Sin t

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Flexible 3-D seismic survey design
Gabriel Alvarez Stanford University
Victor Pereyra, Laura Carcione Weidlinger
Associates Inc.
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Goal
Show with a simple 3-D example how to optimize
the design of a seismic survey such that it is
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Characteristics
Flexible allow survey parameters to change in a
systematic way.
Exhaustive exploits all subsurface information
as well as logistic and economic constraints.
Dips, depths, velocities, presence of fractures,
etc
Available recording equipment, maps of surface
obstacles, etc.
Illumination-based uses target illumination
as the primary design consideration.
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Design Example
Single depth-variable target 300-3000 m
Land prospect.
Sources are expensive.
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Subsurface model
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Subsurface model
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Target reflector
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The standard approach
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Target parameters

• Minimum depth 300 m

• Maximum depth 3000 m

• Maximum dip 60 degrees

• Minimum velocity 2000 m/s

• Maximum frequency 60 Hz

• Minimum trace density 240000 tr/km2

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Survey recording patch
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Other parameters
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Problem Maximum-minimum offset
MMO640 m
Some bins have minimum offset larger than the
target depth.
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Alternatives to solve the problem

• Halve the receiver- and the source-line intervals.

MMO320 m. Good. But
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Alternatives to solve the problem
2. Halve the receiver and source-line interval
and use a rectangular bin
Good. Now the source density doesnt change. But
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Why the need to compromise?
Because we are using the same parameters for the
entire survey area.
We can use different parameters in
different parts of the survey the target is
shallow only in a small region.
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The proposed approach subsurface-based design
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The method in a nutshell
Use a subsurface model to trace rays to the
surface at uniform opening and azimuth angle.
Record the emergence position of the rays at the
surface.
Compute locally optimum spatially-varying
geometry.
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Spatially-varying geometry
1. Maintain a standard geometry but allow
changes in the parameters (line intervals).
2. Maintain a standard receiver template but
allow sources in arbitrary positions.
3. Allow sources and receivers to be in
arbitrary positions.
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Model space dimensionality
Fixed orthogonal geometry
Only six parameters describe each geometry.
Receiver interval Source interval Receiver line
interval Source line interval Number of
receivers/line Number of receiver lines/patch.
Each parameter has a limited number of acceptable
values (integer optmization).
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Assign source-receiver positions
For each geometry based on ray emergence
position being closer to a source or receiver
line.
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Preprocessing
For each trial geometry

• Compute total distance that the rays were moved.

• Compute shot and receiver density, fold, aspect
• ratio, offsets, etc.

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Fitness function
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Objectives and constraints
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Splitting the survey area
Deep zone depths gt700 m (gt85 km2)
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Shallow zone
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Results for shallow zone
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Mid zone
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Results for mid zone
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Deep zone
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Results for deep zone
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Summary of optimum geometry
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Stats of optimum geometries
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A look at the logistics
Logistics are not compromised because

• for each source (salvo) the receiver template
• is standard orthogonal,

• the receiver-line interval in zone 2 is half
  that
• in zone 3 and in zone 1 is half that in zone 2,

• the sources are along continuous lines as usual.

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The bottom line

• The geometry is locally optimum from the
• illumination point of view.

• The average source density is about half
• than with the standard approach.

• Logistics are not compromised.

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Additional remarks
1. We emphasized reflector depth, but we can also
use reflector dip, curvature, etc.
2. Different geometries may be combined to form
the final geometry.
3. Can estimate the local acquisition effort.
This will help in dealing with surface
obstacles.
4. Surface maps should be used at the design
stage to further constrain the position of
sources and receivers.
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Conclusions
The standard seismic survey design is too rigid
because of the assumption that the subsurface is
featureless.
Relaxing this assumption allows the design to be
flexible, illumination based, locally optimum in
terms of the required acquisition effort.
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Thank you for your attention. I will be happy to
entertain your questions.
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Survey recording patch

• Number of receiver lines 8

• Receivers per line 300

• Fold 24 (6 inline x 4 cross-line)

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Constraints in each zone
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Trial geometry parameters
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Stats of optimum geometries
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Shallow zone
Trial geometry parameters
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Mid zone
Trial geometry parameters
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Deep zone
Trial geometry parameters
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Future work
Short term
Compute illumination maps, fold charts,
geometry layout maps, etc.
Mid term
Handle multiple targets, different geometries,
surface maps, other types of targets, etc. Work
with real data.
Long term
Sensitivity analysis on errors in the initial
model.
Explicitely consider spatial sampling as a
constraint.
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Acknowledgments
My deepest appreciation to Dr. Victor Pereyra and
Laura Carcione of Weidlinger Associates for
allowing me to use the Integra software for model
building and ray tracing.