handout processing 1

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SEISMICDATAPROCESSING(PART I)

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• Improve the signal to noise ratio: e.g. by measuring ofseveral channels and stacking of the data (white noiseis suppressed).

• Obtain a higher resolution by adapting the waveformof the signals.

• Isolate the wanted signals (isolate reflections frommultiples and surface waves).

• Obtain information about the subsurface (velocities,reflectivity etc.).

• Obtain a realistic image by geometrical correction(Conversion from travel time into depth and correctionfrom dips and diffractions).

Processing of Reflection Data

3

Seismic Processing

4

• Usually geared to a particular type of application– Mostly CMP reflection processing;– Land or marine, 2D or 3D.

• Commercial:– ProMAX (Landmark);– Omega (Western Geophysical, marine);– Focus (Paradigm);– Amoco and almost every other company

have their own…– Vista (Seismic Image Soft)

• Universities:– Stanford Exploration Project;– Seismic UNIX (Colorado School of Mines);– FreeUSP (Amoco);– SIOSEIS (Scripts, marine);

Seismic Processing Systems

5Printing/storage

Seismic

Processing

Systems

6

CMP Processing Sequence

1. Demultiplex, Vibroseis Correlation, Gain Recovery.Conversion from file formats produced by field data loggers into

processing:

• SEG-Y, SEG-2.

• ProMax, Focus, Omega, SU, Vista, etc., internal formats.

2. Field Geometry.Assignment of source-receiver coordinates, offsets, etc. in

the trace headers.

3. Edit.Removal of bad traces (noisy channels, poorly planted

geophones, channels contaminated by power line noise,

etc.).

7

CMP Processing Sequence (Continued)

4. First Arrival Picking.• May be semi-automatic or manual.

• Required for generation of refraction static, models and for

designing the mutes.

5. Elevation Static.• Based on geometry information, compensates the travel-time

variations caused by variations in source/receiver elevations.

• Transforms the records as if recorded at a common

horizontal datum surface.

6. Refraction Static.• Builds a model for the shallow, low-velocity subsurface.

• Compensates travel-time variations caused by the shallow

velocities. 8


7. ‘Top’, ‘Bottom’, and ‘Surgical’ Mute.Eliminates (sets amplitude=0) the time intervals where strong

non-reflection energy is present: First arrivals, ground roll,airwave.

8. Refraction Static.• Compensates geometrical spreading.

• Based on a simple heuristic relation.

9. Trace Balance.• Equalizes the variations in amplitudes caused by differences

in coupling.

• In true-amplitude processing, replaced with surface-consistent deconvolution.

9

10. Deconvolution or Wavelet Processing.• Compresses the wavelet in time, attenuates reverberations.

• Converts the wavelet to zero-phase for viewing.

11. Gather, CMP Sort.

12. Moveout (Radon, τ-p, f-k) Filtering.Attenuates multiples, ground roll.

13. Velocity analysis.• For each of the CMP gathers, determines the optimal

stacking velocity.


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14. Dip Moveout (DMO) correction.• Transforms the records so that the subsequent NMO + stack

work well even in the presence of dipping reflectors.

15. Normal Moveout (NMO) correction.• Removes the effects of source-receiver separation from

reflection records.• Transforms the records as if recorded at normal incidence.

16. Residual statics.• Removes the remaining small travel time variations caused

by inaccurate statics or velocity model.


� Steps 13-16 above are usually iterated 3-5 times to produce accurate

velocity and residual statics models.

� Success of velocity analysis depends on the quality of DMO/NMO and

residual statics, and vice versa.

11

CMP Processing Sequence (continued)

17. CMP Stack.• Produces a zero-offset section.

• Utilizes CMP redundancy to increase the Signal/Noise ratio.• Can employ various normalization ideas, e.g., diversity

stack.

18. Migration.• Transforms the zero-offset time section into a depth image.

• Establishes correct extents and dips of the reflectors.

19. Frequency Filtering and Display.• Attenuates noise.

• Provides best display for interpretation.

12

Unspecified blocks contain mandatory or optionalinformation.

Initial Process

Schematic arrangement of a seismic field tape:

13

The principle of multiplexing is already discussed in the sectionmeasurement system. It is used when the capacities of the AD converter arenot sufficient to digitize and save all channels at the same time. This iscommon for older measurement systems or for measurements with a largetime window and a lot of channels per shot. The separate values of allchannels are sorted by samples and not by channels.

