Abstract
This article is devoted to the study of the ASARCO demolition seismic data. Two different classes of modeling techniques are explored: First, mathematical interpolation methods and second statistical smoothing approaches for curve fitting. We estimate the characteristic parameters of the propagation medium for seismic waves with multiple mathematical and statistical techniques, and provide the relative advantages of each approach to address fitting of such data. We conclude that mathematical interpolation techniques and statistical curve fitting techniques complement each other and can add value to the study of one dimensional time series seismographic data: they can be use to add more data to the system in case the data set is not large enough to perform standard statistical tests.
Highlights
In geology, seismometric time-series play the important role of understanding the local structure of the earth
Background of the Data In April 2013, two old smaller smoke stacks leftover by the ASARCO company were demolished in the City of El Paso
The University of Texas at El Paso (UTEP) deployed a series of one-component seismometers in downtown El Paso between 0.5 and 5.5 km from the stacks with the objective to record the seismic waves generated by the demolition
Summary
Seismometric time-series play the important role of understanding the local structure of the earth. While siesmometric time series have been studied in many ways, to our knowledge, no academic work looks at the possible knowledge that may be extracted by applying advanced mathematical and statistical interpolation methods to such data. We explore the application of a number of mathematical interpolation techniques to one-dimensional siesmometric time series data, and we study the local variation in the time series. In addition to the mathematical interpolation of the observed data, we study the local variation of the wave using statistical smoothing techniques. We first compute a moving standard deviation filter for the original time series This filter reflects the local variation of the series, a measure of the wave amplitude at a point in time.
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