Giraudat Elsa, Burtin Arnaud, Le Ber Arthur, Fink Mathias, Komorowski Jean-Christophe, Aubry Alexandre
Institut Langevin, ESPCI Paris, PSL University, CNRS, F-75005 Paris, France.
Université Paris Cité, Institut de Physique du Globe de Paris, CNRS, F-75005 Paris, France.
Commun Earth Environ. 2024;5(1):509. doi: 10.1038/s43247-024-01659-2. Epub 2024 Sep 16.
Volcanic eruptions necessitate precise monitoring of magma pressure and inflation for improved forecasting. Understanding deep magma storage is crucial for hazard assessment, yet imaging these systems is challenging due to complex heterogeneities that disrupt standard seismic migration techniques. Here we map the magmatic and hydrothermal system of the La Soufrière volcano in Guadeloupe by analyzing seismic noise data from a sparse geophone array under a matrix formalism. Seismic noise interferometry provides a reflection matrix containing the signature of echoes from deep heterogeneities. Using wave correlations resistant to disorder, matrix imaging successfully unscrambles wave distortions, revealing La Soufrière's internal structure down to 10 km with 100 m resolution. This method surpasses the diffraction limit imposed by geophone array aperture, providing crucial data for modeling and high-resolution monitoring. We see matrix imaging as a revolutionary tool for understanding volcanic systems and enhancing observatories' abilities to monitor dynamics and forecast eruptions.
火山喷发需要精确监测岩浆压力和膨胀情况以改进预测。了解深部岩浆储存对于灾害评估至关重要，但由于复杂的非均质性会干扰标准地震偏移技术，对这些系统进行成像具有挑战性。在这里，我们通过在矩阵形式下分析来自稀疏地震检波器阵列的地震噪声数据，绘制了瓜德罗普岛苏弗里耶尔火山的岩浆和热液系统图。地震噪声干涉测量法提供了一个包含深部非均质性回波特征的反射矩阵。利用抗无序的波相关性，矩阵成像成功地解开了波的畸变，揭示了苏弗里耶尔火山内部结构，深度达10公里，分辨率为100米。该方法超越了地震检波器阵列孔径所施加的衍射极限，为建模和高分辨率监测提供了关键数据。我们将矩阵成像视为理解火山系统以及增强观测站监测动态和预测火山喷发能力的革命性工具。