It is difficult toprocess the datain this form. It ismore convenientand illustrativewhen the data issorted by traces.

Demultiplexing (Sorting of The Data)

14

• To deal with seismic data and their processing it is helpful to know

something about the data formats which are used to store these data.

• Almost every program and every large oil company has developed their

own format. In the course of time several standards have been

developed, to make an exchange possible between the different

programs. The most important standards are:

– SEG-Y

– SEG-D

– SEG-2

• The other Formats SEG-D and SEG-2 are often used for the storage of

raw data. They are suitable for multiplex data and make it possible to

save traces with different lengths. e.g. the SEG2 format saves each shot

separately.

Demultiplexing (Sorting of The Data)

15

SEG stays for Society of Exploration Geophysicists. This is the mostimportant society of geophysicists and seismologists in the oilindustry.

The different formats are very similar. The most important standardtoday is the SEGY format. Every file consist of several parts. Thestandard describes which information is put where in the file :

Structure of The SEG-Y Format

16

Assignment of source-receiver coordinates, offsets, etc.

in the trace headers:• Determine Source and receiver position for

measured data.

• Calculate CMP position.

Field Geometry

17

Often, signal traces must be examined visually to detect

and correct or reject those errorneously recorded or

exceptionally noisy. For this purpose a compressed plot

is made off all records. Example of the former are blank

or “dead” traces, reversed polarity, signal clipping,

incorrect trace sequence, and errorneous recording time.

Trace Edit

18

Editing

19

Editing

20

Muting avoids noise wave contamination of reflections onsummed (stacked trace).

Trace Mute

21

Static corrections are applied to seismic data to compensate for the effects of

variations in elevation, weathering thickness, weathering velocity, or

reference to a datum. The objective is to determine the reflection arrival time

which would have been observed if all measurements had been made on a

(usually) flat plane with no weathering or low velocity layer present. These

corrections are based on up-hole data, refraction first-breaks, or event

smoothing.

Static Correction

22

Static Correction

Static Correction : The whole trace is corrected with the sametime shift.

• Objectives of static corrections :Adjust the seismic traces in such a way that the sourcesand receivers are present at one horizontal level. Toachieve this, the travel times of the separate traces arecorrected.

Dynamic Correction : Different time windows in the traceare corrected differently. This resultsin stretching and compression of theevents (e.g. NMO Correction).

23

Reference Diagram for Land StaticCorrections

24

Datuming

25

• Topographic Correction (elevation statics).

• “Up-hole”-correction using shots in borehole.

• Refraction statics : Corrections for weathered layer

– Delay-Time.

– Generalized reciprocal method (GRM).

– Diminishing residual matrices (DRM).

Methods for Static Correction

26

• Vertical aligning of the different elevations of sourcesand receivers.

• Shot-Static= (Elevation of source - Elevation of reference level) /

Velocity.

• Receiver-Static= (Elevation of receiver - elevation of the referencelevel) / Velocity.

• Correction time for a trace= Shot-Static + Receiver-Static.

Topographic Correction

27

• Subdivision of time shift for source and receiver.

• All traces with equal source are corrected for the time

shift of the specific source.

• All traces with equal receiver are corrected for the time

shift of the specific receiver.

• The statics correction is the sum of the corrections for

appropriate source and receiver.

Topographic Correction

28

Correction for the weathered (low velocity) layer (area

above water layer where pores are filled with air rather

than water).

“Uphole-Static”

• When a shot is fired, also the travel time to the surfaceis recorded and from this travel time, the velocity of theweathered layer can be estimated.

29

Correction for the weathered layer.

• Using the first breaks of a certain shot (refracted

energy) a model can be constructed for the weathered

layer (velocities and depth).

• When the distance between the receiver is too large,

sometimes supplementary refraction measurements are

carried out.

Refraction Statics

30

Methods to determine the velocity and depth of the

weathered layer using refractions.

• Delay-Time.

• GRM (generalized reciprocal method).

• DRM (diminishing residual matrices).

NO STATICSNO STATICS WITH STATICSWITH STATICS

32

Stack of Line without The Application ofStatics

33

Example Where ProMax Routine Made aStatic Solution FACTORS WHICH AFFECT AMPLITUDEFACTORS WHICH AFFECT AMPLITUDE

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• The amplitude of a seismic signal decays with

increasing travel time.

• To obtain a realistic image, this decay must be

compensated for.

