White Noise Estimators for Seismic Data Processing in Oil Exploration.

Abstract

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.

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Document Details

Document Type
Technical Report
Publication Date
Jul 01, 1976
Accession Number
ADA032753

Entities

People

  • Jerry M. Mendel

Organizations

  • University of Southern California

Tags

Communities of Interest

  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • California
  • Coefficients
  • Covariance
  • Data Processing
  • Equations
  • Equations Of State
  • Estimators
  • Filters
  • Geometry
  • Geophysics
  • Information Science
  • Intervals
  • Linear Systems
  • New York
  • Optimal Estimators
  • Statistical Algorithms
  • White Noise

Fields of Study

  • Engineering

Readers

  • Approximation Theory.
  • Seismology