Key Laboratory of Geoscience Big Data and Deep Resource of Zhejiang Province, School of Earth Sciences, Zhejiang University, Hangzhou, 310027, China.
Deep Earth Imaging, Future Science Platform, CSIRO, Kensington, WA, 6151, Australia.
Nat Commun. 2023 Mar 2;14(1):1192. doi: 10.1038/s41467-023-36514-z.
The proliferation of seismic networks in Australia has laid the groundwork for high-resolution probing of the continental crust. Here we develop an updated 3D shear-velocity model using a large dataset containing nearly 30 years of seismic recordings from over 1600 stations. A recently-developed ambient noise imaging workflow enables improved data analysis by integrating asynchronous arrays across the continent. This model reveals fine-scale crustal structures at a lateral resolution of approximately 1-degree in most parts of the continent, highlighted by 1) shallow low velocities (<3.2 km/s) well correlated with the locations of known sedimentary basins, 2) consistently faster velocities beneath discovered mineral deposits, suggesting a whole-crustal control on the mineral deposition process, and 3) distinctive crustal layering and improved characterization of depth and sharpness of the crust-mantle transition. Our model sheds light on undercover mineral exploration and inspires future multi-disciplinary studies for a more comprehensive understanding of the mineral systems in Australia.
澳大利亚地震网络的普及为高分辨率探测大陆地壳奠定了基础。在这里，我们使用包含近 30 年来自 1600 多个台站的地震记录的大型数据集，开发了一个更新的三维剪切速度模型。最近开发的环境噪声成像工作流程通过整合整个大陆的异步阵列，实现了改进的数据分析。该模型以大约 1 度的横向分辨率揭示了大陆大部分地区的精细地壳结构，其特点包括：1）浅层低速（<3.2km/s）与已知沉积盆地的位置高度相关；2）已发现矿床下方的速度始终较快，表明整个地壳对矿床形成过程有控制作用；3）独特的地壳分层以及对地壳-地幔过渡带的深度和清晰度的更好描述。我们的模型为地下矿产勘查提供了线索，并为未来的多学科研究提供了启示，以更全面地了解澳大利亚的矿产系统。