• In general, it is difficult to describe this amplitude decay

analytically, so an approximation is usually made.

Amplitude Correction

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• Reflection and transmission at an interface.

• Geometrical spreading.

• Absorption.

• Receiver response.

• Measurement system

Loss of Amplitude

Loss of amplitude due to:

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• Individual large amplitudes dominate the processing.

• Reflections are difficult to recognize.

• Strong amplitude contrasts influence the digital filtering

(especially for large travel-times).

Problem for Data Processing OBJECTIVES OF GAINOBJECTIVES OF GAINSTRUCTURAL PROCESSING

(“AGC” or “TRACEWISE BALANCE”)

Best continuty

Events visable at all times

STRATIGRAPHIC PROCESSING

(“RELATIVE AMPLTUDES”)

Bright spots visible

Amplitudes proportional to reflectioncoefficients

GAIN 6

AMPLITUDE VARIATIONSAMPLITUDE VARIATIONS

SOLUTIONS:SOLUTIONS:

1.1. TracewiseTracewise balancebalance

All timesAll times

All tracesAll traces

2. Relative amplitude2. Relative amplitude

SystematicSystematic

Output proportional to reflectionOutput proportional to reflection

CoefficientsCoefficients

GAIN FUNCTIONS VARY WITH: TIME, RANGE, LATERALLYGAIN FUNCTIONS VARY WITH: TIME, RANGE, LATERALLY

GAIN 1040

• Trace equalization.

• AGC (“Automatic gain control”).

• Correction for the spherical divergence.

• Programmable gain functions

Methods to Preserve Amplitude Information

GAIN FUNCTION APPLICATIONGAIN FUNCTION APPLICATION

GAIN 11

GAIN FUNCTION APPLICATIONGAIN FUNCTION APPLICATION

GAIN 13

EXAMPLE OF LATERAL VARIATIONEXAMPLE OF LATERAL VARIATION

GAIN 1444

The simplest method is the normalization of the different

traces. All absolute values of a trace are summed and

compared with a reference value. A scaling factor is

determined from the difference between the summation

and the reference value, which is used to multiply all data

with.

Trace Equalization

45

Normalization of amplitude for a certain time sample in acertain time window (not for the whole trace).

Advantage:• All traces are more equal which is needed for further

processing.(Stacking: summation of different traces)

• Amplification of Amplitudes for larger travel times.

Disadvantage:• Shadow effect.• Can lead to amplification of noise.• No physical base for amplification.

Automatic Gain Control (AGC)

46

• Automatic gain controls scales by increasing the amplitudes insegments of the trace where the amplitudes are low.

• It does this by using a moving time window of around a second anddividing the amplitude of the center point by the root mean-squared(rms) amplitude of the window.

• Some reflectors have stronger amplitudes than others and this mayobscure smaller, but important, reflections.

• “Automatic Gain Control” (AGC) boosts the amplitudes so that theyare all of similar size.


47


48

t.v)t(Gr

)t(A =⇒= 1

[ ] [ ] [ ])0(/)0(/)()()(

1)( 22 twtwtwrmstwtwrms

ttvtvtGttv

tA =⇒=

Homogeneous space :

Layered space :

Correction for Spherical Divergence

49

Advantage:• Physical base for amplitude correction.

• Relative Amplitude difference remains equal.

Disadvantages:• Velocity function not know beforehand.

• Noise sources can still remain dominant.

Correction for Spherical Divergence

50

Programmable Gain Control

51

Calculation of decay of amplitude and determine aGain function

Programmed Gain Curve

52

Gain is time-variant scaling based on function, g (t). Base on somecriteria, this function is defined at the time samples (shown by solidcircles) that are usually at the center of specified time gates along thetraces as indicated by 1,2,3 and 4. Gain application simply involvesmultiplying g (t) by the input trace amplitudes.

Applying Amplitude Corrections

53

Scale factors are indicated by the circled numbers at thetimes of application

Four Different PGC Functions

54

Restored amplitudes at late times by correcting for geometrical

spreading (unfortunately ambient noise also has been strengthened

(Yilmaz, 1987).

Corrected Field Records From a Land Survey

55

Before AGC

56

After AGC

57

All traces are normalized using a certain amplitude:

• RMS

• Median value

• Maximum Value

Advantage:• All traces are more equal which is needed for further

processing (Stacking: summation of different traces).

Disadvantage:• No physical base for amplification.

