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

Jiang, Wenbin

doi:10.1093/gji/ggaa296

Cited by 9 publications

(3 citation statements)

References 41 publications

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“…Jiang developed a 3D joint seismic waveform and gravity gradiometry inversion method. A case study in the South China Sea showed that joint inversion results are consistent with the pre-stack depth migration section, and the shape of the salt body is well resolved [31].…”

Section: Introductionmentioning

confidence: 66%

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

Gao

Liu

et al. 2021

Remote Sensing

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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.

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Section: Introductionmentioning

confidence: 66%

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

Gao

Liu

et al. 2021

Remote Sensing

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“…Although wave equation-based traveltime inversion methods [5,6] could provide a better near-surface velocity model because they account for the phase difference, the computation cost is much more expensive because of the wave equation calculation. The refraction traveltime tomography result can also be utilized in geological surveys [7], initial velocity models for early-arrival waveform inversion (EWI) [8][9][10], joint geophysical inversion [11], and medical imaging [12].…”

Section: Introductionmentioning

confidence: 99%

Iterative Interferometric Denoising Filter for Traveltime Picking

Qiao,

Zhou,

Hanafy

et al. 2024

Applied Sciences

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Traveltime picking accuracy is frequently affected by incoherent or random data noise. Within this context, we put forth a new denoising method called iterative interferometric denoising filtering. This method leverages the pseudo-Wigner distribution function to capture the offset and time-symmetric patterns of source wavelets convolved in seismic signals. Incoherent or random noises without this characteristic are eliminated via this approach. The processed data have waveform information distortion and more frequency components. However, the traveltime information can be considered correct, and the improved signal-to-noise ratio makes traveltime picking much more convenient. Our method’s practical applications in a synthetic and in two field datasets show that this technology can increase the signal-to-noise ratio, and the picked traveltime information can be used in traveltime tomography. These two field datasets were collected near the Aqaba Gulf and the Qademah fault, located in King Abdullah Economic City.

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“…To improve the convergence of the multiparameter FWI, ref. [27] used the cross-gradient method to perform the multi-parameter inversion of the variable-density acoustic wave equation, and ref. [28] adopted the truncated Gauss-Newton method to reconstruct velocity and density simultaneously.…”

Section: Introductionmentioning

confidence: 99%

Multi-Constrained Seismic Multi-Parameter Full Waveform Inversion Based on Projected Quasi-Newton Algorithm

Feng

Cao³

et al. 2023

Remote Sensing

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The multi-parameter full waveform inversion (FWI) that integrates velocity and density can make full use of the kinematic and dynamic information of the measured data to reconstruct the underground model. However, it faces problems of crosstalk between multiple parameters and strong nonlinearity. This research proposes a multi-constrained, multi-parameter FWI framework based on the projected quasi-Newton algorithm. This framework can introduce multiple types of prior geological information, which can effectively improve the problem of multi-parameter inversion. Additionally, the quasi-Newton method can eliminate the crosstalk phenomenon to further improve the inversion convergence speed. Taking the 1994BP model as an example, the results show that the projected quasi-Newton method has a faster convergence speed than the spectral projected gradient method, and reduces the crosstalk between parameters; multiple constraint sets are uniquely projected onto the intersection to ensure that the estimated values of model parameters meet multiple constraints. We also experiment with the overthrust model, which shows that the framework we proposed can improve the inversion accuracy and has good adaptability. The proposed multi-parameter inversion framework can be compatible with more prior information to obtain an inversion model that conforms to geological understanding and shows great potential in seismic exploration.

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

Cited by 9 publications

References 41 publications

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

High-Resolution Cooperate Density-Integrated Inversion Method of Airborne Gravity and Its Gradient Data

Iterative Interferometric Denoising Filter for Traveltime Picking

Multi-Constrained Seismic Multi-Parameter Full Waveform Inversion Based on Projected Quasi-Newton Algorithm

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