日本新茂岳火山三次噴發週期地震噪聲中排列熵的時間變化

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艾蒂安(Diah Ayu Rahmalia) 查詢紙本館藏

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地球科學學系

論文名稱

日本新茂岳火山三次噴發週期地震噪聲中排列熵的時間變化
(Temporal variation of permutation entropy in seismic noise during three eruption cycles at Shinmoedake volcano, Japan)

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摘要(中)

摘要
排列熵(PE)是時間序列的複雜性度量，在存在觀測噪聲的情況下很有用。PE將時間序列編碼為符號序列，並與可能的模式匹配作為符號組合。排列熵然後量化出現在時間序列中的可能排列模式。本研究調查了日本新燃岳火山在2011年、2017年和 2018年的三次噴發期間的PE變化。新燃岳火山於2011年1月第一次岩漿噴發，6年後的2017年10月開始新的活動，隨後在2018年3月再次噴發。頻率範圍 1 - 7 Hz用於推斷 PE 的時間變化系列數據。排列熵計算是通過使用嵌入維度 (m=5) 和嵌入延遲 (L=2) 在 20 分鐘的時間窗口長度內進行的。結果顯示，每次噴發前PE值都會下降。PE 值的降低說明與火山震顫和岩漿遷移到較淺深度相關的複雜性降低，這導致地震波衰減。在下降模式結束時，PE 在 2011 年、2017 年和 2018 年的噴發事件之前也表現出上升和突然下降。在 2011 年和 2017 年，由於含水層和高溫岩漿上升之間的相互作用，該特徵與氣泡破裂有關。2018年上升岩漿與2011年凝固岩漿相互作用產生的裂縫影響了 2018 年噴發前 PE 的增加和突然下降。

摘要(英)

ABSTRACT

Permutation entropy (PE) is a complexity metric for time series that is useful in the presence of observational noise. PE encodes the time series into sequences of symbols and is matched with possible patterns as the combination of symbols. Permutation entropy then quantifies the possible permutation pattern that appears in a time series. This study investigated PE variation during three eruptions in 2011, 2017, and 2018 at Shinmoedake volcano, Japan. Shinmoedake had its first magmatic eruption in January 2011 and after 6 years, a new activity began in October 2017 and it was followed by another eruption in March 2018. The frequency range 1 - 7 Hz was used to infer the temporal change of PE in time series data. Permutation entropy calculation was performed by using the embedding dimension (m=5) and embedding delay (L=2) in a 20 minutes time window length. The results showed that PE values decreased before each eruption occurred. Decreasing PE values indicated a reduction of complexity that was associated with volcanic tremor and magma migration to the shallower depth, which caused attenuation of seismic waves. At the end of decreasing pattern, PE also exhibited an increase and sudden decrease just before the eruption events in 2011, 2017, and 2018. In 2011 and 2017, this feature was associated with the bubble bursts due to interaction between the aquifer and high temperature magma ascent. The fractures which were generated by the interaction between the ascending 2018 magma with the 2011 solidified magma influenced PE increase and sudden drop just before the 2018 eruption. We also analyzed the correlation between tremor depth location and PE values that depicted a negative correlation in each eruption period. PE values decreased when tremor occurred at a shallower depth and increased when tremor migrated to larger depths. At shallower depth, volcanic tremor was associated with the presence of steam and bubbles due to the interaction between high temperature magma and the aquifer. This probably attenuated the high frequency (stochastic) signals and produced lower PE values. On the other hand, volcanic tremor at the deeper part was related to the magma pressure build-up as the magma ascended. Steam, bubbles, and high temperature water layer were absent at the deeper part, hence the attenuation of seismic waves was not significant. Therefore, the system became more complex and produced higher PE values.

關鍵字(中)

★ 排列熵
★ 新燃岳火山
★ 火山噴發
★ 顫動深度位置

關鍵字(英)

