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| Numeric implementation of
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Wavefield reconstruction for zero-offset migration based on the
one-way wave-equation is performed by recursive phase-shift in depth
starting with data recorded on the surface as boundary conditions. In
this configuration, the imaging condition extracts the image as time
from the reconstructed wavefield at every location in
space. Thus, the surface data need to be extrapolated backward in time
which is achieved by selecting the appropriate sign of the phase-shift
operation (which depends on the sign convention for temporal Fourier
transforms):
|
(1) |
In equation 1,
represents the acoustic wavefield at
depth for a given frequency at all positions in space ,
and
represents the same wavefield extrapolated to
depth . The phase shift operation uses the depth wavenumber
which is defined by the single square-root (SSR) equation
|
(2) |
where
represents the spatially-variable slowness at depth
level . Equations 1-2 describe wavefield extrapolation
using a pseudo-differential operator, which justifies our use of
laterally-varying slowness
. As indicated earlier, the image is
obtained from this extrapolated wavefield by selection of time ,
which is typically implemented as summation of the extrapolated
wavefield over frequencies:
|
(3) |
Phase-shift extrapolation using wavenumbers computed using
equations 1 and 2 is not feasible in media with lateral
variation. Instead, implementation of such operators is done using
approximations implemented in a mixed space-wavenumber domain
(Huang et al., 1999; Stoffa et al., 1990; Ristow and Ruhl, 1994). A
brief summary the mixed-domain implementation of the split-step
Fourier (SSF) operator is presented in Appendix A.
For velocity analysis, we assume that we can separate the total
slowness
into a known background component
and an
unknown component
. With this convention, we can linearize
the depth wavenumber relative to the background slowness
using a truncated Taylor series expansion
|
(4) |
where the depth wavenumber in the background medium characterized by
slowness
is
|
(5) |
Here,
represents the spatially-variable background
slowness at depth level . Using the wavenumber linearization from
equation 4, we can reconstruct the acoustic wavefields in the
background model using a phase-shift operation
|
(6) |
We can represent wavefield extrapolation using a generic solution to
the one-way wave-equation using the notation
. This
notation indicates that the wavefield
is
reconstructed from the wavefield
using the background
slowness
. This operation is repeated independently for all
frequencies . A typical implementation of zero-offset
wave-equation migration uses the following algorithm:
A seismic image is produced using migration by wavefield extrapolation
as follows: for each frequency, read data at all spatial locations
; then, for each depth, sum the wavefield into the image at that
depth level (i.e. apply the imaging condition) and then reconstruct
the wavefield to the next depth level (i.e. perform wavefield
extrapolation). The ``-'' sign in this algorithm indicates that
extrapolation is anti-causal (backward in time), and the factor ``2''
indicates that we are imaging data recorded in two-way traveltime with
an algorithm designed under the exploding reflector model. Wavefield
extrapolation is usually implemented in a mixed domain
(space-wavenumber), as briefly summarized in Appendix A.
The wavefield perturbation
caused at depth by a
slowness perturbation
at depth is obtained by
subtraction of the wavefields extrapolated from to in the
true and background models:
Here,
and
correspond to a given depth level
and frequency . A similar relation can be applied at all depths
and all frequencies.
Equation 7 establishes a non-linear relation between
the wavefield perturbation
and the slowness perturbation
. Given the complexity and cost of numeric optimization based
on non-linear relations between model and wavefield parameters, it is
desirable to simplify this relation to a linear relation between model
and data parameters. Assuming small slowness perturbations, i.e. small
phase perturbations, the exponential function
can be linearized using the approximation
which is valid for small values of the phase
. Therefore the wavefield perturbation
at depth
can be written as
Equation 8 defines the zero-offset forward scattering operator
, producing the scattered
wavefield
from the slowness perturbation
, based
on the background slowness
and background wavefield
at a given frequency . The image perturbation at depth
is obtained from the scattered wavefield using the time
imaging condition, similar to the procedure used for imaging in the
background medium:
|
(9) |
Given an image perturbation
, we can construct the scattered
wavefield by the adjoint of the imaging condition
|
(10) |
for every frequency . Then, the slowness perturbation at depth
and frequency caused by a wavefield perturbation at depth
under the influence of the background wavefield at the same depth
can be written as
Equation 11 defines the adjoint scattering operator
, producing the slowness
perturbation
from the scattered wavefield
, based
on the background slowness
and background wavefield
. A typical implementation of zero-offset forward and adjoint
scattering uses the following algorithms:
The forward zero-offset wave-equation MVA operator follows a similar
pattern to the implementation of the downward continuation operator:
for each frequency and for each depth, read the slowness perturbation
at all spatial locations , then apply the scattering
operator (
) given equation 11 to the slowness perturbation and
accumulate the scattered wavefield for downward continuation; then,
apply the imaging condition (
) producing the image perturbation
at depth and then reconstruct the scattered wavefield
backward in time using the wavefield extrapolation operator (
)
to the next depth level.
The adjoint zero-offset wave-equation MVA operator also follows a
similar pattern to the implementation of the downward continuation
operator: for each frequency and for each depth, reconstruct the
scattered wavefield forward in time using the wavefield extrapolation
operator (
) to the next depth level, then apply the adjoint of
the imaging condition (
) by adding the image to the scattered
wavefield and then apply the adjoint wavefield scattering operator
(
) to obtain the slowness perturbation .
Both forward and adjoint scattering algorithms require the background
wavefield, , to be precomputed at all depth levels, although more
efficient implementations using optimal checkpointing are possible
(Symes, 2007).
Scattering and wavefield extrapolation are implemented in the mixed
space-wavenumber domain, as briefly explained in Appendix A.
|
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| Numeric implementation of
wave-equation migration velocity analysis operators | |
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Next: Survey-sinking migration and velocity
Up: Wave-equation migration and velocity
Previous: Wave-equation migration and velocity
2013-08-29