AbstractsEarth & Environmental Science

Earth-model discrimination method

by Mensur Omerbashich

Institution: University of New Brunswick
Department: Geodesy and Geomatics Engineering
Degree: Doctorate Degree
Year: 2003
Keywords: global geophysics; Earth modeling; seismotectonics genesis; earthquake prediction; earthquake forecast; earthquake anti-forecast
Posted: 06/23/2018
Record ID: 2222153
Full text PDF: https://doi.org/10.6084/m9.figshare.12847304


Investigation of the earth's interior is attempted via gravimetric terrestrial spectroscopy from superconducting gravimeter (SG) records containing all medium and large earthquakes that affected the SG. I introduce a general (single station, all-type earthquakes; no pre- or post-processing) method that enables discrimination amongst geophysical earth models by establishing if and when there exist high direct functional correlation values between the oscillations of the earth gravity field taken at a model's low eigenfrequencies, and the earth seismicity expressed in seismic energies and seismic magnitudes. Classically in geophysics - like in many sciences - the Fourier Spectral Analysis (and its derivatives) that requires evenly spaced input data, is used. On the other hand, the Vaniček Spectral Analysis (pronounce van-knee-check), being a least squares spectral fit, treats records with gaps as well as fully populated series. The former technique yields power spectra from evenly sampled data, whilst the latter one estimates both variance- and power-spectra from virtually any numerical record. Using this property, I demonstrate for the first time in geophysics the negative effect that the generating of input-data, for the purpose of completing the time-series, has on the Fourier spectral analyses. To accommodate the problem on existing computers and to create non-distorted 8-sec and 32-sec filtered records from the original one-second data, I design a non-equidistant filter that applies Gaussian weights while accounting for missing data within the filtering step. So filtered, the records are then used in computing the least-squares spectra. I deduce a quantifier of the earth's seismic activity, as the average gravity-spectra magnitude in the low eigenfrequencies band, from one-day, and from one week of data. Statistically significant lunar synodic semi-monthly and solar semi-annual periodicities, as extracted from a decade-long series of diurnal average magnitudes, and coinciding with the current knowledge on "tidal triggering" of large earthquakes, are revealed for the first time in a global geophysical quantity. The quantifier provides a relative measure of change in gravity field oscillations as due to emissions of, mostly seismic, kinetic energy reflected in noise. The method is unique in its rigor, since it enables assessments of earth models from single-station (gravity) measurements, by using all global earthquakes above certain strength, i.e., regardless of their type, faulting mechanism, etc., and without preprocessing or post-processing to enhance and correct either raw gravity data or their spectra. As such, the method serves as a basis for a definition of different discriminatory criteria.