Matched filter earthquake detection and double difference relocation at Rotokawa and Ngatamariki geothermal areas: January to November, 2015

Chet Hopp11Victoria Univerisity of Wellington, SGEES, PO Box 600, Wellington 6140, Martha Savage11footnotemark: , John Townend11footnotemark: , Steve Sherburn22GNS Science, Wairakei, Private Bag 2000, Taupo 3352

Matched filter earthquake detection uses waveform cross-correlation between continuous seismic data and known earthquake recordings to identify additional events in a seismic catalogue. Correlation-based detection offers improved performance over traditional, amplitude-based techniques due to its ability to detect signals in noisy data and when multiple events are closely spaced in time. This significantly increases the number of events detected without increasing the rate of false detections. These advantages make matched filter detection ideal for monitoring microseismicity in areas of geothermal power generation, which are characterized by numerous noise sources and the possibility for dense clusters of small-magnitude, induced seismic events.

The presence, importance and cause of induced seismicity at geothermal power generation sites has been recognized for decades (Ward 1972) (Allis 1982). Commonly, temperature and pressure change within a reservoir as a result of fluid injection is the culprit, although seismicity has also been attributed to reservoir volume changes and changes in fluid chemistry (Allis 1982) (Sherburn 2015). Most of this seismicity is of magnitude < 3.0, termed microseismicity, and presents limited hazard to local population and infrastructure, although the degree to which humans are affected varies considerably from location to location. Regardless of risk, microseismicity can provide very useful information about the movement of fluid and pressure within the reservoir, and therefore has important implications for geothermal resource management.

Microseismicity at geothermal areas can be highly repetitive in both its triggering process and its spatial extent. It is therefore suited to detection via matched filtering, which is recognized to be one of the best ways to identify near-repeating signals in continuous data (Gibbons 2006). It is also suited to earthquake detection in noisy geothermal power generation areas because it relies on signal cross-correlation as opposed to relative amplitudes to search for events (Shelly 2007). We investigate the performance of matched filtering on a nearly year-long dataset for Ngatamariki and Rotokawa geothermal fields on the north island of New Zealand, focusing on amplifying the number of detections triggered using standard methods and assessing what any additional detections might contribute to our knowledge of the processes at play within the reservoirs.

#Geologic and geophysical setting
Both the Ngatamariki and Rotokawa geothermal fields are located in the southern Taupo Volcanic Zone (TVZ) on the North Island of New Zealand, approximately 15 and 17 km north of the town of Taupo, respectively (Figure \ref{Figure1}). Rotokawa is a high temperature (>300°C at 1-2.5 km below sea level) reservoir with a roughly circular footprint measuring approximately 6 km across (Sherburn 2015). Ngatamariki, also a high temperature system at >280°C and similar in depth to Rotokawa, measures roughly 7 km2 (Chambefort 2016). Sequences of andesites, rhyolites and volcaniclastic sediments overlie greywacke basement at roughly 3 km below sea level at both fields, although lateral heterogeneity of these units is considerable as is the depth to basement (McNamara 2016) (Chambefort 2014). The geological structure at Rotokawa is dominated by three faults cutting through the field which have been modeled based on offsets in well cuttings of the basement greywacke and Rotokawa Andesite (Wallis 2013) (McNamara 2016). These faults, from West to East, are the Production Field Fault (PFF), Central Field Fault (CFF) and Injection Field Fault (Figure \ref{Figure1}). At Ngatamariki, two important features dominate the local geological structure. The first is the Aratiatia Fault Zone in the southern end of the field (Figure \ref{Figure1}) and the other is a shallow (<2 km) intrusive body, the presence of which was confirmed by drill cutings from wells NM04, NM08 and NM09 (Figure \ref{Figure1}) (Chambefort 2014). Given the low-permeability nature of much of the host rock, reservoir permeability at both fields is thought to be dominated by fractures and faults within the reservoirs along the prevailing NE-SW structural trend (McNamara 2016). However, the structure surrounding the shallow intrusives present in the northern half of Ngatamariki likely complicates the structural grain.

\label{Figure1} Map of the Ngatamariki and Rotokawa geothermal fields, North Island, New Zealand. Red triangles are seismograph sites, black lines represent mapped faults, and green dots represent template events used in the matched filtering process. The goldenrod boundaries are the Boseley (Boseley 2010) and Risk (Risk 2000) resistivity boundaries for Ngatamariki and Rotokawa respectively. Figure 1a and 1b show detailed maps of Ngatamariki and Rotokawa geothermal fields with pertinent wells labeled. Red wells are production wells whereas blue are injection wells.