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TechnoImaging

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Cox L.H.,Montana Tech of the University of Montana | Wilson G.A.,TechnoImaging | Zhdanov M.S.,TechnoImaging | Zhdanov M.S.,University of Utah
Exploration Geophysics | Year: 2010

It is often argued that 3D inversion of entire airborne electromagnetic (AEM) surveys is impractical, and that 1D methods provide the only viable option for quantitative interpretation. However, real geological formations are 3D by nature and 3D inversion is required to produce accurate images of the subsurface. To that end, we show that it is practical to invert entire AEM surveys to 3D conductivity models with hundreds of thousands if not millions of elements. The key to solving a 3D AEM inversion problem is the application of a moving footprint approach. We have exploited the fact that the area of the footprint of an AEM system is significantly smaller than the area of an AEM survey, and developed a robust 3D inversion method that uses a moving footprint. Our implementation is based on the 3D integral equation method for computing data and sensitivities, and uses the re-weighted regularised conjugate gradient method for minimising the objective functional. We demonstrate our methodology with the 3D inversion of AEM data acquired for salinity mapping over the Bookpurnong Irrigation District in South Australia. We have inverted 146 line km of RESOLVE data for a 3D conductivity model with ∼310000 elements in 45min using just five processors of a multi-processor workstation. © 2010 ASEG.


Zhdanov M.S.,TechnoImaging | Zhdanov M.S.,University of Utah | Liu X.,University of Utah
Geophysical Journal International | Year: 2013

Fundamental to complex analysis is the Cauchy integral theorem, and the derivation of Cauchytype integrals. For over 40 yr, Cauchy-type integrals have been used to describe analytical continuation, establish the location of singular points, and study non-single-valued solutions of inverse problems in 2-D potential field theory. In this paper, we revive this interesting and fundamental area of potential field theory to introduce Cauchy-type integrals for 3-D potential fields. In particular, we show how one can evaluate the gravity and gravity gradiometry responses of 3-D bodies as surface integrals over arbitrary volumes that may contain spatially variable densities. This method of 3-D spatial-domain potential field modelling has never been realized before, and we show how it is particularly suited to the terrain correction of airborne gravity and gravity gradiometry data. The surface integrals are evaluated numerically on a topographically conforming grid with a resolution equal to the digital elevation model. Thus, our method directly avoids issues related to prismatic discretization of the digital elevation model and their associated volume integration which may result in inappropriate discretization of the earth model, particularly for regions of rugged topography.We demonstrate our method with a model study for airborne gravity gradiometry data simulated for a next-generation 1 Eö√Hz system over the Kauring test site in Western Australia. © The Authors 2013. Published by Oxford University Press on behalf of The Royal Astronomical Society.


Zhdanov M.S.,University of Utah | Liu X.,University of Utah | Wilson G.,TechnoImaging
First Break | Year: 2010

The geological interpretation of gravity gradiometry data is challenging. With the exception of the vertical gradient, maps of the different gravity gradients are often complicated and cannot be directly correlated with geological structure. 3D inversion has been the only practical tool for the quantitative interpretation of gravity gradiometry data. However, it is a complicated and time-consuming procedure that is very dependent on the initial 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 its application for rapid 3D imaging of entire gravity gradiometry surveys. This method is based on the direct integral transformation of the observed gravity gradients into a subsurface density distribution that can be used for interpretation, or as an initial model for subsequent 3D regularized inversion. We present a case study for the interpretation of gravity gradiometry data acquired in the Nordkapp Basin. We find agreement between the results obtained from potential field migration and those obtained from 3D regularized inversion, and show that the migration result are comparable to smooth inversion. For regional-size datasets, runtimes for migration are in the order of minutes compared to hours for inversion. © 2010 EAGE.


Zhdanov M.S.,University of Utah | Cai H.,University of Utah | Wilson G.A.,TechnoImaging
Geophysical Journal International | Year: 2012

We introduce a new method of rapid interpretation of magnetic vector and tensor field data, based on ideas of potential field migration which extends the general principles of seismic and electromagnetic migration to potential fields. 2-D potential field migration represents a direct integral transformation of the observed magnetic fields into a subsurface susceptibility distribution, which can be used for interpretation or as an a priori model for subsequent regularized inversion. Potential field migration is very stable with respect to noise in the observed data because the transform is reduced to the downward continuation of a well-behaved analytical function. We present case studies for imaging of SQUID-based magnetic tensor data acquired over a magnetite skarn at Tallawang, Australia. The results obtained from magnetic tensor field migration agree very well with both Euler deconvolution and the known geology. © 2012 The Authors Geophysical Journal International © 2012 RAS.