★ Permutation entropy
★ Shinmoedake volcano
★ Eruption
★ Tremor depth location

論文目次

TABLE OF CONTENTS

ABSTRACT..........................................................................................................…...........…...i
ACKNOWLEDGMENTS..…………………………...……………………….……………....ii
TABLE OF CONTENTS...............................................................................................……...iii
LIST OF FIGURES……………………………………………………………….…………..iv
LIST OF TABLES…………………………………………………………………..…………v
CHAPTER I INTRODUCTION.............................................................................….....…...1
1.1 Background of Shinmoedake volcano…...................................................................….1
1.1.1 Volcano-tectonic setting of Shinmoedake volcano...……………...……………..1
1.2.1 Volcanic activity at Shinmoedake volcano……………………………………....1
1.2 Ambient Seismic Noise.....................….....................................................................…3
1.2.1 Nature of ambient seismic noise..………………………………………...……..3
1.2.2 Complexity analysis in ambient seismic noise……..……................................…3
1.3 Permutation entropy...........…............................................……………………………4
1.4 Aims and structure of this thesis................................….............................................…5
CHAPTER II DATA DESCRIPTION AND PREPROCESSING..........…......….…….…11
2.1 Data Acquisition................…..........................….......................…….……………….11
2.2 Data Preprocessing.................................................….................…………………….12
CHAPTER III PERMUTATION ENTROPY CALCULATION....….…………………..16
3.1 Application of the method..............….........................……………………………….16
3.2 Temporal variation of permutation entropy......…...............................................….…18
CHAPTER IV DISCUSSION AND CONCLUSIONS…..........................….............…….28
4.1 PE variation during period I.................................…................................................…28
4.2 PE variation during period II................................…................................................…29
4.3 PE variation during period III..............................…................................................…31
4.4 Relationship between PE and tremor depth.........…................................................…31
4.5 Conclusions..............................................................................................................…32
REFERENCES..........................................................…...................................................…..37
APPENDIX A: The relationship between temporal PE values and the variation of m, L during October 2017……………………………………………………………………..…...41
APPENDIX B: The relative error of PE values as a function of N………………………….46
APPENDIX C : The relationship between PE variation and infrasound recordings…….…51
APPENDIX D : The relationship between PE variation and spectrograms of vertical component waveforms…………..…………………………………………………………..54
APPENDIX E : The lowest PE variation from April 2017 until May 2018………….…….59
APPENDIX F : Plot of tremor depth location vs permutation entropy…...………………..65
APPENDIX G : Temporal variation of PE and tremor locations…………………………..68

