Robust 3D gravity gradient inversion by planting anomalous densities

Geophysics ◽  
2012 ◽  
Vol 77 (4) ◽  
pp. G55-G66 ◽  
Author(s):  
Leonardo Uieda ◽  
Valéria C. F. Barbosa
Keyword(s):  
Iterative Algorithm ◽  
Iron Ore ◽  
Density Contrast ◽  
Southeastern Brazil ◽  
Airborne Gravity ◽  
Gravity Gradient ◽  
Inversion Method ◽  
Multiple Sources ◽  
Sensitivity Matrix ◽  
Current Estimate

We have developed a new gravity gradient inversion method for estimating a 3D density-contrast distribution defined on a grid of rectangular prisms. Our method consists of an iterative algorithm that does not require the solution of an equation system. Instead, the solution grows systematically around user-specified prismatic elements, called “seeds,” with given density contrasts. Each seed can be assigned a different density-contrast value, allowing the interpretation of multiple sources with different density contrasts and that produce interfering signals. In real world scenarios, some sources might not be targeted for the interpretation. Thus, we developed a robust procedure that neither requires the isolation of the signal of the targeted sources prior to the inversion nor requires substantial prior information about the nontargeted sources. In our iterative algorithm, the estimated sources grow by the accretion of prisms in the periphery of the current estimate. In addition, only the columns of the sensitivity matrix corresponding to the prisms in the periphery of the current estimate are needed for the computations. Therefore, the individual columns of the sensitivity matrix can be calculated on demand and deleted after an accretion takes place, greatly reducing the demand for computer memory and processing time. Tests on synthetic data show the ability of our method to correctly recover the geometry of the targeted sources, even when interfering signals produced by nontargeted sources are present. Inverting the data from an airborne gravity gradiometry survey flown over the iron ore province of Quadrilátero Ferrífero, southeastern Brazil, we estimated a compact iron ore body that is in agreement with geologic information and previous interpretations.

Lithologic characterization using airborne gravity gradient and aeromagnetic data for mineral exploration: A case study in the Quadrilátero Ferrífero, Brazil

2015 ◽  
Vol 3 (2) ◽  
pp. SL1-SL13 ◽  
Author(s):  
Cericia Martinez ◽  
Yaoguo Li
Keyword(s):  
Iron Ore ◽  
Physical Property ◽  
Density Contrast ◽  
Iron Formation ◽  
Magnetic Data ◽  
Airborne Gravity ◽  
Gravity Gradient ◽  
Contrast Model ◽  
Ore Bodies ◽  
Quadrilátero Ferrífero

We present a study on utilizing airborne gravity gradient and magnetic data to characterize an iron ore formation in Minas Gerais, Brazil. The target iron ore bodies have a distinctly high density contrast and produce well-defined anomalies in airborne gravity gradiometry data. The high-grade hematite iron ores are associated with low and moderate susceptibility, making magnetic data useful in distinguishing potential ore bodies from the host iron formation. The airborne gravity gradient and magnetic data over part of the Gandarela Syncline iron formation in the Quadrilátero Ferrífero are independently inverted to obtain a 3D susceptibility and density contrast model. These detailed 3D physical property distributions of subsurface features are then used for geologic characterization and interpretation purposes through lithologic associations. We outline two approaches to link the two physical property distributions and identify representative geologic units in the study area. The geologic units are then organized into a 3D lithology model to help characterize subsurface geologic structure and ore distribution. The lithologic models provide an intuitive representation of the geology and can assist in future exploration plans or in assessment of resource distribution and quality. Our study demonstrates that such approaches are feasible on the deposit scale.

scholarly journals AIRBORNE GRAVITY GRADIOMETRY – DATA PROCESSING AND INTERPRETATION

2013 ◽  
Vol 31 (3) ◽  
pp. 427 ◽  
Author(s):  
Dionisio Uendro Carlos ◽  
Marco Antonio Braga ◽  
Henry F. Galbiatti ◽  
Wanderson Roberto Pereira
Keyword(s):  
Iron Ore ◽  
A Priori ◽  
Synthetic Data ◽  
Real Data ◽  
Geological Mapping ◽  
Airborne Gravity ◽  
Gravity Gradient ◽  
Gravity Gradiometry ◽  
Quadrilátero Ferrífero ◽  
Airborne Gravity Gradiometry

