Suppr超能文献

基于频率相关偏移预处理的全波形反演的目标函数。

An objective function for full-waveform inversion based on frequency-dependent offset-preconditioning.

机构信息

Departamento de Física Teórica e Experimental, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.

Departamento de Biofísica e Farmacologia, Universidade Federal do Rio Grande do Norte, Natal, RN, Brazil.

出版信息

PLoS One. 2020 Oct 28;15(10):e0240999. doi: 10.1371/journal.pone.0240999. eCollection 2020.

Abstract

Full-waveform inversion (FWI) is a powerful technique to obtain high-resolution subsurface models, from seismic data. However, FWI is an ill-posed problem, which means that the solution is not unique, and therefore the expert use of the information is required to mitigate the FWI ill-posedness, especially when wide-aperture seismic acquisitions are considered. In this way, we investigate the multiscale frequency-domain FWI by using a weighting operator according to the distances between each source-receiver pair. In this work, we propose a weighting operator that acts on the data misfit as preconditioning of the objective function that depends on the source-receiver distance (offset) and the frequency used during the inversion. The proposed operator emphasizes information from long offsets, especially at low frequencies, and as a consequence improves the update of deep geological structures. To demonstrate the effectiveness of our proposal, we perform numerical simulations on 2D acoustic Marmousi2 case study, which is widely used in seismic imaging tests, considering three different scenarios. In the first two ones, we have used an acquisition geometry with a maximum offset of 4 and 8 km, respectively. In the last one, we have considered all-offsets. The results show that our proposal outperforms similar strategies, for all scenarios, providing more reliable quantitative subsurface models. In fact, our inversion result has the lowest error and the highest similarity to the true model than similar approaches.

摘要

全波形反演(FWI)是一种从地震数据中获取高分辨率地下模型的强大技术。然而,FWI 是一个不适定问题,这意味着解不是唯一的,因此需要专家利用信息来减轻 FWI 的不适定性,特别是在考虑宽孔径地震采集时。为此,我们根据每个震源-接收器对之间的距离,通过使用加权算子研究多尺度频域 FWI。在这项工作中,我们提出了一种加权算子,它作用于数据不适定作为依赖于源-接收器距离(偏移量)和反演过程中使用的频率的目标函数的预处理。所提出的算子强调来自长偏移量的信息,特别是在低频时,从而改善了深部地质结构的更新。为了证明我们的建议的有效性,我们在广泛用于地震成像测试的二维声学 Marmousi2 案例研究上进行了数值模拟,考虑了三种不同的情况。在前两种情况下,我们分别使用了最大偏移量为 4 和 8 公里的采集几何形状。在最后一种情况下,我们考虑了所有偏移量。结果表明,我们的建议在所有情况下都优于类似的策略,提供了更可靠的定量地下模型。事实上,我们的反演结果比类似的方法具有更低的误差和更高的与真实模型的相似性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/4982/7592739/693cc67c54cc/pone.0240999.g001.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验