• No equalization of losses with time.

• Large value in a trace can dominate.

Trace Balancing

58

Common-shit gathers after trace balancing. Balancing is time-invariant scaling of amplitudes to a common rms level for all traces.

59

FilteringSPLITSPLIT--SPREAD FIELD RECORDSPREAD FIELD RECORD

TYPES OF NOISETYPES OF NOISE

62

CAUSES OF POOR SIGNALCAUSES OF POOR SIGNAL--TOTO--NOISENOISE

�� NONNON--OPTIMAL FIELD PROCEDURESOPTIMAL FIELD PROCEDURES

�� STRONG COHERENT NOISESTRONG COHERENT NOISE

�� SCATTERING OR ABSORPTIONSCATTERING OR ABSORPTION

-- VULCANICSVULCANICS

-- FRACTURED ZONEFRACTURED ZONE

�� NEARNEAR--SURFACE PROBLEMSSURFACE PROBLEMS

-- POOR COUPLINGPOOR COUPLING

-- ABSORPTIONABSORPTION

�� IMPROPER PROCESSING (STACK)IMPROPER PROCESSING (STACK)

*

TYPES OF FILTERS

Instrument Compensation

Bandpass Filters

Deconvolution

Waveshaping

Spatial (Mixing)

K-F Filters (Velocity, Wedge, Pie Slice)

NARROWING THE PASSBANDNARROWING THE PASSBANDCONSTANT FREQUENCY BANDWIDTHCONSTANT FREQUENCY BANDWIDTH

VARYING ENDPOINTSVARYING ENDPOINTS

STEEPENING THE SLOPESSTEEPENING THE SLOPES LENGTHENING THE OPERATORLENGTHENING THE OPERATOR

RULE OF THUMBRULE OF THUMBFOR FILTER SPECIFICATION...FOR FILTER SPECIFICATION...

FOURIER TRANSFORMFOURIER TRANSFORM

FILTER SCAN WITH NORMALIZING AFTER FILTERFILTER SCAN WITH NORMALIZING AFTER FILTER

No Filter 4-8-16-24 6-12-24-36 8-16-32-48 10-20-40-60 14-28-56-84 18-16-72-108

74

75

F-K FilterF-K Filter

76

F-K FilterF-K Filter

XX

TT

+K+K-K-K

FF

REJECT or PASS

77

Contoh Aplikasi F-K Filter pada data VSPContoh Aplikasi F-K Filter pada data VSP

78

Filter TEST?Filter TEST?

??

??

??

79

Deconvolution

80

Convolution is a mathematical operation defining the change ofshape of a waveform resulting from its passage through a filter.

The asterix denotes the convolution operator. In seismic, weobtain a response for a certain model by convolving the seismicsignal of the source with the reflectivity function.

Convolution

81

Mathematically the convolution is defined as follows:

where k = 0 ... m+n; gi = (i=0 ... m) and fj = (j= 0 ... n).

The convolution can also be performed in the Fourierdomain:Convolution in time domain = Multiplication (of theAmplitude and spectrum and addition of the Phasespectrum) in Fourier domain.

Convolution

82

Example of a Convolution

83

Example of a Convolution

84

Convolution of the reflectivity function with the signal of the sourcereturns the seismic trace.

Convolutional Model of a Seismogram

85

The cross-correlation function is a measure of the similarity between twodata sets. One dataset is displaced varying amounts relative to the other andcorresponding values of the two sets are multiplied together and theproducts summed to give the value of cross-correlation.

The cross-correlation is defined as:

ii

ixy yx .)( ∑ += ττφ

where xi: (i=0 ... n); yi: (i= 0 ... n); φxy(τ): (-m < τ < +m) with m = max. displacements.

Similar to the convolution, the cross-correlation can also performed in theFourier domain :Cross-correlation = Multiplication of Amplitudes and Subtraction of Phasespectrum.

Cross-Correlation

86

Cross-Correlation Function

87

The Auto-correlation is a Cross-correlation of a functionwith itself. It is mathematically defined as:

ii

ixy xx .)( ∑ += ττφ

where xi = (i=0 ... n);φxx(τ) = (-m < τ < +m)and

m = max. displacement.

Auto-Correlation

88

Auto-Correlation of Two Identical Waveforms

89

Auto-Correlation: Multiples

90

• A gradually decaying function indicative of short-period reverberation.

• A function with separate side lobes indicative of long-period reverberations: multiples.