ABSTRACT. This paper discusses some processing techniques (all codes were implemented with open source software) developed for airborne gravity gradient systems, aiming at outlining geological features by applying mathematical formulations based on the potential field properties and its breakdown into gradiometric tensors. These techniques were applied to both synthetic and real data. These techniques applied to synthetic data allow working in a controlled environment, under- standing the different processing results and establishing a comparative parameter. These methodologies were applied to a survey area of the Quadrilátero Ferrífero to map iron ore targets, resulting in a set of very helpful and important information for geological mapping activities and a priori information for inversion geophysical models.Keywords: processing, airborne gravity gradiometry, iron ore exploration, FTG system, FALCON system. RESUMO. Neste trabalho apresentamos algumas técnicas de processamento (todos os códigos foram implementados em softwares livres) desenvolvidas para aplicação aos dados de aerogradiometria gravimétrica. Os processamentos foram aplicados tanto a dados sintéticos como a dados reais. A aplicação a dados sintéticos permite atuar em um ambiente controlado e entender o padrão resultante de cada processamento. Esses mesmos processamentos foram aplicados em uma área do Quadrilátero Ferrífero para o mapeamento de minério de ferro. Todos os resultados desses processamentos são muito úteis e importantes para o mapeamento geológicoe como informação a priori para modelos de inversão geofísica.Palavras-chave: processamento, dados de aerogradiometria gravimétrica, exploração de minério de ferro, sistema FTG, sistema FALCON.

3D inversion of airborne gravity gradiometry data in mineral exploration: A case study in the Quadrilátero Ferrífero, Brazil

Geophysics ◽  
2013 ◽  
Vol 78 (1) ◽  
pp. B1-B11 ◽  
Author(s):  
Cericia Martinez ◽  
Yaoguo Li ◽  
Richard Krahenbuhl ◽  
Marco Antonio Braga
Keyword(s):  
Iron Ore ◽  
Mineral Exploration ◽  
Density Contrast ◽  
Airborne Gravity ◽  
Gravity Gradiometry ◽  
Inversion Algorithm ◽  
3D Inversion ◽  
Ore Bodies ◽  
Airborne Gravity Gradiometry

We present a case study of applying 3D inversion of gravity gradiometry data to iron ore exploration in Minas Gerais, Brazil. The ore bodies have a distinctly high-density contrast and produce well-defined anomalies in airborne gravity gradiometry data. We have carried out a study to apply 3D inversion to a [Formula: see text] subarea of data from a larger survey to demonstrate the utility of such data and associated inversion algorithm in characterizing the deposit. We examine multiple density contrast models obtained by first inverting [Formula: see text]; then [Formula: see text], [Formula: see text], and [Formula: see text] jointly; and finally all five independent components to understand the information content in different data components. The commonly discussed [Formula: see text] component is sufficient to produce geologically reasonable and interpretable results, while including additional components involving horizontal derivatives increases the resolution of the recovered density model and improves the ore delineation. We show that gravity gradiometry data can be used to delineate the iron ore formation within this study area.

scholarly journals Application of curvatures and Poisson’s relation to airborne gravity gradient data in oil exploration

2013 ◽  
Vol 2013 (1) ◽  
pp. 1-4
Author(s):  
Carlos Cevallos ◽  
Peter Kovac ◽  
Sharon J. Lowe
Keyword(s):  
Airborne Gravity ◽  
Gravity Gradient ◽  
Oil Exploration

Evaluating gravity gradient components based on a reweighted inversion method

2019 ◽  
Vol 16 (4) ◽  
pp. 491-506
Author(s):  
Ju-Liang Cao ◽  
Peng-Bo Qin ◽  
Zhen-Long Hou
Keyword(s):  
Gravity Gradient ◽  
Inversion Method

Trace metals in Rio Doce sediments before and after the collapse of the Fundão iron ore tailing dam, Southeastern Brazil

Chemosphere ◽  
2021 ◽  
Vol 262 ◽  
pp. 127879 ◽  
Author(s):  
Eduardo Baudson Duarte ◽  
Mirna Aparecida Neves ◽  
Fabricia Benda de Oliveira ◽  
Marx Engel Martins ◽  
Carlos Henrique Rodrigues de Oliveira ◽  
...  
Keyword(s):  
Trace Metals ◽  
Iron Ore ◽  
Southeastern Brazil ◽  
Before And After ◽  
Tailing Dam ◽  
Iron Ore Tailing

