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Seismic inverse Q filtering is a data processing technology for enhancing the resolution of reflection seismology images. Q is the anelastic attenuation factor or the seismic quality factor, a measure of the energy loss as the seismic wave moves. ==Basics== Seismic inverse Q-filtering employs a wave propagation reversal procedure that compensates for energy absorption and corrects wavelet distortion due to velocity dispersion.〔Wang 2008, From Preface.〕 By compensating for amplitude attenuation with a model of the visco-elastic attenuation model type, seismic data can provide true relative-amplitude information for amplitude inversion and subsequent reservoir characterization. By correcting the phase distortion due to velocity dispersion, seismic data with enhanced vertical resolution can yield correct timings for lithological identification.〔Wang 2008, From the back cover〕 However, Wang's outline of the subject is excellent and to follow his path, inverse Q filtering can be introduced based on the 1-D one-way propagation wave equation. He introduce this equation:.〔Wang 2008, p.60-62. chapter 4〕 : where U(r,w) is the plane wave of radial frequency w at travel distance r, k(w) is the wavenumber and i is the imaginary unit. Reflection seismograms record the reflection wave along the propagation path r from the source to reflector and back to the surface. With this approach Wang assumes that the plane wave U(r,w) has already been attenuated by a Q filter through travel distance r. We must have this in mind when we go to the step of finding a solution of (1.1). It is necessary that the initial U(r,w) either is already created by a forward synthetic Q-filtering process or taken directly from seismic surface data. Wang has introduced this concept in chapter 5 in his book.〔Wang 2008, chapter 5.3 Forward Q-filtering〕 I think it is necessary to have this in mind also when the inverse theory is developed. Equation (1.1) has an analytical solution given by : 抄文引用元・出典: フリー百科事典『 ウィキペディア(Wikipedia)』 ■ウィキペディアで「Seismic inverse Q filtering」の詳細全文を読む スポンサード リンク
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