White Noise Estimators for Seismic Data Processing in Oil Exploration.

摘要

This paper develops a Kalman filtering approach to obtaining optimal smoothed estimates of the so-called reflection coefficient sequence. This sequence contains important information about subsurface geometry. Our theoretical problem is one of estimating white plant noise for the systems. By means of the equations which are derived herein, it is possible to compute fixed-interval, fixed-point, or fixed-lag optimal smoothed estimates of the reflection coefficient sequence, as well as respective error covariance-matrix information. Our optimal estimators are compared with an ad hoc prediction error filter, which has recently been reported on in the geophysics literature.