Developing and Exploiting a Unique Seismic Dataset from South African Gold Mines for Source Characterization and Wave Propagation
Abstract
In this project, we are developing and exploiting a unique seismic dataset to address the characteristics of small seismic events and the associated seismic signals observed at local (<200 km) and regional (<2000 km) distances. The dataset is being developed using mining-induced events from three deep gold mines in South Africa recorded on in-mine networks (<1 km) composed of tens of high-frequency sensors, a network of four broadband stations installed as part of this project at the surface around the mines (1-10 km), and a network of existing broadband seismic stations at local/regional distances (50-1000 km) from the mines. After a year of seismic monitoring of mine activity (2007), over 10,000 events in the range -3.4 < ML < 4.4 have been catalogued and recorded by the in-mine networks. Events with positive magnitudes are generally well recorded by the surface-mine stations, while magnitudes of 3.0 and larger are seen at regional distances (up to ~600 km) in high-pass filtered recordings. We have analyzed in-mine recordings in detail at one of the South African mines (Savuka) to (i) improve on reported hypocentral locations, (ii) verify sensor orientations, and (iii) determine full moment tensor solutions. Hypocentral relocations on all catalogued events have been obtained from P- and S-wave travel-times reported by the mine network operator through an automated procedure that selects travel times falling on Wadati lines with slopes in the 0.6-0.7 range; sensor orientations have been verified and, when possible, corrected by correlating P-, SV-, and SH-waveforms obtained from theoretical and empirical (polarization filter) rotation angles; full-moment tensor solutions have been obtained by inverting P-, SV-, and SH-spectral amplitudes measured on the theoretically rotated waveforms with visually assigned polarities.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 01, 2008
- Accession Number
- ADA516115
Entities
People
- Andrew A. Nyblade
- Jordi Julia
- Lindsay Linzer
- Ray Durrheim
- Regin Gok
- William R. Walter
Organizations
- Pennsylvania State University