NS41B-1937
Garner Valley Vibroseis Data Processing Using Time-Frequency Filtering Techniques to Remove Unwanted Harmonics and External Noise

Thursday, 17 December 2015
Poster Hall (Moscone South)
Neal Edward Lord1, Herb F Wang1, Dante Fratta1,2, Chelsea Lancelle1 and Athena Chalari3, (1)University of Wisconsin Madison, Madison, WI, United States, (2)University of Wisconsin - Madison, Madison, WI, United States, (3)Silixa Ltd., Hertfordshire, United Kingdom
Abstract:
Time-frequency filtering techniques can greatly improve data quality when combined with frequency swept seismic sources (vibroseis) recorded by seismic arrays by removing unwanted source harmonics or external noise sources (e.g., cultural or ambient noise). A source synchronous filter (SSF) is a time-frequency filter which only passes a specified width frequency band centered on the time varying frequency of the seismic source. A source delay filter (SDF) is a time-frequency filter which only passes those frequencies from the source within a specified delay time range. Both of these time-frequency filters operate on the uncorrelated vibroseis data and allow separate analysis of the source fundamental frequency and each harmonic. In either technique, the time-frequency function of the source can be captured from the source encoder or specified using two or more time-frequency points.

SSF and SDF were both used in the processing of the vibroseis data collected in the September 2013 seismic experiment conducted at the NEES@UCSB Garner Valley field site. Three vibroseis sources were used: a 45 kN shear shaker, a 450 N portable mass shaker, and a 26 kN vibroseis truck. Seismic signals from these sources were recorded by two lines of 1 and 3 component accelerometers and geophones, and the Silixa Ltd’s intelligent Distributed Acoustic Sensing (iDASTM ) system connected to 762 m of trenched fiber optical cable in a larger rectangular area. SSF and SDF improved vibroseis data quality, simplified data interpretation, and allowed new analysis techniques. This research is part of the larger DOE’s PoroTomo project (URL: http://geoscience.wisc.edu/feigl/porotomo).