Abstract:The automatic velocity pickup technique that is based on the combination of joint -side confidence concept with graphic theory brings good result in processing the well continuous seismic data; however,it fails to choose proper interval velocity factor to extrapolate velocity curves in the cases of low S/N ratio, uncontinuous primary reflections,velocity inversion and seismic data from uplifted area.In order to overcome this difficulty, velocity spectra are recognized and classified step by step with the use of multi-step statistical judgement method;and corresponding interval velocity factor and direction factor are chosen in terms of differ; nt geological types, In the light of the tree structure characteristics, the spcetra can be classed into simple and complex ones, Furthermore, multiple waves may be muted by recognizing statistically the distributions of primary waves and multiple waves in spectra.The multi -step statistical judgzment method can effectively simulate the abilities of manual velocity pickup in recognizing and classifying the spectra in the light of the macro characteristics of velocity spectra; then the reliability of velocity pickup and the adaptability to complex geological condition can be improved obviously.This method can be formularized as; manual velocity pickup experience= joint -side confidence+graphic thzory+pattern recognition.
收稿日期: 1987-11-23
引用本文:
柴振彝, 许文龙. 模式识别方法在速度自动拾取中的应用[J]. 石油地球物理勘探, 1988, 23(5): 590-598.
Chai Zhenyi, Xu wenlong. The application of pattern recognition to automatic velocity pick up. OGP, 1988, 23(5): 590-598.