity gradiometry data based on multinary transformation of the model parameters. This concept is a generalization of binary density inversion to the models described by any number of discrete model parameters. The multinary inversion makes it possible to explicitly exploit the sharp contrasts of the density between the host media and anomalous targets in the inversion of gravity and gravity gradiometry data. In the framework of the multinary inversion method, we use the given values of density and error functions to transform the density distribution into the desired step-function distribution. To accommodate a possible deviation of the densities from the fixed discrete values, we develop an adaptive technique for selecting the corresponding standard deviations, guided by the inversion process. The novel adaptive multinary inversion algorithm is demonstrated to be effective in determining the shape, location, and densities of the anomalous targets. We find that this method can be effectively applied for the inversion of the full tensor gravity gradiometry (FTG) data computer simulated for the SEG salt density model and for the field FTG data collected in the Nordkapp Basin, Barents Sea.

Feasibility and Limitations of Void Detection Using Gravity Gradiometry

Detecting and characterizing near-surface voids is a long-standing problem in near-surface geophysics primarily because of the low signal-to-noise ratio due to the typically small sizes of these targets. Anticipated advances in gravity gradiometry instrumentation and data acquisition may provide the improved resolution required to address these targets. In this paper, we investigate void detection using simulated full tensor gravity gradiometry data. We show through numerical simulations that low-altitude gravity gradiometry can observe signals from voids well above the modern instrument noise level. We develop a practical detection algorithm to determine the tunnel orientation and its location in the subsurface. The algorithm first finds the tunnel orientation through a tensor rotation and then solves for the tunnel location in the subsurface based on the directional vectors obtained from the rotated tensor data. We use this algorithm to study the feasibility and limitations of the gravity gradiometry technique in void detection. We conclude that the method can be effective in many practical scenarios.

Three-dimensional geology from potential field geophysics: Applications to Bathurst Mining Camp, Eastern Canada

SUMMARY Interpretation methods and tools for geophysics datasets continue to evolve. Advances in clustering algorithms, the use of implicit functions to create 3D surfaces, new algorithms to estimate source depths and dips, and the availability of clever computational geometry libraries, contribute to the discipline of potential field interpretation techniques, allowing for a much more explicit statement of implied 3D description. While traditional scalar measures of potential fields have benefited from applying new ideas, perhaps more exciting is the reduction in ambiguity imposed from gradient measurement when used as the basis for field interpretation. Full tensor gravity gradiometry in particular, allows for 2D fault dip and throw calculations. Direct detection of high density bodies and faults via state-of-the-art gravity gradiometry is now a reality. Bodies greater than 200m in lateral extent are detectable. Implicit 3D structural geology modelling techniques derived from gravity curvature attributes of the observed gravity field present a leading edge technique for defining structurally controlled near surface geology geometry. A demonstration from the Bathurst camp dataset is given.

Full tensor gravity gradiometry data inversion: Performance analysis of parallel computing algorithms

We apply reweighted inversion focusing to full tensor gravity gradiometry data using message-passing interface (MPI) and compute unified device architecture (CUDA) parallel computing algorithms, and then combine MPI with CUDA to formulate a hybrid algorithm. Parallel computing performance metrics are introduced to analyze and compare the performance of the algorithms. We summarize the rules for the performance evaluation of parallel algorithms. We use model and real data from the Vinton salt dome to test the algorithms. We find good match between model and real density data, and verify the high efficiency and feasibility of parallel computing algorithms in the inversion of full tensor gravity gradiometry data.

Fast Density Inversion Solution for Full Tensor Gravity Gradiometry Data

We modify the classical preconditioned conjugate gradient method for full tensor gravity gradiometry data. The resulting parallelized algorithm is implemented on a cluster to achieve rapid density inversions for various scenarios, overcoming the problems of computation time and memory requirements caused by too many iterations. The proposed approach is mainly based on parallel programming using the Message Passing Interface, supplemented by Open Multi-Processing. Our implementation is efficient and scalable, enabling its use with large-scale data. We consider two synthetic models and real survey data from Vinton Dome, US, and demonstrate that our solutions are reliable and feasible.