An efficient data‐subspace inversion method for 2-D magnetotelluric data

Geophysics ◽  
2000 ◽  
Vol 65 (3) ◽  
pp. 791-803 ◽  
Author(s):  
Weerachai Siripunvaraporn ◽  
Gary Egbert
Keyword(s):  
Significant Loss ◽  
Inversion Method ◽  
Data Sets ◽  
Reduced Basis ◽  
Sensitivity Matrix ◽  
Approximate Methods ◽  
Magnetotelluric Data ◽  
Data Set ◽  
Data Space ◽  
Occam’S Inversion

There are currently three types of algorithms in use for regularized 2-D inversion of magnetotelluric (MT) data. All seek to minimize some functional which penalizes data misfit and model structure. With the most straight‐forward approach (exemplified by OCCAM), the minimization is accomplished using some variant on a linearized Gauss‐Newton approach. A second approach is to use a descent method [e.g., nonlinear conjugate gradients (NLCG)] to avoid the expense of constructing large matrices (e.g., the sensitivity matrix). Finally, approximate methods [e.g., rapid relaxation inversion (RRI)] have been developed which use cheaply computed approximations to the sensitivity matrix to search for a minimum of the penalty functional. Approximate approaches can be very fast, but in practice often fail to converge without significant expert user intervention. On the other hand, the more straightforward methods can be prohibitively expensive to use for even moderate‐size data sets. Here, we present a new and much more efficient variant on the OCCAM scheme. By expressing the solution as a linear combination of rows of the sensitivity matrix smoothed by the model covariance (the “representers”), we transform the linearized inverse problem from the M-dimensional model space to the N-dimensional data space. This method is referred to as DASOCC, the data space OCCAM’s inversion. Since generally N ≪ M, this transformation by itself can result in significant computational saving. More importantly the data space formulation suggests a simple approximate method for constructing the inverse solution. Since MT data are smooth and “redundant,” a subset of the representers is typically sufficient to form the model without significant loss of detail. Computations required for constructing sensitivities and the size of matrices to be inverted can be significantly reduced by this approximation. We refer to this inversion as REBOCC, the reduced basis OCCAM’s inversion. Numerical experiments on synthetic and real data sets with REBOCC, DASOCC, NLCG, RRI, and OCCAM show that REBOCC is faster than both DASOCC and NLCG, which are comparable in speed. All of these methods are significantly faster than OCCAM, but are not competitive with RRI. However, even with a simple synthetic data set, we could not always get RRI to converge to a reasonable solution. The basic idea behind REBOCC should be more broadly applicable, in particular to 3-D MT inversion.

A local level-set method for 3D inversion of gravity-gradient data

Geophysics ◽  
2015 ◽  
Vol 80 (1) ◽  
pp. G35-G51 ◽  
Author(s):  
Wangtao Lu ◽  
Jianliang Qian
Keyword(s):  
Inverse Problem ◽  
Level Set Method ◽  
Level Set ◽  
Local Level ◽  
Density Contrast ◽  
Gravity Gradient ◽  
Gravity Center ◽  
Level Set Function ◽  
Local Level Set ◽  
Set Function

We have developed a local level-set method for inverting 3D gravity-gradient data. To alleviate the inherent nonuniqueness of the inverse gradiometry problem, we assumed that a homogeneous density contrast distribution with the value of the density contrast specified a priori was supported on an unknown bounded domain [Formula: see text] so that we may convert the original inverse problem into a domain inverse problem. Because the unknown domain [Formula: see text] may take a variety of shapes, we parametrized the domain [Formula: see text] by a level-set function implicitly so that the domain inverse problem was reduced to a nonlinear optimization problem for the level-set function. Because the convergence of the level-set algorithm relied heavily on initializing the level-set function to enclose the gravity center of a source body, we applied a weighted [Formula: see text]-regularization method to locate such a gravity center so that the level-set function can be properly initialized. To rapidly compute the gradient of the nonlinear functional arising in the level-set formulation, we made use of the fact that the Laplacian kernel in the gravity force relation decayed rapidly off the diagonal so that matrix-vector multiplications for evaluating the gradient can be accelerated significantly. We conducted extensive numerical experiments to test the performance and effectiveness of the new method.

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