<p>We present three projects that use different bandwidths of the ambient noise spectrum to solve geophysical problems. Specifically, we use signals within the noise field to determine surface and shear wave velocities, image the shallow and deep crust, and monitor time-dependent deformation resulting from geothermal fluid injection and extraction. Harrat Al-Madinah, a Cenozoic bimodal alkaline volcanic field in west-central Saudi Arabia, is imaged using shear-velocities obtained from natural ambient seismic noise. To our knowledge, this project is the first analysis of Saudi Arabia structure using ambient noise methods. Surface wave arrivals are extracted from a year's worth of station-pair cross-correlations, which are approximations of the empirical Green's function of the interstation path. We determine group and phase velocity surface wave dispersion maps with a 0.1 decimal degree resolution and resolve a zone of slow surface wave velocity south-east of the city of Medina, which is spatially correlated with the most recent historical eruption (the 1256 CE Medina eruption). Dispersion curves are calculated at each grid-point of the surface-wave velocity maps and inverted to obtain measurements of shear-velocity with depth. The 1D velocity models are then used to produce average shear-velocity models for the volcanic field. A shear-velocity increase ranging from 0.5 to 1.0 km/s, suggesting a layer interface, is detected at approximately 20 km depth and compared to P-wave measurement from a previous refraction study. We compute cross-section profiles by interpolating the inversions into a pseudo-3D model and resolve a zone of slow shear-velocity below the 1256 CE eruption location. These areas are also spatially correlated with low values of Bouguer gravity. We hypothesize that the low shear-velocity and gravity measurements are caused by fluids and fractures created from prior volcanic eruptions. We use the coda of cross-correlations extracted from ambient noise to determine shear-velocity changes at Rotokawa and Ngatamariki, two electricity producing geothermal fields located in the North Island of New Zealand. Stacks of cross correlations between stations prior to the onset of production are compared to cross correlations of moving stacks in time periods of well stimulation and the onset of electricity production using the Moving Window Cross Spectral technique. An increase between 0.05% to 0.1% of shear-velocity is detected at Rotokawa coinciding with an increase of injection. The shear-velocity subsequently decreases by approximately 0.1% when the rate of production surpasses the rate of injection. A similar amplitude shear-velocity increase is detected at Ngatamariki during the beginning of injection. After the initial increase, the shear-velocity at Ngatamariki fluctuates in response to differences in injection and production rates. A straight-ray pseudo-tomography analysis is conducted at the geothermal fields, which reveals that localized positive velocity changes are co-located with injection wells. Lastly, we use ambient noise and active sources at the Ngatamariki geothermal field to determine the structure of the top 200 meters using the Refraction Microtremor technique. We deployed a linear 72-channel array of vertical geophones with ten meter spacing at two locations of the geothermal field and determine average 1D and 2D shear-velocity profiles. We were able to image depths between 57 to 93 meters for 2D profiles and up to 165 meters for 1D profiles. A shear-velocity anomaly was detected across one of the lines that coincided with the inferred location of a fault determined from nearby well logs. This suggests that the method can be used to cheaply and quickly constrain near-surface geology at geothermal fields, where ambient noise is abundant and typical reflection and refraction surveys require large inputs of energy and are hindered by attenuation and scattering in near-surface layers.</p>
Using ambient seismic noise to study temporal and spatial surface wave velocity structures and ambient noise field characteristics of central South Island, New Zealand