The role of pre-existing Precambrian structures in rift evolution: The Albertine and Rhino grabens, Uganda

We integrated Shuttle Radar Topography Mission (SRTM) Digital Elevation Models (DEM), airborne magnetic, radiometric and three-dimensional Full Tensor Gravity Gradiometry (3D-FTG) data to investigate the role of Precambrian structures in the evolution of the largely amagmatic Miocene–Recent aged Albertine and Rhino grabens in Uganda. These grabens represent the northern segment of the Western Branch of the East African Rift System (EARS). The two NE-trending grabens are connected by a right-stepping transfer zone and they extend within the Archean–Paleoproterozoic Northeast Congo block which represents the northeastern extension of the Congo craton. Our results show the following and highlight the importance of pre-existing structures in the evolution of continental rift systems: (1) The NE-extent of the Albertine full-graben is controlled by NE-trending Precambrian fabric and the graben terminates at its northeastern end when it encounters a multiply folded Precambrian basement terrain with poorly-developed NW-trending structural grain. Additionally, the northeastern termination of the Albertine graben coincides with the presence of NW-trending right-stepping high-density bodies within the Precambrian terrain. (2) The transfer zone between the Albertine and Rhino grabens is controlled by NE-trending Precambrian structures which might have facilitated the development of relay ramp faults. (3) Strain localization within the better-developed southeastern border fault of the Rhino half-graben is facilitated by the presence of Precambrian structures better aligned in a NE-direction in the southeastern part of the basin compared to its northwestern part. (4) Further to the northeast, the Rhino graben is segmented and transitions into a narrower ENE-trending half-graben with a better-developed border fault on its northwestern side. This segmentation coincides with the presence of N-trending Precambrian structures. (5) The Rhino graben terminates farther northeast against the NW-trending Precambrian Aswa shear zone; a prominent structure with complex, but generally NW-trending fabric.

Defining a deep fault network for Australia, using 3D “worming”

Defining a deep fault network for Australia, using 3D 'worming'. The original work on multi-scale edge detection ('worming') done by Hornby et al. in 1999 has become increasingly popular as a starting point for rapid interpretation using potential field data. Both gravity and magnetic grids are used. Several improvements have been made in the following years such that it is routine to capture points, 'worms' and linear features in a form suitable for overlay in GIS packages. There are important extensions which have recently been completed: (a). support for gravity gradiometry using the measured gradients directly (b). creation of interface and foliation data implying 3D surfaces that are geolocated. (c). adaption of Euler deconvolution techniques to both full tensor gravity gradiometry (FTG) and a best located method for scalar measures. This paper reports on these new extensions applied to the Australian gravity grid and on issues arising from these efforts to improve/generalise the worming technology and get 3D contacts that can be interpreted. This large scale gravity dataset, with a high density of near surface features, contains far too many gradients interpreted as faults, so a thinning strategy is required to find the significant deep crustal faults. These deep crustal faults require proper attribution of depth, dip direction and dip, and also extent constraints. For the FTG case, the largest 3-survey merge attempted to date has occurred with data acquired in Kenya. The new and improved 3D worming has been applied in the context of rapidly defining the horst/graben layouts in an active rift zone. Some discussion and illustration of the present problems of how to build, merge and manage a 3D fault network, where the issues of faults terminating on other faults and which fault cuts which, will be shown and discussed.

Multinary Inversion for Tunnel Detection

We introduce multinary inversion to explicitly exploit the physical property contrasts between different objects and their host medium, e.g., between air-filled tunnels and their surrounding earth. Conceptually, multinary inversion is a generalization of binary inversion to multiple physical properties. However, unlike existing realizations of binary inversion which are solved using stochastic optimization methods, our realization of multinary inversion can be solved using deterministic optimization methods. This is significant as the method can be applied to both linear and nonlinear operators and easily extends to joint inversion of multimodal geophysical data. Using synthetic models of full-tensor gravity gradiometry data, multinary inversion is demonstrated to be robust for tunnel detection relative to the presence of significant geological noise.

Full tensor CSEM and MT for subsalt structural imaging in the Red Sea: Implications for seismic and electromagnetic integration

The mapping of complex salt, subsalt sediments, and basement structures in the Red Sea was addressed through the integration of coincident high-resolution wide-azimuth (WAZ) 3D seismic data, full tensor gravity gradiometry (FTG), and MT/CSEM techniques. The data acquisition was designed to enable advanced multi-geophysical integration schemes to image the subsalt geologic structures. Multi-offset, multicomponent electromagnetic measurements were recorded for both MT and CSEM with overlapping frequency bands. The analysis of the data and the preliminary 3D inversion results indicate that the two methods provide coherent information for the evaporitic overburden and the subsalt sediment sections. In addition, the MT data also show sensitivity to the deep basement structures. The obtained resistivity distributions strongly correlate with imaged seismic events from the 3D migrated seismic volumes and with the lateral- and vertical-velocity variations in the salt and presalt sections. These data suggest that the acquired electromagnetic data set can support the interval velocity-depth model building in areas of low seismic sensitivity such as the intrasalt and subsalt sections.

