scholarly journals Recovering Magnetization of Rock Formations by Jointly Inverting Airborne Gravity Gradiometry and Total Magnetic Intensity Data

Minerals ◽  
2021 ◽  
Vol 11 (4) ◽  
pp. 366
Author(s):  
Michael Jorgensen ◽  
Michael S. Zhdanov
Keyword(s):  
Joint Inversion ◽  
Magnetization Vector ◽  
Mineral Deposit ◽  
Airborne Gravity ◽  
Earth Model ◽  
Magnetic Intensity ◽  
Gravity Gradiometry ◽  
Rock Formations ◽  
Magnetic Inversion ◽  
Airborne Gravity Gradiometry

Conventional 3D magnetic inversion methods are based on the assumption that there is no remanent magnetization, and the inversion is run for magnetic susceptibility only. This approach is well-suited to targeting mineralization; however, it ignores the situation where the direction of magnetization of the rock formations is different from the direction of the induced magnetic field. We present a novel method of recovering a spatial distribution of magnetization vector within the rock formation based on joint inversion of airborne gravity gradiometry (AGG) and total magnetic intensity (TMI) data for a shared earth model. Increasing the number of inversion parameters (the scalar components of magnetization vector) results in a higher degree of non-uniqueness of the inverse problem. This increase of non-uniqueness rate can be remedied by joint inversion based on (1) Gramian constraints or (2) joint focusing stabilizers. The Gramian constraints enforce shared earth structure through a correlation of the model gradients. The joint focusing stabilizers also enforce the structural similarity and are implemented using minimum support or minimum gradient support approaches. Both novel approaches are applied to the interpretation of the airborne data collected over the Thunderbird V-Ti-Fe deposit in Ontario, Canada. By combining the complementary AGG and TMI data, we generate jointly inverted shared earth models that provide a congruent image of the rock formations hosting the mineral deposit.

3D inversion of airborne gravity gradiometry data for the Budgell Harbour Stock, Newfoundland: A case history using a probabilistic approach

Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. B269-B284 ◽  
Author(s):  
Meixia Geng ◽  
J. Kim Welford ◽  
Colin G. Farquharson ◽  
Alexander L. Peace
Keyword(s):  
Joint Inversion ◽  
Probabilistic Approach ◽  
Stable Solution ◽  
Airborne Gravity ◽  
Inversion Method ◽  
Gravity Gradiometry ◽  
3D Inversion ◽  
Long Wavelength ◽  
Text Model ◽  
Airborne Gravity Gradiometry

We have studied the Mesozoic Budgell Harbour Stock, a gabbroic intrusion in north-central Newfoundland, Canada, using 3D inversion of airborne gravity gradiometry data based on a probabilistic inversion method. Significantly, differences were observed between the results when inverting the single [Formula: see text] component and when inverting the 5C combination. We also found that the [Formula: see text] model failed to reproduce the long-wavelength signals from other components, whereas the model recovered from five components accommodated all of the signals from all of the components. To estimate the influence of long-wavelength signals from targets other than the intrusion, such as deeper bodies or large-scale terrain variations, inversion tests are performed on a synthetic model. The inversion results for the synthetic example indicate that the joint inversion of five components is more sensitive to long-wavelength signals, which can generate spurious structures to fit all of the signals from the five components. In contrast, the [Formula: see text] model is less affected by the long-wavelength signals and thus tends to produce a stable solution, despite failing to incorporate all of the long-wavelength signals from the tensor data. We found that gravity gradiometry data could be used to delineate the intrusion within this study area, which is also consistent with the susceptibility model recovered from inversion of aeromagnetic data and with results from a previous geophysical study. Moreover, the differences between the [Formula: see text] model and the 5C model may reflect the long-wavelength signals in the gravity gradiometry data.

scholarly journals Interpretation of airborne gravity gradiometry and magnetic data using cross-gradients

2012 ◽  
Vol 2012 (1) ◽  
pp. 1-4
Author(s):  
Carlos Cevallos ◽  
Mark Dransfield ◽  
Jacqueline Hope ◽  
Heather Carey
Keyword(s):  
Magnetic Data ◽  
Airborne Gravity ◽  
Gravity Gradiometry ◽  
Airborne Gravity Gradiometry
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