ADAPTIVE FILTERING OF SEISMIC ARRAY DATA ADVANCED ARRAY RESEARCH
Abstract
Adaptive multichannel prediction filtering has been completed on four data samples, and adaptive maximum-likelihood signal extraction has been done on one sample. Comparison of adaptive results with those obtained from processing the same data with stationary filters (nonchanging filters designed from correlation-function estimates) shows that the adaptive filters approach the stationary filters as k sub s (the rate-of-convergence parameter in the adaptive algorithm) approaches 0. For larger values of k sub s, adaptive prediction-error filtering does better than stationary filters on nontime-stationary data, but stationary filters are better on data samples which appear to be time-uniform. The performance of an adaptively designed maximum-likelihood filter was shown to be essentially equivalent to that of a maximum-likelihood filter which was conventionally designed from correlation-function estimates.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 18, 1967
- Accession Number
- AD0821909
Entities
People
- Aaron H. Booker
- John P. Burg
- Ronald J. Holyer
Organizations
- Texas Instruments