The FOCI™ method of depth migration

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Presentation transcript:

The FOCI™ method of depth migration Gary Margrave Saleh Al-Saleh Hugh Geiger Michael Lamoureux POTSI

Wavefield extrapolators and stability A stabilizing Wiener filter Outline Wavefield extrapolators and stability A stabilizing Wiener filter Dual operator tables Spatial resampling Post stack testing Pre stack testing FOCI

Wavefield Extrapolators The phase-shift extrapolation expression output wavefield Fourier transform of input wavefield

Wavefield Extrapolators The phase-shift operator wavelike evanescent

Wavefield Extrapolators The PSPI extension

Wavefield Extrapolators wavenumber

Wavefield Extrapolators wavenumber

Wavefield Extrapolators In the space-frequency domain where

Wavefield Extrapolators In the space-frequency domain imaginary real meters

Wavefield Extrapolators Back to the wavenumber domain wavenumber

Wavefield Extrapolators Back to the wavenumber domain wavenumber

Stabilization by Wiener Filter Two useful properties Product of two half-steps make a whole step. The inverse is equal to the conjugate in the wavelike region.

Stabilization by Wiener Filter A windowed forward operator for a half-step Solve by least squares

Stabilization by Wiener Filter is a band-limited inverse for Both have compact support Form the FOCI™ approximate operator by FOCI™ is an acronym for Forward Operator with Conjugate Inverse.

Properties of FOCI operator Let Then

Properties of FOCI operator determines phase accuracy. determines stability. Empirical observation:

Properties of FOCI operator Amount of evanescent filtering is inversely related to stability

Operator tables Since the operator is purely numerical, migration proceeds by construction of operator tables.

Operator tables We construct two operator tables for small and large h. The small h table is used most of the time, with the large h being invoked only every nth step.

Operator Design Example

Improved Operator Design

Spatial Resampling Wavenumber Frequency Wavelike

In red are the wavenumbers of a 7 point filter Spatial Resampling Frequency In red are the wavenumbers of a 7 point filter Wavenumber

Spatial Resampling Frequency Downsampling for the lower frequencies uses the filter more effectively

Spatial resampling is done in frequency “chunks”.

Run Time Experiment

Run Times log-log Scale PS slope 1.07 FOCI slope 1.03 FOCI slope 1.05 Slopes for last three points

Phase Shift Impulse Response

FOCI Impulse Response nfor=7, ninv=15, (21 pt), no spatial resampling

FOCI Impulse Response nfor=7, ninv=15, (21 pt), with spatial resampling

Marmousi Velocity Model

Exploding Reflector Seismogram

FOCI Post-Stack Migration nfor=21, ninv=31, nwin=0

FOCI Post-Stack Migration nfor=21, ninv=31, nwin=51

FOCI Post-Stack Migration nfor=21, ninv=31, nwin=21

FOCI Post-Stack Migration nfor=7, ninv=15, nwin=7

Marmousi Velocity Model

FOCI Pre-Stack Migration nfor=21, ninv=31, nwin=0, deconvolution imaging condition

FOCI Pre-Stack Migration nfor=21, ninv=31, nwin=0, deconvolution imaging condition

FOCI Pre-Stack Migration Shot 30

FOCI Pre-Stack Migration Shot 30

FOCI Pre-Stack Migration Stack +50*Shot 30

Detail of Pre-Stack Migration

Marmousi Reflectivity Detail

Marmousi Velocity Model

FOCI Pre-Stack Migration Velocity model convolved with 200m smoother

FOCI Pre-Stack Migration Velocity model convolved with 400m smoother

FOCI Pre-Stack Migration Exact Velocities

FOCI Pre-Stack Migration Velocities smoothed over 200m

FOCI Pre-Stack Migration Velocities smoothed over 400m

Detail of Pre-Stack Migration Exact Velocities

Detail of Pre-Stack Migration Velocities smoothed over 200m

Detail of Pre-Stack Migration Velocities smoothed over 400m

Run times Full prestack depth migrations of Marmousi on a single 2.5GHz PC using Matlab code. 20 hours for the best result 1 hour for a usable result

Conclusions Explicit wavefield extrapolators can be made local and stable using Wiener filter theory. The FOCI method designs an unstable forward operator that captures the phase accuracy and stabilizes this with a band-limited inverse operator. Reducing evanescent filtering increases stability. Spatial resampling increases stability, improves operator accuracy, and reduces runtime. The final method appears to be ~O(NlogN). Very good images of Marmousi have been obtained.

Research Directions Better phase accuracy. Extension to 3D. Extension to more accurate wavefield extrapolation schemes. Migration velocity analysis. Development of C/Fortran code on imaging engine.

A US patent application has been made for the FOCI process. Acknowledgements We thank: Sponsors of CREWES Sponsors of POTSI NSERC MITACS PIMS A US patent application has been made for the FOCI process.

Detail of Pre-Stack Migration

FOCI Pre-Stack Migration nfor=21, ninv=31, nwin=0, deconvolution imaging condition

FOCI Pre-Stack Migration nfor=21, ninv=31, nwin=0, deconvolution imaging condition