| Title | Detecting Microseismic Activity in American Samoa with Surface and Deep Borehole Stations |
|---|---|
| Authors | C M. Boese, T. Bodell, M. Cheng, A. Lucas |
| Year | 2016 |
| Conference | New Zealand Geothermal Workshop |
| Keywords | Seismic monitoring, geothermal exploration, borehole seismometers, volcano-tectonic earthquakes, American Samoa. |
| Abstract | American Samoa is located at the eastern end of a ~500 km-long chain of islands formed by hotspot volcanism. The original shield volcano edifices of the islands are recent structures that formed from submarine volcanoes <5 Ma. Various theories explaining the origin of widespread recent and historic rejuvenated volcanism throughout the Samoa chain are based on limited seismic and geochemical data. This paper presents the deployment status and preliminary results obtained from a new network of borehole and surface seismometers. American Samoa`s remote location adjacent to the Pacific and Australian Plate Boundary place it at risk of intensely active tectonic processes. To supplement the only existing broadband recording station in Apia, Upolu (120 km northwest of American Samoa) an unprecedented seismic monitoring network has been installed on Tutuila and Ta’u islands: 6 highly-sensitive monitoring stations have been set up with 3 borehole sensors placed at 60-670 m (205-2,020 feet) depth and 3 movable surface seismometers placed at strategically important locations. The network is designed to detect local seismicity associated with volcanic activity, to help reassess the island`s geothermal potential, provide structural and stratigraphic information and to mitigate geologic hazards. To accurately constrain earthquake locations throughout the islands a 1-D velocity model is needed. A new technique that utilizes the ever-present, high natural background noise created by the Pacific Ocean to extract information about the subsurface velocity has been tried. However, this ambient seismic noise technique has not produced the required results to constrain the velocity structure. Therefore, earthquake data from the existing 6-station SLISE network between 2005 and 2009 and the new stations is being processed to derive an initial 1-D velocity model. |