Joint inversion of gravity gradiometry data by model-weighted clustering in logarithmic space

2019 ◽  
Author(s):  
Zhengwei Xu ◽  
Le Wan ◽  
Muran Han ◽  
Michael S. Zhdanov ◽  
Yue Mao
Keyword(s):  
Joint Inversion ◽  
Gravity Gradiometry ◽  
Logarithmic Space ◽  
Weighted Clustering

scholarly journals Joint Inversion of 2D Gravity Gradiometry and Magnetotelluric Data in Mineral Exploration

Minerals ◽  
2019 ◽  
Vol 9 (9) ◽  
pp. 541 ◽  
Author(s):  
Rongzhe Zhang ◽  
Tonglin Li
Keyword(s):  
2D Gravity ◽  
Joint Inversion ◽  
Mineral Exploration ◽  
Gravity Data ◽  
Computation Time ◽  
Iteration Algorithm ◽  
Imaging Method ◽  
Gravity Gradiometry ◽  
Magnetotelluric Data ◽  
Data Space

We have developed a mineral exploration method for the joint inversion of 2D gravity gradiometry and magnetotelluric (MT) data based on data-space and normalized cross-gradient constraints. To accurately explore the underground structure of complex mineral deposits and solve the problems such as the non-uniqueness and inconsistency of the single parameter inversion model, it is now common practice to perform collocated MT and gravity surveys that complement each other in the search. Although conventional joint inversion of MT and gravity using model-space can be diagnostic, we posit that better results can be derived from the joint inversion of the MT and gravity gradiometry data using data-space. Gravity gradiometry data contains more abundant component information than traditional gravity data and can be used to classify the spatial structure and location of underground structures and field sources more accurately and finely, and the data-space method consumes less memory and has a shorter computation time for our particular inversion iteration algorithm. We verify our proposed method with synthetic models. The experimental results prove that our proposed method leads to models with remarkable structural resemblance and improved estimates of electrical resistivity and density and requires shorter computation time and less memory. We also apply the method to field data to test its potential use for subsurface lithofacies discrimination or structural classification. Our results suggest that the imaging method leads to improved characterization of geological targets, which is more conducive to geological interpretation and the exploration of mineral resources.

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.

3-D joint inversion of seismic waveform and airborne gravity gradiometry data

2020 ◽  
Vol 223 (2) ◽  
pp. 746-764
Author(s):  
Wenbin Jiang
Keyword(s):  
Density Distribution ◽  
Model Building ◽  
Joint Inversion ◽  
Velocity Model ◽  
Airborne Gravity ◽  
Inversion Method ◽  
Gravity Gradiometry ◽  
Velocity Models ◽  
Seismic Waveform ◽  
Velocity Model Building

SUMMARY Seismic full waveform inversion (FWI) is a robust velocity model building technique for hydrocarbon exploration. However, the density reconstruction within the framework of multiparameter FWI leads to more degrees of freedom in the parametrization, and the sensitivity of the inversion change significantly from velocity to density, thereby increasing the ill-posedness of the inverse problem. Gravity gradiometry data inversion is an effective method for resolving density distribution. Combining gravity gradiometry data in FWI could alleviate the non-linearity of the inversion by contributing additional density information for the velocity model building. I develop a 3-D joint seismic waveform and gravity gradiometry inversion method for estimating the velocity and density distribution in the subsurface. The method alternatingly minimizes the waveform and gravity gradiometry misfit. The cross-gradient constraint is applied to enhance the structural similarity between the density and velocity models. The effectiveness of the joint inversion algorithm is demonstrated by a 3-D checkerboard model and 3-D SEAM model. Synthetic examples demonstrate that the joint inversion can improve the image quality in geologically complex areas. A case study from the South China Sea shows that the joint inversion improves the velocity and density solutions compared to a standalone seismic FWI. The joint inversion results are consistent with the pre-stack depth migration section and the shape of the salt body is well resolved.

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.

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