Cox L.H.,TechnoImaging | Wilson G.A.,TechnoImaging | Zhdanov M.S.,University of Utah
Geophysics | Year: 2012

Time-domain airborne surveys gather hundreds of thousands of multichannel, multicomponent samples. The volume of data and other complications have made 1D inversions and transforms the only viable method to interpret these data, in spite of their limitations. We have developed a practical methodology to perform full 3D inversions of entire time- or frequency-domain airborne electromagnetic (AEM) surveys. Our methodology is based on the concept of a moving footprint that reduces the computation requirements by several orders of magnitude. The 3D AEM responses and sensitivities are computed using a frequency-domain total field integral equation technique. For time-domain AEM responses and sensitivities, the frequency-domain responses and sensitivities are transformed to the time domain via a cosine transform and convolution with the system waveform. We demonstrate the efficiency of our methodology with a model study relevant to the Abitibi greenstone belt and a case study from the Reid-Mahaffy test site in Ontario, Canada, which provided an excellent practical opportunity to compare 3D inversions for different AEM systems. In particular, we compared 3D inversions of VTEM-35 (time-domain helicopter), MEGATEM II (time-domain fixed-wing), and DIGHEM (frequency-domain helicopter) data. Our comparison showed that each system is able to image the conductive overburden and to varying degrees, detect and delineate the bedrock conductors, and, as expected, that the DIGHEM system best resolved the conductive overburden, whereas the time-domain systems most clearly delineated the bedrock conductors. Our comparisons of the helicopter and fixed-wing time-domain systems revealed that the often-cited disadvantages of a fixed-wing system (i.e., response asymmetry) are not inherent in the system, but rather reflect a limitation of the 1D interpretation methods used to date. © 2012 Society of Exploration Geophysicists.


Zhdanov M.S.,University of Utah | Cox L.H.,TechnoImaging
IEEE Geoscience and Remote Sensing Letters | Year: 2013

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. © 2004-2012 IEEE.


Wilson G.A.,TechnoImaging | Cox L.H.,TechnoImaging | Cuma M.,University of Utah | Zhdanov M.S.,University of Utah
Leading Edge | Year: 2012

Today's mineral exploration is driven by the simple fact that discovery rates have not kept pace with the depletion of existing reserves. To improve discovery rates, there is an industry-wide consensus on the need to increase the "discovery space" by exploring under cover and to greater depths. This attracts increased risks which may be mitigated by improved targeting. To do this, mining geophysics needs to shift toward 3D geological models founded upon improved petrophysical understanding and geophysical inversion. Regardless of the inversion methodology used, all geological constraints manifest themselves in the user's prejudice of an a priori model, upper and lower bounds, and choice of regularization. However, the practice of geologically constrained inversion is not the major problem needing to be addressed. It is known (and accepted) that geology is inherently 3D, and is a result of complex, overlapping processes related to genesis, metamorphism, deformation, alteration and/or weathering. Yet, the mining geophysics community to date has not fully accepted that geophysics should also be 3D, and most often relies on qualitative analysis, 1D inversion, and deposit-scale 2D or 3D inversion. There are many reasons for this unfortunate deficiency, not the least of which has been the lack of capacity of existing 3D inversion algorithms. To date, these have not been able to invert entire surveys with sufficient resolution in sufficient time to practically affect exploration decisions. © 2012 Society of Exploration Geophysicists.


Zhdanov M.S.,TechnoImaging | Zhdanov M.S.,University of Utah | Liu X.,University of Utah | Wilson G.A.,TechnoImaging | Wan L.,University of Utah
Geophysical Prospecting | Year: 2011

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. © 2011 European Association of Geoscientists & Engineers.


Cuma M.,University of Utah | Wilson G.A.,TechnoImaging | Zhdanov M.S.,TechnoImaging | Zhdanov M.S.,University of Utah
Geophysical Prospecting | Year: 2012

Inversion of gravity and/or magnetic data attempts to recover the density and/or magnetic susceptibility distribution in a 3D earth model for subsequent geological interpretation. This is a challenging problem for a number of reasons. First, airborne gravity and magnetic surveys are characterized by very large data volumes. Second, the 3D modelling of data from large-scale surveys is a computationally challenging problem. Third, gravity and magnetic data are finite and noisy and their inversion is ill posed so regularization must be introduced for the recovery of the most geologically plausible solutions from an infinite number of mathematically equivalent solutions. These difficulties and how they can be addressed in terms of large-scale 3D potential field inversion are discussed in this paper. Since potential fields are linear, they lend themselves to full parallelization with near-linear scaling on modern parallel computers. Moreover, we exploit the fact that an instrument's sensitivity (or footprint) is considerably smaller than the survey area. As multiple footprints superimpose themselves over the same 3D earth model, the sensitivity matrix for the entire earth model is constructed. We use the re-weighted regularized conjugate gradient method for minimizing the objective functional and incorporate a wide variety of regularization options. We demonstrate our approach with the 3D inversion of 1743 line km of FALCON gravity gradiometry and magnetic data acquired over the Timmins district in Ontario, Canada. Our results are shown to be in good agreement with independent interpretations of the same data. © 2012 European Association of Geoscientists & Engineers.


Zhdanov M.S.,University of Utah | Gribenko A.,University of Utah | Wilson G.,TechnoImaging
Geophysical Research Letters | Year: 2012

We introduce a new approach to the joint inversion of multimodal geophysical data using Gramian spaces of model parameters and Gramian constraints, computed as determinants of the corresponding Gram matrices of the multimodal model parameters and/or their attributes. We demonstrate that this new approach is a generalized technique that can be applied to the simultaneous joint inversion of any number and combination of geophysical datasets. Our approach includes as special cases those extant methods based on correlations and/or structural constraints of the multimodal model parameters. As an illustration of this new approach, we present a model study relevant to exploration under cover for iron oxide copper-gold (IOCG) deposits, and demonstrate how joint inversion of gravity and magnetic data is able to recover alteration associated with IOCG mineralization. Copyright 2012 by the American Geophysical Union.

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