Prediction of Seed Waveforms Using Surface Wave Dispersion Information

International Society of Explosives Engineers
Siavash Mahvelati Douglas Rudenko Brian Warner Mohamad Sharif
Organization:
International Society of Explosives Engineers
Pages:
10
File Size:
916 KB
Publication Date:
Jan 26, 2026

Abstract

Predicting and optimizing production shot vibrations using time-shifting and superposition of signature hole waveforms (seed waves) has been widely used for many years. In this method, a single borehole is detonated and recorded with seismographs at the locations of concern. Since a single hole waveform is a reproducible event, it is reasonable that the seismic signature from a multi-hole production shot can be predicted by summing a series of single hole waveforms that have been time‐lagged at intervals corresponding to delay times from the production shot. However, there are instances where seed waveforms are collected at locations other than the exact location of concern, which raises questions regarding the applicability of such recordings. The present study adopts the well-known concept of dispersion of surface waves to predict seed waves at a location of interest based on seismograms recorded at a closer offset. Surface waves, as their name suggests, are seismic waves that propagate along the Earth's surface. They are the dominant wave type within one wavelength from the ground surface. Surface waves are dispersive in nature meaning that in a layered medium, wave components with different frequencies travel at different velocities causing an input signal to disperse as it propagates. The proposed technique takes seed waves recorded at one location as the input and passes it through a frequency-dependent function developed using site dispersion characteristics. The site’s dispersion characteristics are either measured directly with surface wave methods or retrieved using shear wave velocity information. The output of the function is the seed wave prediction at the farther location of concern. The theoretical background, including the underlying assumptions and limitations, is discussed in detail, and the application of the technique is illustrated through field data from two sites.
Citation

APA: Siavash Mahvelati Douglas Rudenko Brian Warner Mohamad Sharif  (2026)  Prediction of Seed Waveforms Using Surface Wave Dispersion Information

MLA: Siavash Mahvelati Douglas Rudenko Brian Warner Mohamad Sharif Prediction of Seed Waveforms Using Surface Wave Dispersion Information. International Society of Explosives Engineers, 2026.

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