processing ali (1)

8/13/2019 Processing Ali (1)

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By:AliMisaghi

Why seismic processing ?

Processing Steps


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By:AliMisaghi Whats a seismic trace?

Sandstone

Coal

Carbonate

Salt

Shale

*

S(t)

*

R(t) Seismic trace+ Noise (t)=Rf(t)

Filtering

Stacking

.

.

.

Deconvolution


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*

g(t)

f(t)

*

g(t)

f(t)
http://www.eas.asu.edu/~spanias/convolution_demo.htm


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Wave propagation


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Land dataMarine data

Split shot gather


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0.0

0.2

0.4

0.6

0.8

1.0

0 500 1000 1500 2000 2500

X (m)

T

(s)

Direct

Ground roll

Head wave (refraction)First multiple

Primary

R1 R2

Seismic eventsNon-primary events


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Primary

Earths surface

Subsurface reflector

S R1

Ground rollDirect P-wave

R2

Head wave (refraction)

First multiple

Seismic events

Non-primary events


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CDP Fold =Number of receivers xreceiver interval

2 xshot interval


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CDP gather NMO Stack


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Migration

The goal of migration is to make thestacked section appear similar to the

geologic cross-section

Oz Yilmaz


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A step in seismicprocessingin which reflections in seismicdata

are moved to their correct locations in the x-y-time space of

seismicdata, including two-way traveltimeand position relative to

shotpoints
http://www.glossary.oilfield.slb.com/Display.cfm?Term=seismichttp://www.glossary.oilfield.slb.com/Display.cfm?Term=processinghttp://www.glossary.oilfield.slb.com/Display.cfm?Term=seismichttp://www.glossary.oilfield.slb.com/Display.cfm?Term=seismichttp://www.glossary.oilfield.slb.com/Display.cfm?Term=traveltimehttp://www.glossary.oilfield.slb.com/Display.cfm?Term=traveltimehttp://www.glossary.oilfield.slb.com/Display.cfm?Term=seismichttp://www.glossary.oilfield.slb.com/Display.cfm?Term=seismichttp://www.glossary.oilfield.slb.com/Display.cfm?Term=processinghttp://www.glossary.oilfield.slb.com/Display.cfm?Term=seismic


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m

n

Zn Zm


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Typical ProMax flow for velocity analysis.


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Examining the normal moveout equation, it is possible toanalyze NMO velocities by plotting reflections in T2 X2space


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Concept of Constant Velocity Stack as an aid to stackingvelocity estimation.


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One method to determine stacking velocity is to use aConstant Velocity Stack (CVS) for several CDP gathers


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Same CVS panel of traces as before switching to variabledensity color for the traces to utilize dynamic range


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Same as previous color panels with velocity range nowhalved to better pick correct velocities


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Another term for Normal Moveout Equation.


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Options in the ProMax Velocity Analysis Routine.


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Demonstration of the velocity spectra


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CDP gather with NMO applied (center) surrounded by panelshaving progressively lower velocity (left) or higher velocity.


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From left to right are panels for Semblance, Gather, DynamicStack, Flip Stacks, and Velocity Function Stack.


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The ProMax routine Velocity Analysis has it all from left toright: velocity spectra, interactive cursor with CDP gather,dynamic stack, and a variation on CVS


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The Semblance Panel shows the semblance plot, the pickedvelocity function, guide functions, and the interval velocitycomputed from the picked function.


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Dix equation converts stacking velocities to interval velocities.

Ho e e o get RMS elocities one can contin e to


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By:AliMisaghi However, you get RMS velocities, one can continue to

calculate interval velocities, interval thicknesses, and averagevelocities.


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Remaining three panels in Velocity Analysis routine.


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Use of ProMax routine Velocity Viewer and Editor

i


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A common problem with stacking is residual NMO on theCDP gathers resulting from imperfect velocity specification.

i


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Example of the data/velocity Interleave Display usingLandmarks SeisCube program.

i


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Progressive Mute Analysis

i


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Prestack CDP gather with a horizon plotted along an eventthat is not perfectly flattened by NMO; other causes might bestatics, noise, and/or lithology that is affecting the phase.

i


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hi


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hi


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ProMax routine CDP/Ensemble Stack vertically stacksinput ensembles of traces.

hi


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Definition of multiplies as it applies to processingseismic reflection data using ProMax.

hi


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Example of a surface multiple on left in red and intrabedmultiple on the right in blue.

hi


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Comparison of short-path and long-path multiples.

hi


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Conceptual abstraction of the TauP domain

hi

O i i i i fl ti d t i t t d i


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Organizing seismic reflection data into ray-parameter domainhas certain advantages that are elaborated here.

hi


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Working definition of the Radon Filter commonlyused for multiple suppressionworking in the intercept-time (T) / ray parameter (p) or slowness domain.

hi


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Use of the radon transform for the removal of multiples bydiscriminating on the basis of moveouthere no rejection.


