Using ambient seismic noise to study temporal and spatial surface wave velocity structures and ambient noise field characteristics of central South Island, New Zealand

<p>Ambient seismic noise is used to examine the spatial and temporal surface wave velocity structures and ambient seismic noise fields in the vicinity of different fault zone environments. This study focuses on two distinct regions of central South Island, New Zealand. The Canterbury Plains is a sedimentary basin with many minor faults, which was considered to have low seismic hazard prior to the 2010 – 2011 Canterbury earthquake sequence. We focus on the time period immediately following the 2010 Darfield earthquake, which ruptured the previously unmapped Greendale Fault. The second region of interest is the central Southern Alps. The locked portion of the Alpine Fault currently poses one of the largest seismic hazards for New Zealand. The wealth of data from both permanent and temporary seismic deployments in these regions make them ideal areas in which to assess the effectiveness of ambient noise for velocity modelling in regions surrounding faults at different stages of their seismic cycles. Temporal velocity changes are measured following the Mw 7.1 Darfield earthquake of 4 September 2010 in the Canterbury Plains. Nine-component cross-correlations are computed from temporary and permanent seismic stations lying on and surrounding the Greendale Fault. Using the Moving-Window Cross-Spectral method, surface wave velocity changes are calculated for the four months immediately following the earthquake until 10 January 2011, for 0.1 — 1.0 Hz. An average increase in seismic velocity of 0.14 ± 0.04 % is determined throughout the region, providing the first such estimate of postseismic relaxation rates in Canterbury. Depth analyses further showed that velocity changes are confined to the uppermost 5 km of the subsurface and we attribute this to postseismic relaxation via crack-healing of the Greendale Fault and throughout the surrounding region. Rayleigh and Love wave dispersion is examined throughout the Canterbury region. Multi-component cross-correlation functions are analysed for group and phase dispersion curves. These are inverted using frequency-time analysis for 2-D phase and group velocity maps of Rayleigh and Love waves. A high-velocity zone to the southeast of the region coincides with volcanic rocks of Banks Peninsula. Dispersion curves generated from the surface wave tomography are further inverted for one-dimensional shear velocity profiles. These models show a thin, low-velocity near surface layer consistent with the basin sediments, which thins towards the foothills of the Southern Alps. A near-surface damage zone is identified along the length of the Greendale Fault, with consistent reduced Vs velocities to depth of up to 5 km. Surface and shear wave velocity maps are computed for the central Southern Alps to image the seismic structure of the region. Tomographic surface maps at periods of 5 – 12 s are produced from dispersion measurements of three-component cross-correlation functions. At periods of 5 – 8 s a strong NE-SW trending velocity contrast highlights the Alpine Fault. One-dimensional shear velocity models, computed from the surface wave maps, are in agreement with previous models produced by other conventional methods. An analysis of surface wave amplitudes through signal-to-noise ratios of cross-correlations reveals strong directional effects. Calculated signal-to-noise ratios are up to eight times higher for surface waves travelling north-west than for waves travelling to the south or east. We attribute this to a combination of more energetic ocean wave signals from the Southern Ocean compared to the Tasman Sea.</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

