本日選文（共 1 篇）。
[646] 在地形條件嚴峻的瑞士 Lavey 地熱儲層周圍之大型 N 陣列與分布式聲學感測（DAS）
Large N-array and DAS around the Lavey geothermal reservoir in Switzerland in challenging topographic settings
- 期刊：GJI (OUP) — RSS
- Published：Wed, 11 Feb 2026 00:00:00 GMT
- DOI：10.1093/gji/ggag063
- 原文連結：連結
Summary (EN) From April to June 2025, a dense seismic network of 271 three‑component stations was deployed within an 8 km radius around Lavey‑les‑Bains, Switzerland, and complemented by distributed acoustic sensing (DAS) along a buried telecommunication cable to investigate the country’s hottest known natural geothermal system. The site—home to the 3 km‑deep Lavey‑1 well drilled in 2022, which showed unexpectedly low flow despite temperatures above 120°C—lies in the narrow Rhône Valley with steep topography, strong lateral heterogeneity and elevated anthropogenic noise that complicate seismic imaging. The paper describes the network geometry, instrumentation and deployment logistics, assesses data completeness and noise characteristics, and presents initial ambient‑noise and earthquake recordings, reporting high data quality and spatial coverage and establishing a benchmark dataset for developing passive imaging techniques in complex Alpine environments.
重點摘要（繁中） 2025年4月至6月，研究團隊在瑞士Lavey‑les‑Bains周邊8公里範圍內部署了271個三分量地震站，並沿埋地電信光纜佈置了分布式聲學感測（DAS），以研究該國已知最熱的天然地熱系統。該場域包含於2022年鑽到3公里深但雖然溫度超過120°C卻流量偏低的Lavey‑1探井，位於狹窄的羅納河谷，地形陡峭、側向構造異質性強且有人為噪音高，增加了地震成像難度。作者描述了網絡幾何、儀器與部署後勤，評估資料完整性與噪音特性，並展示首批環境噪音與地震記錄，結果顯示資料品質與空間覆蓋率高，提供一套在複雜阿爾卑斯環境中發展被動成像技術的基準資料。