Reflector imaging using trial reflector and crosscorrelation: Application to fracture imaging for sonic data

Geophysics ◽  
2016 ◽  
Vol 81 (6) ◽  
pp. S433-S446 ◽  
Author(s):  
Nobuyasu Hirabayashi

I have developed two high-resolution imaging methods that do not require a priori information on the structural dip. The dip information is often necessary to image complex structures using Kirchhoff migration by selecting only the constructively interfering parts of waveforms, especially for data with limited acquisition geometry. However, such dip information is not generally available. The methods that I evaluated use a trial reflector, which is defined for each image point and source-receiver pair, to search for the true geologic reflector. The coincidence of these reflectors is judged by a coherency analysis of event signals for the trial reflector using the crosscorrelations, and the coherency is converted to a weight. The weight is combined with the stacking methods of waveform samples in migration. In the first method, a waveform sample summed at an image point for a source-receiver pair is obtained by the common-depth-point stack of array data for the trial reflector. In the second method, a waveform sample of a source-receiver pair at the traveltime of the reflected ray for the trial reflector is smeared in the Fresnel zone computed for the trial reflector. My methods were applied to image fractures for sonic data, whose frequency range is centered approximately 8 kHz, and they provide higher resolution images than those given by conventional Kirchhoff migration.

2000 ◽  
Vol 54 (5) ◽  
pp. 721-730 ◽  
Author(s):  
S. S. Kharintsev ◽  
D. I. Kamalova ◽  
M. Kh. Salakhov

The problem of improving the resolution of composite spectra with statistically self-similar (fractal) noise is considered within the framework of derivative spectrometry. An algorithm of the numerical differentiation of an arbitrary (including fractional) order of spectra is produced by the statistical regularization method taking into account a priori information on statistical properties of the fractal noise. Fractal noise is analyzed in terms of the statistical Hurst method. The efficiency and expedience of this algorithm are exemplified by treating simulated and experimental IR spectra.


Sign in / Sign up

Export Citation Format

Share Document