<p>Ambient seismic noise is used to examine the spatial and temporal surface wave velocity structures and ambient seismic noise fields in the vicinity of different fault zone environments. This study focuses on two distinct regions of central South Island, New Zealand. The Canterbury Plains is a sedimentary basin with many minor faults, which was considered to have low seismic hazard prior to the 2010 – 2011 Canterbury earthquake sequence. We focus on the time period immediately following the 2010 Darfield earthquake, which ruptured the previously unmapped Greendale Fault. The second region of interest is the central Southern Alps. The locked portion of the Alpine Fault currently poses one of the largest seismic hazards for New Zealand. The wealth of data from both permanent and temporary seismic deployments in these regions make them ideal areas in which to assess the effectiveness of ambient noise for velocity modelling in regions surrounding faults at different stages of their seismic cycles. Temporal velocity changes are measured following the Mw 7.1 Darfield earthquake of 4 September 2010 in the Canterbury Plains. Nine-component cross-correlations are computed from temporary and permanent seismic stations lying on and surrounding the Greendale Fault. Using the Moving-Window Cross-Spectral method, surface wave velocity changes are calculated for the four months immediately following the earthquake until 10 January 2011, for 0.1 — 1.0 Hz. An average increase in seismic velocity of 0.14 ± 0.04 % is determined throughout the region, providing the first such estimate of postseismic relaxation rates in Canterbury. Depth analyses further showed that velocity changes are confined to the uppermost 5 km of the subsurface and we attribute this to postseismic relaxation via crack-healing of the Greendale Fault and throughout the surrounding region. Rayleigh and Love wave dispersion is examined throughout the Canterbury region. Multi-component cross-correlation functions are analysed for group and phase dispersion curves. These are inverted using frequency-time analysis for 2-D phase and group velocity maps of Rayleigh and Love waves. A high-velocity zone to the southeast of the region coincides with volcanic rocks of Banks Peninsula. Dispersion curves generated from the surface wave tomography are further inverted for one-dimensional shear velocity profiles. These models show a thin, low-velocity near surface layer consistent with the basin sediments, which thins towards the foothills of the Southern Alps. A near-surface damage zone is identified along the length of the Greendale Fault, with consistent reduced Vs velocities to depth of up to 5 km. Surface and shear wave velocity maps are computed for the central Southern Alps to image the seismic structure of the region. Tomographic surface maps at periods of 5 – 12 s are produced from dispersion measurements of three-component cross-correlation functions. At periods of 5 – 8 s a strong NE-SW trending velocity contrast highlights the Alpine Fault. One-dimensional shear velocity models, computed from the surface wave maps, are in agreement with previous models produced by other conventional methods. An analysis of surface wave amplitudes through signal-to-noise ratios of cross-correlations reveals strong directional effects. Calculated signal-to-noise ratios are up to eight times higher for surface waves travelling north-west than for waves travelling to the south or east. We attribute this to a combination of more energetic ocean wave signals from the Southern Ocean compared to the Tasman Sea.</p>

A Superior Seismic Data Preprocessing Technique to Improve the Resolution of Surface wave Velocity Spectrums

A high-resolution surface wave velocity spectrum, also known as dispersion image, is of paramount importance for any seismic survey to accurately predict subsurface earth’s properties. The presence of diversified noise in the field acquisition and dissimilar attenuation due to mechanical and radial damping makes it challenging for different wavefield transformation algorithm to produce a detailed and precise velocity spectrum. Standard seismic data preprocessing technique like trace normalisation or bandpass filter fails to address all issues appropriately. Here we have presented a new superior preprocessing technique that can eradicate most of the shortcomings adequately. Experimental field data and published results are used to demonstrate the accuracy of the proposed method. The proposed method also found to produce superior results when compared against the popular commercially available software package Surfseis 6. Overall, the proposed method improves the quality of the velocity spectrum significantly, and it produces a sharper dispersion image even for the extremely noisy data. The work presented here enhances our ability to interpret the surface wave data precisely and help explore accurate properties of the subsurface earth.

Experimental Validation of Slip-Forming Using Ultrasonic Sensors

Slip-forming in concrete construction enables the continuous placement of concrete using a climbing form, the efficiency of which depends on appropriate slip-up timing. This implies the importance of knowing accurately the development of concrete strength over time, which has been assessed manually to date in construction fields. This paper presents a method for automating the slip-forming process by determining the optimal slip-up time using the in-situ strength of concrete. The strength of concrete is evaluated by a formula relating the strength to the surface wave velocity measured with ultrasonic sensors. Specifically, this study validates the applicability of the slip-form system with ultrasonic sensors for continuously monitoring the hardening of concrete through its application in several construction sites. To this end, a slip-form system with a pair of ultrasonic modules at the bottom of the panel was tested and the time variation of surface wave velocity in the concrete material was monitored during the slip-forming process. The results show that the proposed method can provide the optimal slip-up time of the form to automate the slip-forming process. This approach is expected to apply to other construction technologies that required the continuous monitoring of concrete strength for construction efficiency as well as quality maintenance.