Abstract

Airborne (or satellite) gravity measurement is a commonly used remote sensing method to obtain the underground density distribution. Airborne gravity gradiometry data have a higher horizontal resolution to shallower causative sources than airborne gravity anomaly, so joint exploration of airborne gravity and its gradient data can simultaneously obtain the anomaly feature of sources with different depths. The most commonly used joint inversion method of gravity and its gradient data is the data combined method, which is to combine all the components into a data matrix as mutual constraints to reduce ambiguity and non-uniqueness. In order to obtain higher resolution results, we proposed a cooperate density-integrated inversion method of airborne gravity and its gradient data, which firstly carried out the joint inversion using cross-gradient constraints to obtain two density structures, and then fused two recovered models into a result through Fourier transform; finally, data combined joint inversion of airborne gravity, and gradient data were reperformed to achieve high-resolution density result using fused density results as a reference model. Compared to the data combined joint inversion method, the proposed cooperate density-integrated inversion method can obtain higher resolution and more accurate density distribution of shallow and deep bodies meanwhile. We also applied it to real data in the mining area of western Liaoning Province, China. The results showed that the depth of the skarn-type iron mine in the region is about 900–1300 m and gives a more specific distribution compared to the geological results, which provided reliable data for the next exploration plan.

Highlights

  • Airborne gravity measurement is a usual used remote sensing method to obtain the underground density structure

  • Since the cross-gradient function is mostly used in the joint inversion method between different physical parameters, we introduce structural constraints for different components of the gravity data and obtain two density inversion results

  • We presented a cooperate density-integrated inversion method, which used the crossgradient and fusion methods to improve the resolution of the joint inversion of airborne gravity and its gradient data

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Summary

Introduction

Airborne gravity measurement is a usual used remote sensing method to obtain the underground density structure It is often ill-posed and requires certain prior information and constraints to guarantee the results that are unique and stable. Zhang extended the data-space joint inversion algorithm of magnetotelluric, gravity, and magnetic data to include first-arrival seismic travel-time and normalized cross-gradient constraints This method could effectively improve the computational speed and greatly reduce memory requirements [30]. Since the cross-gradient function is mostly used in the joint inversion method between different physical parameters, we introduce structural constraints for different components of the gravity data and obtain two density inversion results. Data fusion can combine the respective advantages of different geophysical data to obtain high-resolution results. The high-resolution method is verified on synthetic and real data

High-Resolution Cooperate Density-Integrated Inversion Method
Theoretical Model Tests
Real Data Application
Conclusions

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