Colored inversion in depth domain

Meza, Ramses

doi:10.1190/segam2021-3577157.1

Cited by 2 publications

(1 citation statement)

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“…Seismic waveform indicator inversion builds the initial geologic model based on seismic waveform similarity and the spatial distance between wells, and the direct inversion is carried out on depth-domain seismic data constrained by the Bayesian framework. In addition, Meza (2021) proposed a workflow for depth-domain colored inversion implemented with commercial software [12]. Because the accuracy for the first category of methods depends on the trained model, it has poor generalization performance on other depth-domain datasets.…”

Section: Introductionmentioning

confidence: 99%

A Wavelet Extraction Method of Attenuation Media for Direct Acoustic Impedance Inversion in Depth Domain

Sun,

Cai,

Yao

2024

Applied Sciences

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The seismic image produced by pre-stack depth migration is more accurate and has clearer geological significance than the time image. However, the waveform of the depth-domain seismic image is affected not only by depth-dependent velocity variation but also by media attenuation, resulting in strong spectral variation of depth-domain seismic data. Therefore, depth-domain seismic inversion is still challenging. We propose a wavelet extraction method of attenuation media based on the generalized seismic wavelet, to address this issue. Then, the estimated depth-domain wavelets were applied to the direct acoustic impedance inversion. First, we investigated the effect of attenuation media on depth-domain source wavelets and derived an analytical formula for the depth-domain wavelets of attenuation media. Next, the time-domain generalized seismic wavelet was extended to the depth domain, which was utilized to study the feasibility of using the generalized seismic wavelet to characterize the seismic wavelet of the depth-domain attenuation media. Based on the orthogonal matching pursuit, we propose a method to extract the depth-domain generalized seismic wavelet directly from depth-domain seismic data. Finally, we applied this method to the depth-domain direct acoustic impedance inversion of a 3D field data example. Tests on the synthetic and 3D field datasets show that the proposed method can correctly extract the depth-domain seismic wavelet of attenuation media and attain direct inversion of the depth-domain acoustic impedance with high accuracy. Therefore, our method is effective and has robust potential in reservoir characterization, fluid prediction, and attribute extraction in the depth domain.

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Section: Introductionmentioning

confidence: 99%