參考文獻

REFERENCES

Amigó, J.M., Zambrano, S., Sanjuán, M.A.F., 2008. Combinatorial detection of determinism in noisy time series. Epl 83. https://doi.org/10.1209/0295-5075/83/60005
Arzilli, F., Morgavi, D., Petrelli, M., Polacci, M., Burton, M., Di Genova, D., Spina, L., La Spina, G., Hartley, M.E., Romero, J.E., Fellowes, J., Diaz-Alvarado, J., Perugini, D., 2019. The unexpected explosive sub-Plinian eruption of Calbuco volcano (22–23 April 2015; southern Chile): Triggering mechanism implications. J. Volcanol. Geotherm. Res. 378, 35–50. https://doi.org/10.1016/j.jvolgeores.2019.04.006
Asten, M.W., Henstridge, J.D., 1984. Array estimators and the use of microseisms for reconnaissance of sedimentary basins. Geophysics 49, 1828–1837. https://doi.org/10.1190/1.1441596
Bandt, C., Pompe, B., 2002. Permutation Entropy: A Natural Complexity Measure for Time Series. Phys. Rev. Lett. 88, 4. https://doi.org/10.1103/PhysRevLett.88.174102
Bonnefoy-Claudet, S., Cotton, F., Bard, P.Y., 2006. The nature of noise wavefield and its applications for site effects studies. A literature review. Earth-Science Rev. 79, 205–227. https://doi.org/10.1016/j.earscirev.2006.07.004
Brenguier, F., Shapiro, N.M., Campillo, M., Ferrazzini, V., Duputel, Z., Coutant, O., Nercessian, A., 2008. Towards forecasting volcanic eruptions using seismic noise. Nat. Geosci. 1, 126–130. https://doi.org/10.1038/ngeo104
Brothelande, E., Amelung, F., Yunjun, Z., Wdowinski, S., 2018. Geodetic evidence for interconnectivity between Aira and Kirishima magmatic systems, Japan. Sci. Rep. 8, 1–10. https://doi.org/10.1038/s41598-018-28026-4
Cao, Y., Tung, W. wen, Gao, J.B., Protopopescu, V.A., Hively, L.M., 2004. Detecting dynamical changes in time series using the permutation entropy. Phys. Rev. E - Stat. Physics, Plasmas, Fluids, Relat. Interdiscip. Top. 70, 7. https://doi.org/10.1103/PhysRevE.70.046217
Cuesta-Frau, D., Murillo-Escobar, J.P., Orrego, D.A., Delgado-Trejos, E., 2019. Embedded dimension and time series length. Practical influence on permutation entropy and its applications. Entropy 21, 1–25. https://doi.org/10.3390/e21040385
Daw, C.S., Finney, C.E.A., Tracy, E.R., 2003. A review of symbolic analysis of experimental data. Rev. Sci. Instrum. 74, 915–930. https://doi.org/10.1063/1.1531823
Donaldson, C., Caudron, C., Green, R.G., Thelen, W.A., White, R.S., 2017. Relative seismic velocity variations correlate with deformation at Kīlauea volcano. Sci. Adv. 3, 1–12. https://doi.org/10.1126/sciadv.1700219
Geshi, N., Takarada, S., Tsuitsui, M., Mori, T., Kobayashi, T., 2010. Products of the August 22, 2018 eruption of Shinmoedake Volcano, Kirishima Volcanic Group, Japan. Bull. Volcanol. Soc. Jpn 55, 53–64.
Glynn, C.C., 2016. Forecasting volcanic eruption using permutation entropy variations in ambient seismic noise. MS Thesis. National Central University
Glynn, C.C., Konstantinou, K.I., 2016. Reduction of randomness in seismic noise as a short-term precursor to a volcanic eruption. Sci. Rep. 6, 1–9. https://doi.org/10.1038/srep37733
Godano, C., Carcadi, C., Privitera, E., 1996. Intermittent Behaviour of Volcanic Tremor at Mt. Etna. Pure Appl. Geophys. 147, 551–556. https://doi.org/doi:10.1007/bf01089699
Gutenberg, B., 1967. Microseisms, Contemporary Physics. https://doi.org/10.1080/00107516708204387
Ichihara, M., Matsumoto, S., 2017. Relative Source Locations of Continuous Tremor Before and After the Subplinian Events at Shinmoe-dake, in 2011. Geophys. Res. Lett. 44, 10,871-10,877. https://doi.org/10.1002/2017GL075293
Imura, R., 1992. Eruptive history of the Kirishima Volcano during the past 22 000 years. Geogr. Reports - Tokyo Metrop. Univesity 27, 71–89.
Kagiyama, T., 1994. Kirishima Volcanoes - Multi active volcanic group generated in a slightly tensile stress field. J. Geog. 103, 479–487.
Kagiyama, T., Utada, H., Yukutake, T., Mogi, T., Amita, K., 1996. Resistivity structure of the central and the southeastern part of Kirishima volcanoes. Bull. Volcanol. Soc. Jpn., 41(5), 215-225.
Kamata, H., Kodama, K., 1999. Volcanic history and tectonics of the Southwest Japan Arc. Isl. Arc 8, 393–403. https://doi.org/10.1046/j.1440-1738.1999.00241.x
Kato, K., Yamasato, H., 2013. The 2011 eruptive activity of Shinmoedake volcano, Kirishimayama, Kyushu, Japan-Overview of activity and Volcanic Alert Level of the Japan Meteorological Agency. Earth, Planets Sp. 65, 489–504. https://doi.org/10.5047/eps.2013.05.009
Kobayashi, T., 2019. Effectivity of Combination use of Multiple SAR Satellites for Volcano Monitoring - A Practical Lesson for SAR Constellation. Int. Geosci. Remote Sens. Symp. 4727–4730. https://doi.org/10.1109/IGARSS.2019.8898509
