尺度匹配方法在井震联合重建和多次波衰减中的应用


Autoria(s): 刘贺
Contribuinte(s)

刘洪

Data(s)

31/05/2009

Resumo

Scale matching method means adjusting information with different scale to the same level. This thesis focuses on scale unification of information with different frequency bandwidth. Well-seismic cooperate inversion is an important component of reservoir geophysics; multiple prediction & subtraction is a development of multiple attenuation in recent years. The common ground of these two methods is that they both related to different frequency bandwidth unification. Well log、cross-hole seismic、VSP、3D seismic and geological information have different spatial resolution, we can decrease multi-solution of reservoir inversion and enhance the vertical and lateral resolution of the geological object by integrate those information together; Compare the predicted multiple generated by SRME with the real multiple, we find the predicted multiple convolutes at least one wavelet more, which brings frequency bandwidth difference between them. So the subtraction method also relates to multi-scale information unification. This thesis gives a method of well constrained seismic high resolution processing basing on auto gain control modulation. It uses base function method which utilizes original well-seismic match result as initial condition and processed seismic trace as initial model to extrapolate the high frequency information of the well logs to the seismic profiles. In this way we can broaden the bandwidth of the seismic and make the high frequency gain geological meaning. In this thesis we introduce the revised base function method to adaptive subtraction and verify the validity of the method using models. Key words: high frequency reconstruction, scale matching, base function, multiple, SRME prediction & subtraction

Identificador

http://159.226.119.211/handle/311031/1482

http://www.irgrid.ac.cn/handle/1471x/174377

Idioma(s)

中文

Fonte

尺度匹配方法在井震联合重建和多次波衰减中的应用.刘贺[d].中国科学院地质与地球物理研究所,2009.20-25

Palavras-Chave #高频重建 #尺度匹配 #基函数 #多次波 #SRME预测相减
Tipo

学位论文