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hi


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More on the use of the Radon Filter.

ghi


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ghi


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Migration

ghi Migration


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By:AliMisag Migration

Migration is an inversion operation involving

rearrangement of seismic information elements so that

reflections and diffractions are plotted at their truelocations.

R.E Sheriff

The goal of migration is to make the stacked sectionappear similar to the geologic cross-section

Oz Yilmaz

ghi


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Unmigrated

ghi


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Migrated

ghi


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Migration

Collapses diffractions

Corrects for dip

Moves dipping events in the updip direction

Removes effects of surface curvature

unties the bowties

ghi

Reconstructing the wavefield


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By:AliMisag Reconstructing the wavefield

ghi


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Constant velocity migration

ghi Schematic that shows the imaging problem for a simple

ti li


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anticline.

ghi Schematic that shows the imaging problem for a simple


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By:AliMisa

syncline.

ghi

Schematic that shows the imaging problem for a vertical fault


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By:AliMisa Schematic that shows the imaging problem for a vertical fault.

aghi

Schematic that shows the imaging problem for a 30-degree


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g g p gfault.

aghi Schematic that shows the imaging problem for a reef model.


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aghi


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Kirchoff migration (diffraction stacking)

Finite difference method

F-K migration

integral solution of wave equation

derivative solution of wave equation

Fourier domain solution of wave equation

Migration Methods

aghi


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By:AliMisa

Kirchoff Migration

(Diffraction Summation)For every point (x,z), collapse all energy from

hyperbola with vrms

AB

C O

t0

x

t

2

22

0

2 4

rmsv

xtt

aghi


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By:AliMisa

Kirchoff Migration

(Diffraction Summation)Factors to consider before summing energy in

diffraction:

Obliquity factorA cos

Spherical divergence factor

A 1/r

Wavelet shaping factor

phase correction

aghi

Migration collapses diffractions to


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By:AliMisa Migration collapses diffractions to

reveal structure

aghi

Migration collapses diffractions to


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By:AliMisa Migration collapses diffractions to

reveal structure

aghi


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By:AliMisa

Finite Difference Migration

Solving the wave equation by stepping down

discrete intervals from z=0

Downward continue wavefield to explodingreflector

Define an angle for width of cone for to be

included in migration for each pointwider cone more accurate

narrow cone faster, better approximations

aghi


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aghi

Migration steepens and mo es


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sintan a

Migration steepens and moves

dipping reflectors

Apparent dip in time section is related to true

dip:

(migrators equation)

aghi

Collapsing diffraction and relocating


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p g g

dipping surface

Diffraction D Apex P

Reflector B A

saghi

F K Migration


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By:AliMis F-K Migration

Events can be separated by

their dips in F-K space

Transform according to

migrators equation tan

a=sin

Advantage: very

computationally efficient!

Disadvantage: only works for

constant velocity (without

modifications that

compromise its efficiency)

saghi


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saghi Migration removes multiple-


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g p

branch reflections

Synclines

get broader Anticlines

get narrower

saghi

U t i th b ti


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By:AliMis Untying the bowties

saghi

Limitations of Migration


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By:AliMis Limitations of Migration

Insufficient spatial resolution will result in aliasing

2-D slice of 3-D wavefield (need 3-D migration!)

Edge effects

Coherent noise

Requires knowledge of velocity structure Time migration methods assume lateral velocity varies

slowly (otherwise need depth migration)

saghi


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saghi


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3-D Processing

Binning by common midpoints in cells on a

grid

Migration can be two stage 2-D migration(in-line direction, then cross-line direction)

or full 3-D wavefield solution

Most other processing operations areunchanged

Display is more difficult (and more fun!)

saghi


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By:AliMis

saghi

Why Deconvolution?


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By:AliMis Why Deconvolution?

Decreases ringing

Increases resolution

Improves appearance of stacked section and

makes it easier to interpret

Section is more like the earth and less like the

seismic source

Can remove multiples

saghi

Convolutional model of a


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By:AliMi Convolutional model of a

seismogram

s=w*e+n

source wavelet

11v

22v

33v

44v

55v

Earth response function seismogram

*

(+noise)

=

saghi

Spiking Filter


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By:AliMi Spiking Filter

Take existingwavelet andtransform to a unit

impulse (deltafunction)

Also calledwhitening because

it aims to create awhite spectrum

isaghi

Predictive Deconvolution


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By:AliMi Predictive Deconvolution

Deconvolution with a built-in time lag

Use to remove

Multiples

Bubble pulse

isaghi

Deconvolution Example


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By:AliMi Deconvolution Example

isaghi Raw gather decon Bandpassfiltered


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autocorrelograms

isaghi

R


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By:AliM Raw

gathers

isaghi


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After

decon

Misaghi


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Misaghi

Deconvolution


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Deterministic Inverse Filtering

Deghosting

Least Squares (Optimum) Filtering

Spiking filter

Wavelet shaping

Predictive Deconvolution

Misaghi

Convolutional model of a


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seismogram

s=w*e+n

One equation with 3 unknowns

How can we possibly find e?