Konstantinou, K.I., 2002. Deterministic non-linear source processes of volcanic tremor signals accompanying the 1996 Vatnajökull eruption, Central Iceland. Geophys. J. Int. 148, 663–675. https://doi.org/10.1046/j.1365-246X.2002.01608.x
Little, D.J., Kane, D.M., 2017. Permutation entropy with vector embedding delays. Phys. Rev. E 96, 1–8. https://doi.org/10.1103/PhysRevE.96.062205
Maeno, F., Taniguchi, H., 2007. Spatiotemporal evolution of a marine caldera-forming eruption, generating a low-aspect ratio pyroclastic flow, 7.3 ka, Kikai caldera, Japan: Implication from near-vent eruptive deposits. J. Volcanol. Geotherm. Res. 167, 212–238. https://doi.org/10.1016/j.jvolgeores.2007.05.003
Matsumoto, K., Geshi, N., 2021. Shallow crystallization of eruptive magma inferred from volcanic ash microtextures: a case study of the 2018 eruption of Shinmoedake volcano, Japan. Bull. Volcanol. 83, 1–14. https://doi.org/10.1007/s00445-021-01451-6
Matsumoto, S., Shimizu, H., Matsushima, T., Uehira, K., Yamashita, Y., Nakamoto, M., Miyazaki, M., Chikura, H., 2013. Short-term spatial change in a volcanic tremor source during the 2011 Kirishima eruption. Earth, Planets Sp. 65, 323–329. https://doi.org/10.5047/eps.2012.09.002
Miyabuchi, Y., Hanada, D., Niimi, H., Kobayashi, T., 2013. Stratigraphy, grain-size and component characteristics of the 2011 Shinmoedake eruption deposits, Kirishima Volcano, Japan. J. Volcanol. Geotherm. Res. 258, 31–46. https://doi.org/10.1016/j.jvolgeores.2013.03.027
Miyoshi, M., Shimono, M., Hasenaka, T., Sano, T., Mori, Y., Fukuoka, T., 2010. Boron systematics of Hisatsu and Kirishima basaltic rocks from southern Kyushu, Japan. Geochem. J. 44, 359–369. https://doi.org/10.2343/geochemj.1.0076
Nakada, S., Nagai, M., Kaneko, T., Suzuki, Y., Maeno, F., 2013. The outline of the 2011 eruption at Shinmoe-dake (Kirishima), Japan. Earth, Planets Sp. 65, 475–488. https://doi.org/10.5047/eps.2013.03.016
Nakamichi, H., Yamanaka, Y., Terakawa, T., Horikawa, S., Okuda, T., Yamazaki, F., 2013. Continuous long-term array analysis of seismic records observed during the 2011 Shinmoedake eruption activity of Kirishima volcano, southwest Japan. Earth, Planets Sp. 65, 551–562. https://doi.org/10.5047/eps.2013.03.002
Nakao, S., Morita, Y., Yakiwara, H., Oikawa, J., Ueda, H., Takahashi, H., Ohta, Y., Matsushima, T., Iguchi, M., 2013. Volume change of the magma reservoir relating to the 2011 Kirishima Shinmoe-dake eruption-Charging, discharging and recharging process inferred from GPS measurements. Earth, Planets Sp. 65, 505–515. https://doi.org/10.5047/eps.2013.05.017
Nakata, N., Gualtieri, L., Fichtner, A., 2019. Seismic Ambient Noise, in: Introduction. Nakata, N., Gualtieri, L., Fichtner, A. (Eds.), pp. Xx-xxvii. Cambridge university press. New York. https://doi.org/10.1017/9781108264808 ?c
Natsume, Y., Ichihara, M., Takeo, M., 2019. A non-linear time-series analysis of the harmonic tremor observed at Shinmoedake volcano, Japan. Geophys. J. Int. 216, 1768–1784. https://doi.org/10.1093/gji/ggy522
Nurfitriana, I., 2019. Permutation Entropy Variation of Seismic Noise prior to Eruptive Activity at Shinmoedake Volcano, Japan. MS Thesis. National Central University.
Riedl, M., Müller, A., Wessel, N., 2013. Practical considerations of permutation entropy: A tutorial review. Eur. Phys. J. Spec. Top. 222, 249–262. https://doi.org/10.1140/epjst/e2013-01862-7
Ryabov, V.B., Correig, A.M., Urquizu, M., Zaikin, A.A., 2003. Microseism oscillations: From deterministic to noise-driven models. Chaos, Solitons and Fractals 16, 195–210. https://doi.org/10.1016/S0960-0779(02)00165-0
Shearer, P.M., 2009. Introduction to Seismology, second. ed. Cambridge University Press, New York.
Staniek, M., Lehnertz, K., 2007. Parameter selection for permutation entropy measurements. Int. J. Bifurc. Chaos 17, 3729–3733. https://doi.org/10.1142/S0218127407019652
Wilkinson, M., 1997. Nonlinear dynamics, chaos-theory, and the” sciences of complexity”: their relevance to the study of the interaction between host and microflora. Old Herborn Univ. Semin. Monogr. 111–130.
Yamada, T., Ueda, H., Mori, T., Tanada, T., 2019. Tracing volcanic activity chronology from a multiparameter dataset at Shinmoedake Volcano (Kirishima), Japan. J. Disaster Res. 14, 687–700. https://doi.org/10.20965/jdr.2019.p0687
Yang, Y., Ritzwoller, M.H., 2008. Characteristics of ambient seismic noise as a source for surface wave tomography. Geochemistry, Geophys. Geosystems 9. https://doi.org/10.1029/2007GC001814
Zieger, T., Sens-Schönfelder, C., Ritter, J.R.R., Lühr, B.G., Dahm, T., 2016. P-wave scattering and the distribution of heterogeneity around Etna volcano. Ann. Geophys. 59. https://doi.org/10.4401/ag-7085

指導教授

柯士達(K. I. Konstantinou)

審核日期

2021-8-19

推文