Common-midpoint spatial autocorrelation analysis of seismic ambient noise obtained from a spatially unaliased sensor distribution

Author:

Hayashi Koichi1ORCID,Craig Mitchell2,Tan Shunjia3,Konishi Chisato4,Suzuki Haruhiko5,Tahara Michitaka5ORCID,Falkenstein Kent6ORCID,He Bin7,Cheng Daxiang7

Affiliation:

1. Geometrics/OYO Corporation, 2190 Fortune Drive, San Jose, California 95014, USA.(corresponding author).

2. California State University, East Bay, 25800 Carlos Bee Blvd., Hayward, California 94542, USA..

3. School of Geophysics and Measurement Control Technology, ECUT and Institute of Geology, CAGS, No. 26 Baiwanzhuang Street, Beijing 100037, China..

4. OYO Corporation, 1-66-2, Miyahara-cho, Kita-ku, Saitama, Saitama 331-0812, Japan..

5. OYO Corporation, 1-10-2, Sakuragi-cho, Omiya-ku, Saitama, Saitama 330-0854, Japan..

6. Geometrics, 2190 Fortune Drive, San Jose, California 95014, USA..

7. Laurel Geophysical Instruments LTD, Qikeshu Innovation Park B5-1, NO.55 Banjieta Road, Chaoyang District, Beijing, China..

Abstract

We have introduced a passive surface-wave method using seismic ambient noise obtained from dozens of receivers forming spatially unaliased 2D arrays. The method delineates 2D or 3D S-wave velocity ([Formula: see text]) models to depths of several hundreds of meters, without using any sources. Typical data acquisition uses 50–100 vertical-component 2 Hz geophones on the surface with 5–30 m receiver spacing. Cableless seismographs with GPS record 20–60 min of ambient noise. We establish a 2D grid covering the investigation area and use a common-midpoint spatial autocorrelation (CMP-SPAC) method to calculate phase velocities, resulting in a dispersion curve for each grid point. The method provides dozens of ispersion curves in the investigation area. We use a 1D nonlinear inversion to estimate a 1D [Formula: see text] profile for each grid point, and then we construct pseudo-2D or pseudo-3D [Formula: see text] models from the 1D [Formula: see text] profiles. The precision and accuracy of the CMP-SPAC method were tested with a numerical simulation using a 3D finite-difference method. The results of the simulation demonstrated the applicability of the method to complex velocity structures. We applied the method to an active fault investigation in China. Sixty-four cableless seismographs were deployed in an investigation area of 330 × 660 m (217,800 m2) with 5 and 30 m receiver spacings for dense and sparse grids, respectively. A 3D [Formula: see text] model was obtained to a depth of 150 m from CMP-SPAC analysis. The resultant 3D [Formula: see text] model indicates approximately 50 m of vertical displacement on a known fault.

Publisher

Society of Exploration Geophysicists

Subject

Geochemistry and Petrology,Geophysics

Reference57 articles.

1. Application of the Spatial Auto-Correlation Method for Shear-Wave Velocity Studies Using Ambient Noise

2. Boore, M. D., 2006, Determining subsurface shear-wave velocities: A review: Proceedings of the 3rd International Symposium on the Effects of Surface Geology on Seismic Motion, 103.

3. Geophone array formation and semblance evaluation

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