Ambient Seismic Noise Tomography in the Auckland Volcanic Field

Auckland, New Zealand's most populous region (1.4 million), is situated over a monogenetic volcanic eld of at least 53 volcanoes. The most recent eruption in the Auckland Volcanic Field (AVF) was 600 years ago, therefore the AVF is considered active. The risk and hazard of a volcanic eruption in Auckland are di cult to assess. It has been di cult to produce a high resolution model of the subsurface structure of Auckland due to its low seismicity. However, because of New Zealand's long coastlines, Auckland experiences high energy ocean wave generated seismic noise. This study is the rst to use ocean noise to infer the structure of the Auckland subsurface. We successfully incorporated a University of Auckland borehole seismometer from Rangitoto Island (RBAZ) into an existing network of GeoNet seismometers in Auckland. We were able to correct for the di erent instrument responses of the 12 seismometers. The vertical components of 200 days of noisy wave elds from 66 possible station pairs were cross-correlated to estimate the impulse response; this way, the resulting time series is as if one of the stations is a seismic source, and the other a receiver. Using these 66 impulse responses, we estimated Rayleigh wave group and phase velocity dispersion relations by multiple lter analysis. Frequency-dependent surface wave speeds with periods between 3 and 10 seconds provided robust information about the subsurface. We inverted group and phase velocity dispersion curves for shear velocities near the surface to approximately 25 km depth. We found that shear velocity variations correlate well with the crust type and surface geology. The distribution of low-velocity zones shows good spatial correlation with the Murihiku and Waipapa Terranes (semi-continental crust). Models with monotonically increasing shear wave velocity mainly associated with the Dun Mountain Ophiolite Belt, of the Maitai Terrane (oceanic crust). Near the surface (0-1.5 km), basement rock exposures correlated well with higher shear wave velocities, while soft cover rock and poorly consolidated sediments correlated with lower velocities. The average of our 16 models also largely agrees with a shear velocity model obtained by joint teleseismic receiver functions and seismic surface wave inversion techniques by Horspool et al. (2006). II Acknowledgments I had the support of many people while I worked on this project. It seems right to celebrate them at the completion of this thesis by thanking a few of them. I thank God for blessing me with the mental faculties to learn quickly, solve problems, and the strength to persevere. Conducting this research project challenged my abilities and took considerable self discipline. When I started this project, I had e ectively no experience programming or using command-line interface software. Over the course of this project, I wrote many short programs in python, performed basic tasks on a computer with a Linux OS, used an SQL database, wrote my thesis in Latex, and used commandline interface programs such as MSNoise and Computer Programs in Seismology. My development in these areas was largely task directed and self taught. I frequently voiced my concerns to God and asked for help, and found myself able to press on. I thank my supervisor, Dr. Kasper van Wijk of the Physics Department, Faculty of Science, University of Auckland, for helping me consider problems in new ways, test ideas, annotate code, and understand what needed to be done. I lived in Hamilton for more than half of this course, and Dr. van Wijk was supportive of this, skyping, and corresponding with me by frequent email exchange. Dr. van Wijk also critiqued my suggestions, and added to them. He shared creative ways of presenting ideas and using gures e ectively. He is also very good at using cartopy, a python library containing cartographic tools. He wrote the scripts used to produce many of the maps used in this thesis, and also some of the other gures. Dr. van Wijk also proofed my writing and suggested many changes that have greatly clari ed our work, and increased my understanding. I thank Dr. Robert Herrmann of the Earthquake Center, Saint Louis University, for answering my many questions about how to use Computer Programs in Seismology and helping me to understand the graphical and numerical output. I thank Bernhard Spörli for his invaluable help interpreting the models in the context of the crustal type, geological structure, and lithology. His knowledge of New Zealand's tectonostratigraphic terranes was particularly relevant. I thank DEVORA for providing the computer I used, and the RBAZ seismic data, III IV and for funding the frequent data acquisition trips the Rangitoto. I thank Dr Kate Kennedi, of the School of Environment, Faculty of Science, University of Auckland, for helping organise data acquisition trips and providing the necessary equipment. I thank Dr Mark Chadwick from GNS for giving advice and directions on how to download and archive seismic records. I also thank Nigel Lewin of Information Services, Faculty of Science Administration, University of Auckland, for setting up a remote connection between my laptop and the DEVORA computer, so that I could work from Hamilton. I thank Carolin Boese, of IESE, for providing initial estimates of the orientations of the horizontal components of borehole seismometers in the Auckland Volcano Seismic Network (Appendix F). I want to thank my mother and mother-in-law for taking care of my daughter, enabling my wife and I to continue studying full-time. I want to thank my family and friends for their support. I also want to thank my wife, Kinga, for all the time she gave me, for her loving, persistent encouragement and support, and her constant belief in my abilities. I also want to thank my daughter Xylia, for making Kinga and I so happy with her love, smiles, and laughter.