Autocorrelation Functions ContainReverberations

91

Auto-correlation :

Cross-correlation :

Normalization of Correlation

92

• Convolution was the forward operation :

Source (t) * reflectivity (t) = signal (t)

• Deconvolution is the reverse operation:

Reflectivity (t) = signal (t) *-1 source (t)

Deconvolution

95

CONVOLUTIONAL MODELCONVOLUTIONAL MODEL WAVELET CONTRIBUTORSWAVELET CONTRIBUTORS

97

WAVELET CONTRIBUTORSWAVELET CONTRIBUTORS

98

““IDEAL” DECONVOLUTIONIDEAL” DECONVOLUTION

99

PULSE COMPRESSIONPULSE COMPRESSION

100

SUMMARY OF PURPOSESSUMMARY OF PURPOSES

101

=

)1()0(

)0()1()1()0(

1 id

ido

iiii

iiii

aa

φφ

φφφφ

AutocorrelationInverse filter

Cross-Correlation

i = inputd = desired

Optimum Wiener Filters for TheDeconvolution of Seismic Data

102

Objectives:

• Compress the wavelet

into a sharp minimum- or

zero-phase shape.

• Broaden (flatten) its

spectrum.

Deconvolution

103

Spiking and Predictive Deconvolution– Basic Idea

SUPPRESSION OF COHERENT NOISEAFTER PREDICTIVE DECONVOLUTIONSUPPRESSION OF COHERENT NOISEAFTER PREDICTIVE DECONVOLUTION

INPUT OUTPUTINPUT OUTPUT

105 106

A CMP stack (a) with no deconvolution, (b) with spiking deconvolution beforestack, (c) with signature processing (minimum-phase conversion of themeasured signature) followed by spiking deconvolution, (d) with signatureprocessing only (conversion of the signature to a spike).

107 108

109 110

111

• Sorting from shot gathers to “common-midpoint”

(CMP) gathers.

• In a CMP gather, the reflections all come from the

same point for flat layer.

• We can also make common-receiver gathers.

• A common-depth-point (CDP) is similar to a CMP, but

adjusts for the dip of the layers.

CMP Sort

112

Seismic data acquisition with multifold coverage is done in shot-receiver (s,g)coordinates.

The figure is a schematic depiction of the recording geometry and ray pathassociated with flat reflector. Seismic Data processing, on the other hand,conventionally is done in midpoint-offset (y,h) coordinates. The requiredcoordinate transformation is achieved by sorting the data into CMP gathers.Based on the field geometry information, each individual trace is assigned tothe midpoint between the shot and receiver location associated with thattrace. Those trace with the same midpoint location are grouped together,making up a CMP gather.

Albeit incorrectly, the term common depth point (CDP) and CommonMidpoint (CMP) often are used interchangeably.

CMP SORTING

113

Figure depicts the geometry of a CMP gather and ray paths associated witha flat reflector. Note that CDP gather is equivalent to a CMP gather onlywhen reflectors are horizontal and velocities do not vary horizontally.However, when there are dipping reflectors in the subsurface, these twogathers are not equivalent and only the term CMP gather should be used.Selected CMP gathers obtained from sorting the deconvolved shot gathers.

Common Midpoint Sorting

114

Raypaths associated with

Common Shot Gather


Common Mid-Point Gather


Common Offset Gather


Common Receiver positionGather

Common Midpoint Sorting

115

CMP Gather

116

Shot Gathers and Midpoints

117

CMP Gathers Now

118

For most recording geometries, the fold of coverage nffor CMP stacking is given by :

sn

n ggf ∆

∆=2

∆g : receiver group∆s : shot intervalng : The number of recording channels

Fold of Coverage for CMP Stacking

NMO Correction of a CMP gatherNMO Correction of a CMP gather

CMP Stack a CMP gatherCMP Stack a CMP gather

Stacking

Example of stacking toattenuate multiple

Example of stacking toattenuate multiple

SIGNAL-TO-NOISEAMPLITUDE IMPROVEMENT

SIGNAL-TO-NOISEAMPLITUDE IMPROVEMENT

where N = number of uniquerange traces stacked

where N = number of uniquerange traces stacked

STACKSTACK

Stack sectionStack section

124

In addition to providing an improved signal-to-noise ratio,

multifold coverage with nonzero-offset recording yields

velocity information about the subsurface. Velocity

analysis is performed on selected CMP gathers or groups

of gathers. The output from one type of velocity analysis

is a table of numbers as function of velocity versus two-

way zero-offset time (velocity spectrum). These numbers

represent some measure of signal coherency along the

hyperbolic trajectories governed by velocity, offset, and

travel time.

