Determination of quality factor (Q) in reflection seismic data

2013 ◽  
Author(s):  
W. O. Raji ◽  
A. Rietbrock
Materials ◽  
2020 ◽  
Vol 13 (21) ◽  
pp. 4708
Author(s):  
Beatriz Sisniega ◽  
Jon Gutiérrez ◽  
Virginia Muto ◽  
Alfredo García-Arribas

The resonance quality factor Q is a key parameter that describes the performance of magnetoelastic sensors. Its value can be easily quantified from the width and the peak position of the resonance curve but, when the resonance signals are small, for instance when a lot of damping is present (low quality factor), this and other simple methods to determine this parameter are highly inaccurate. In these cases, numerical fittings of the resonance curves allow to accurately obtain the value of the quality factor. We present a study of the use of different expressions to numerically fit the resonance curves of a magnetoelastic sensor that is designed to monitor the precipitation reaction of calcium oxalate. The study compares the performance of both fittings and the equivalence of the parameters obtained in each of them. Through these numerical fittings, the evolution of the different parameters that define the resonance curve of these sensors is studied, and their accuracy in determining the quality factor is compared.


2021 ◽  
Vol 51 (2) ◽  
pp. 129-139
Author(s):  
Mehdi Nouri DELOUEI ◽  
Mohammad-Reza GHEITANCHI

Among important parameters in simulation of earthquake data in high frequencies are the high frequency spectral amplitude decay and the Quality factor. Amplitude spectral decay is determined by the Kappa parameter (K) and the Quality factor (Q) which is usually expressed by a power relation of frequency (f) as Q = Q0 f n, where Q0 is Q at 1 Hz. The 2017 Sarpol-e-Zahab earthquake with magnitude Mw = 7.3 in Kermanshah province near the Iran-Iraq border caused extensive destruction and heavy human loss. Thus, the study of different aspects of this event is of high importance. In this paper an attempt is made to partly explain the attenuation properties of this region in Zagros suture zone by determining the Kappa and the Quality factors in this region. In this study, accelerograph records of aftershocks of the above-mentioned earthquake have been analysed. The best linear fit for the Kappa, based on the distance (R) in km, is estimated as: K = 0.0005 R + 0.034 for the horizontal component, which exhibits increase with increasing epicentral distance. The correlation of the Quality factor was also found as Q = 88.6 f 0.8, which is in accordance with an active tectonic region.


2011 ◽  
Vol 19 (02) ◽  
pp. 155-179 ◽  
Author(s):  
JINGHUAI GAO ◽  
SENLIN YANG ◽  
DAXING WANG ◽  
RUSHAN WU

In this paper, we derive an approximate equation combining the quality factor Q, the travel time of a wave, and the variation of the instantaneous frequency (IF) at the envelope peaks of two successive seismic wavelets, along the wave-propagating direction, based on the theory of one-way wave propagation in a 1D viscoelastic medium. We then propose a method (called the WEPIF method) to estimate Q by measuring the variations of the wavelet envelope peak IF (WEPIF) with the travel time of seismic wavelet. For zero-offset VSP data and poststack seismic data, we describe how to implement the WEPIF method in detail. A test on synthetic VSP data shows that the WEPIF method is less sensitive to interference from the reflector than the logarithm spectral ratio and the centroid frequency shift methods. Applied to field VSP data, the WEPIF method gives a Q-curve with nearly the same distribution as the results from a known well. Applied to poststack seismic data, it produces a Q-profile that indicates an intense absorption zone corresponding to the excellent gas-bearing reservoir. This allows us to predict a potential high-productivity gas well. Drilling confirmed this prediction. The WEPIF method can be applied to poststack seismic data and zero-offset VSP data.


Geophysics ◽  
1989 ◽  
Vol 54 (5) ◽  
pp. 659-661 ◽  
Author(s):  
Ali A. Nowroozi

Over three decades ago, Dix (1955) derived an approximate equation for the determination of interval velocity from observed reflection seismic data. Assuming a stack of m horizontal layers, with interval velocities [Formula: see text], layer thicknesses [Formula: see text], j = 1, m, and near‐vertical raypaths, Dix (1955) showed that [Formula: see text]where [Formula: see text] and [Formula: see text] are the two‐way vertical times and [Formula: see text] and [Formula: see text] are the root‐mean‐square (rms) velocities to interfaces j + 1 and j, respectively.


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