Microtremor method Saibi. Dec, 18, 2014.

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Microtremor method Saibi. Dec, 18, 2014

Outline INTRODUCTION BACKGROUND SURVEY DESIGN & DATA ACQUISITION DATA PROCESSING & INTERPRETATION CONCLUSION

Introduction The ReMi method is useful in determining: Site-specific earthquake response Liquefaction potential Soil compaction Subsurface geology Current commonly used techniques of estimating shallow shear velocities for assessment of earthquake site response are too costly for use in most urban areas. They require large sources to be effective in noisy urban settings. So that, the Refraction Microtremor (ReMi) method overcomes these problems by using standard P-wave recording equipment and surrounding noise to produce average one-dimensional shear-wave profiles down to 100m depths.

Surface Wave Methods Active Source Spectral-Analysis-of-Surface-Waves (SASW) method – 2 channel approach Multi-channel method using f-k processing Passive Source 2-D circular array and f-k processing Refraction Microtremor (ReMi) - passive energy with linear array

Background What is ReMi method? The refraction microtremor technique is based on two fundamental ideas. common seismic-refraction recording equipment can effectively record surface waves at frequencies as low as 2 Hz. a simple, two-dimensional slowness-frequency (p-f) transform of a microtremor record can separate Rayleigh waves from other seismic arrivals, and allow recognition of true phase velocity against apparent velocities. Two essential factors that allow exploration equipment to record surface-wave velocity dispersion, with a minimum of field effort, are the use of a single geophone sensor at each channel, rather than a geophone “group array”, and the use of a linear spread of 12 or more geophone sensor channels.

Background Single geophones are the most commonly available type, and are typically used for refraction rather than reflection surveying. The advantages of ReMi from a seismic surveying point of view are : It requires only standard refraction equipment already owned by most consultants and universities; it requires no triggered source of wave energy; and it will work best in a seismically noisy urban setting. Traffic and other vehicles, and possibly the wind responses of trees, buildings, and utility standards provide the surface waves this method analyzes.

Background Briefly, ReMi processing involves 3 steps: Velocity Spectral Analysis Rayleigh Phase-Velocity Dispersion Picking Shear-Velocity Modeling

Steps in Surface Wave Analysis Data Collection Sensor, # sensor, array configuration, frequencies, time or frequency domain, source, source offset etc … Data Processing Developing dispersion curve relating surface wave velocity versus frequency or wavelength Phase unwrapping (SASW), multi-channel transformations Forward Modeling/Inversion Match a theoretical dispersion curve to the measured experimental dispersion curve Two approaches to forward modeling Modal dispersion curves (typical use fundamental mode) Effective velocity dispersion curve

Field Testing Arrangement Array 1 (L>150 m) Array 2 (L>300 m)

Survey design and data acquisition The equipment needed includes : a 12- or 24-channel digital refraction gear with 4.5-14 Hz single vertical geophones phones and recording cable. The total array length can vary from 300 ft to 600 ft. Arrays as short as 60 ft and as long as several kilometers have been used for recording ReMi data. As a rule of thumb the maximum depth of resolution is about one-third to one-half the length of the array. Amplitude or frequency-response calibration of geophones is not needed - as with refraction, ReMi uses only the phase information in the recorded wavefield.

SASW Method Sample Data Receiver Located 340 m from Source Uses the phase difference recorded between a pairs of receivers with receiver spacing, d, to determine the effective surface wave velocity. The phase velocity at a given frequency, f, is calculated from the unwrapped phase difference, f, and receiver spacing, d, using: Procedure is repeated for multiple pairs of receivers to develop a dispersion curve for the site Sample Data Receiver Located 340 m from Source

Refraction Microtremor (ReMi) Utilizes the slant stack (p-t) algorithm to develop a frequency-slowness relationship A spectral ratio is calculated from the power at a each frequency-slowness point normalized by the average power at that frequency Based on assumption that energy impinges on array from all directions Identifies likely phase velocity values: peak, and middle “slope” Slowness versus Frequency

Active Source f-k Method One of several wavefield transformation methods Uses a multi-channel receiver array For each frequency, trial wavenumbers are used to shift and sum the response from all receiver pairs The phase velocity is calculated from the wavenumber with the maximum power using: Sample Data

2-D Passive Array f-k Method Sample Data Similar to 1-D approach but utilizes a 2-D array (typically circular) because the location of source is not known For each frequency, trial kX and kY values (velocity and direction) are used to shift and sum the response from all receiver pairs The phase velocity is calculated from the wavenumber with the maximum power using: Peak

ReMi test results from Reno NV international airport showing power spectral ratio images for (a) the 8-Hz geophone array; (b) the 4.5-Hz geophone array. (c) phase-velocity dispersion characteristics; (d) S-wave velocity depth profiles (Louie, 2007)

SASW analysis in the Mississippi embayment, top row: S-wave velocity and estimated lithology; bottom left: lithology key; bottom right: measured dispersion characteristic Vph(f) at site C compared to the forward response of the S-wave profile at C. Upper Claiborne=Eocene silts and clays, Memphis Sand=coarse-to-fine-grained sand, Wolf river=Mississippi River sand/gravel alluvium layers, Upland complex=Pliocene sand and gravel. (Rosenblad et al., 2010)

SPAC microtremor array analysis from Kilauea volcano, Hawaii: (a) seismometer array; (b) R-wave dispersion characteristics; (c) S-wave velocity profiles; after Soccarotti et al. 2003