Hybrid modelling of gravity, gravity gradients and magnetic fields

ABSTRACTModern 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.

Modelagem numérica e validação de dados tensoriais de aerogradiometria gravimétrica 3D-FTG

Mineralizações de óxido de ferro são geralmente controladas por estruturas crustais e locais, como zonas de cisalhamento, zonas de falha e contatos litológicos. O sistema Air-FTG (Airborne Full Tensor Gravity Gradiometry) é atualmente a única tecnologia aérea existente capaz de medir o tensor total gradiente de gravidade associado a estas mineralizações. Ele faz medidas em tempo real do gradiente do campo gravitacional em três direções ortogonais e ao mesmo tempo corrige a orientação e as acelerações da aeronave. Cada uma destas medidas ú relacionada a contrastes de densidade ou a geometria de corpos superficiais discretos. O objetivo deste artigo é implementar um algoritmo numérico capaz de calcular as cinco componentes independentes do tensor e utilizar o conhecimento adquirido com ele para auxiliar na interpretaçao dos dados reais e na validação do método. A aquisição de dados com o sistema Air-FTG foi realizada no Quadrilátero Ferrífero, no estado de Minas Gerais, Brasil, tendo como objetivo mapear os corpos de hematita compacta. Foi aplicado um procedimento completo para processamento dos dados de gravimetria terrestre com o intuito de compará-los com os dados reais de FTG. Os resultados indicam, juntamente com a interpretação conjunta dos modelos geológicos, que as componentes do tensor comprovam a alta resolução do sistema, permitindo a identificação de corpos de minério de ferro com grande precisão. Os resultados mostram também que as componentes do sistema FTG conseguem detectar corpos mineralizados mais próximos da superfície, além de estruturas geológicas como lineamentos, extremidades, cantos e, como conseqüência, a forma dos corpos. Conclui-se com base nos resultados do levantamento adquirido com a plataforma Air-FTG que este sistema pode prover informações mais detalhadas dos alvos do que a gravimetria terrestre convencional.

Planejamento e controle de qualidade de dados de gradiometria gravimétrica 3D-FTG

O presente trabalho de pesquisa faz uma descricao detalhada das fases do planejamento e controle de qualidade dos dados de 3D-FTG (Full Tensor Gravity Gradiometry). Apresenta as caracteristicas do sistema FTG, controle de qualidade dos dados durante o voo e o resultado do controle de qualidade dos dados adquiridos atraves da analise da relacao sinal ruido e dos modelos sinteticos de cada componente do tensor do gradiente de gravidade. Mineralizacoes de oxido de ferro sao largamente controladas por estruturas crustais e locais, como zonas de cisalhamento, zonas de falha e contatos litologicos. Um controle cartografico preciso destas estruturas e critico para se encontrar concentracoes consideraveis e economicas destes tipos de depositos. O Air-FTG (Airborne Full Tensor Gravity Gradiometry) e atualmente a unica tecnologia aerea existente capaz de medir o tensor total gradiente de gravidade e pode ser usado tanto para levantamentos detalhados como regionais. O sistema aereo FTG faz medidas em tempo real do gradiente do campo gravitacional em tres direcoes ortogonais e ao mesmo tempo corrige a orientacao e as aceleracoes da aeronave. A aquisicao de dados com o sistema Air-FTG foi realizada no Quadrilatero Ferrifero, no estado de Minas Gerais, Brasil.

Tensor deconvolution: A method to locate equivalent sources from full tensor gravity data

We present a method dedicated to the interpretation of full tensor (gravity) gradiometry (FTG) data called tensor deconvolution. It is especially designed to benefit from the simultaneous use of all the FTG components and of the gravity field. In particular, it uses tensor scalar invariants as a basis for source location. The invariant expressions involve all of the independent components of the tensor. This method is a tensor analog of Euler deconvolution, but has the following advantages compared to the conventional Euler deconvolution method: (1) It provides a solution at every observation point, without the use of a sliding window. (2) It determines the structural index automatically; as a consequence, the structural index follows the variations of the field morphology. (3) It uses all components of the measured full gradient tensor and gravity field, thus reducing errors caused by random noise. It is based on scalar invariants that are by nature insensitive to the orientation of the measuring device. We tested our method on both noise-free and noise-contaminated data. These tests show that tensor solutions cluster in the vicinity of the center of causative bodies, whereas Euler solutions better outline their edges. Hence, these methods should be combined for improved contouring and depth estimation. In addition, we use a clustering method to improve the selection of solutions, which proves advantageous when data are noisy or when signals from close causative bodies interfere.