日本地球惑星科学連合2019年大会

講演情報

[J] ポスター発表

セッション記号 S (固体地球科学) » S-SS 地震学

[S-SS11] 地震波伝播:理論と応用

2019年5月28日(火) 15:30 〜 17:00 ポスター会場 (幕張メッセ国際展示場 8ホール)

コンビーナ:西田 究(東京大学地震研究所)、白石 和也(海洋研究開発機構)、新部 貴夫(石油資源開発株式会社)、澤崎 郁(防災科学技術研究所)

[SSS11-P08] Measuring the NCF dispersion without the long inter-station distance limitation – a new method based on hybrid peak time matching

*Ying-Nien Chen1Yuancheng Gung2Ling-Yun Chiao3 (1.Institute of Seismology, National Chung Cheng University, Taiwan.、2.Department of Geosciences, National Taiwan University, Taipei, Taiwan.、3.Institute of Oceanography, National Taiwan University, Taipei, Taiwan.)

キーワード:phase velocity measurement, Empirical Green’s Function, ambient noise

Over the past decade, the probing of Earth structures using seismic ambient noises has been widely used by seismologists and is now a well-developed technique. Based on an implicit high-frequency approximation, the consensus is that the noise cross-correlation function (NCF) of continuous seismic records resembles the Green’s Function (GF) of the far-field surface wave between sensors. This perspective leads to the application of the long interstation distance criterion in the dispersion measurements, and, accordingly, much of the low-frequency content in the NCF is rejected. Herein we show that, for a far-field source, the NCF used in most surface wave studies should not be considered as representative of the empirical Green’s Function (EGF); instead, it is simply the interference product between sensors. We present a theoretical derivation of an explicit definition for a “high-frequency approximation” and clarify the relationship between the NCF and the EGF. Furthermore, we propose a new method to measure the NCF dispersion, in which the phase velocity is estimated by matching the peak delay time observed in the time domain NCF to the one predicted by the theoretical complex NCF signals. In this hybrid peak time matching technique, the long interstation distance is no longer a required condition and phase velocities can be determined more precisely at lower frequencies. Therefore, this permits the investigation of deeper structures using noise data.