We make assumptions:

e, nare white (random)

wis minimum phase

Misaghi


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w

e

s

Misaghi

Earth response Wavelet Seismogram


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Amplitud

e

Spectrum

Autocorre

lation

Amp

litude

Misaghi

Deterministic Deconvolution


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Assume that an operator f(t) exists such that

)()(*)( ttftw In the Fourier domain:

1)()( FW

f

w

i

f

i

w

eAF

eAW

)()(

)()(

wi

w eAF

)(

1)( so

and

)()(

)(/1)(

wf

wf AA

The inverse operator f(t) has opposite phase

and inverse amplitude spectrum from the

source wavelet w t

Misaghi

Deterministic Deconvolution


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By:AliM Deterministic Deconvolution

Assumptions:

1 source wavelet is minimum phase

2 noise is zero

3 wavelet is known

Not true, especially 2

In practice, the Fourier domain

implementation is not very good if

assumptions are not met

Other methods are more stable

Misaghi

Deghosting


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By:AliM Deghosting

Eliminate source & receiver ghosts byconsidering them as time delayed copies of

the source (and with known depths the time

delays are known) Alternatively, hydrophones and geophones

with different responses can be combined to

eliminate ghosting effects

Misaghi

Correlation


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By:AliM Co e at o

Autocorrelation

Cross-correlation

1,,1,01

)(1

0

Nkxx

N

xrkN

t

kttk

1,,1,01

),(

1

0

NkyxNyxg

kN

t

kttk

Misaghi

Wavelet Estimation


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In general, the source wavelet is unknown Source wavelet can be estimated from

seismogram alone assuming:

minimum phase waveletwhite earth response spectrum

ewx rrr * autocorrelation

(with white earth response)wx rrr 0

Autocorrelation of seismogram is the autocorrelation of

source wavelet (within a constant)

Misaghi

Optimum Weiner Filters


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By:AliM p

Want to find the optimum filter components fithat minimize the error

between the desired and actual outputs in a least-squares sense:

t

ttt xfdL 2

)(

)1(,,2,1,0,0

ni

f

L

i

By setting

so 022

it

t t

titt

i

xxfxdf

L

Recognizing the terms for auto- and cross-correlation,

ii grf

it

t t

titt xdxxf

or

Misaghi



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ii grf

Or, in matrix form,

1

2

1

0

1

2

1

0

0321

3012

2101

1210

nnnnn

n

n

n

g

g

g

g

f

f

f

f

rrrr

rrrr

rrrr

rrrr

The autocorrelation matrix is a Toeplitz matrix, and can be

inverted by Levinson recursion

are called the normal equations

Misaghi



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p

1

2

1

0

1

2

1

0

0321

3012

2101

1210

nnnnn

n

n

n

g

g

g

g

f

f

f

f

rrrr

rrrr

rrrr

rrrr

The giterms are the cross-correlation of the desired wavelet

with the input wavelet (seismogram).

0

0

01

1

2

1

0

0321

3012

2101

1210

nnnn

n

n

n

f

f

ff

rrrr

rrrr

rrrrrrrr

In the case of spiking deconvolution, the normal equations

take the form

Misaghi

Wavelet Processing


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By:AliM g

Attempt to shift source wavelet to someother known wavelet, to accomplish one or

more of:

Reduce variation of source (between shots,between receivers)

Shift to another known wavelet

e.g., hydrophone response to matchseismometer

Separate wavelet and earth response more

clearly

Misaghi

Wavelet Processing


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Misaghi

Wavelet Processing


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g

Transform to zero phase and broaden spectrumIncrease resolution


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Misaghi

Real data91o


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1) Shots : 2 548

2) Minimum phase

3) Traces have been resampled (2ms >4ms) and decimated (384 > 192)

4) Fk filter

5) Geometry has been applied

6) Velocity file is available(By Geco)

12.5 m25 m

7.5 m 8.5 m

Misaghi Real data work flow

S ti


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Check the mute

Velocity Analysis

NMO

Stack

Sorting

Pick mute

True Amplitude Recovery

Deconvolution

Velocity Manipulation

Migration

Demultiple

Misaghi

Real data

P j t lt


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-A report:-Explanation of the processing steps with proper

and related snap shots(Mute, TAR, Decon, NMO,

Demultipling, Stacking, Migration,etc

-Final results(a comparison study)

-Brute-stack section(s)

-Demultipled stack section(s)

-Migrated section(s)

Project results:

processing ali (1)

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