Velocity Analysis

125

Velocity Analysis

The aim of the velocity analysis is to find the velocity, thatflattens a reflection hyperbola, which returns the best resultwhen stacking is applied. This velocity is not always the realRMS velocity.

Therefore, a distinction is made between:•Vstack : The velocity that returns the best stacking result.•Vrms : The actual RMS-velocity of a layer.

For a horizontal layer and small offsets, both velocities aresimilar. When the reflectors are dipping then vstack is not equalto the actual velocity, but equal to the velocity that results in asimilar reflection hyperbola.

126

There are different ways to determine the velocity:

• (t2-x2)-Analysis.

• Constant velocity panels (CVP).

• Constant velocity stacks (CVS).

• Analysis of velocity spectra.

For all methods, selected CMP gathers are used.

Determine The Velocity

127

The (t2-x2) -Analysis is based on the fact, that the Moveout-expression for the square of t and x result in a linear event.When different values for x and t are plotted, the slope can beused to determine v2, the square root returns the propervelocity.

Example of a t2-x2-Analysis :

(t2-x2)-Analysis

128

Examining the normal moveout equation, it is possible to analyzeNMO velocities by plotting reflections in T2 X2 space.

129

The NMO-correction is applied for a CMP using different

constant velocities. The results of the different velocities

are compared and the velocity that results in a flattening of

the hyperbolas is the velocity for a certain reflector.

CVP - Constant Velocity Panels

130

Options in The ProMax Velocity AnalysisRoutine

131

• Similar to the CVP-method the data is NMO-corrected.

This is carried out for several CMP gathers and the

NMO-corrected data is stacked and displayed as a

panel for each different stacking velocity. Stacking

velocities are picked directly from the constant velocity

stack panel by choosing the velocity that yields the

best stack response at a selected event.

• CVP and CVS both have the disadvantage that the

velocity is approximated as good as the distance

between two test velocities. Both methods can be

used for quality control and for analysis of noisy data.

CVS - Constant Velocity Stacks

132

Stacking Velocity

133

Concept of Constant Velocity Stack as An Aidto Stacking Velocity Estimation

134

The velocity spectrum is obtained when the stacking results

for a range of velocities are plotted in a panel for each

velocity side by side on a plane of velocity versus two-way

travel-time. This can be plotted as traces or as iso-

amplitudes. This method is commonly used by interactive

software to determine the velocities.

Velocity-Spectrum

135

• Amplitude of stacking

• Normalized amplitude of stacking

• Semblance

Normalized Amplitude of stacking :

Semblance :

Amplitude of Stacking : ∑=

=n

itit ws

1,

|

||

,1

ti

n

i

tt

w

sns∑

=

=

∑∑∑

•=

t iti

tt

t w

s

nSemblance 2

,

2

1

Wi,t value for i-th trace, time t

Methods to Calculate The Velocity-Spectrum

136Mapping of the offset axis to the velocity axis

Velocity Spectrum

137

Demonstration of The Velocity Spectra

138

Constant Velocity Stack (CVS)

One Method to Determine Stacking Velocity is to Use A ConstantVelocity Stack (CVS) for Several CDP Gathers.

139

Same CVS Panel of Traces as Before Switching to VariableDensity Color for The Traces to Utilize Dynamic Range.


140

Same as Previous Color Panels with Velocity Range NowHalved to Better Pick Correct Velocities.


141

Constant Velocity Moveout (CVP) Corrections(1)

142Velocity ft/s

Constant Velocity Moveout (CVP) Corrections(2)

143

Influence of Missing Long Offset Traces onVelocity Spectra

144

Influence of Missing Long Offset Traces andStatics on Velocity Spectra

145

Semblance-Analysis

146

147 148

Error for High Velocities and Large TravelTimes

Static“Corrections applied to seismic data to compensatefor the effects of variations in:

- elevation,- weathering thickness,- weathering velocity

‘(near-surface velocity anomalies)’ or- reference to a datum.”

1. What are residual static?1. What are residual static?

Residual StaticCMP GATHERCMP GATHER

2. Why are residual static needed?2. Why are residual static needed?

CMP GATHERS BEFORE AFTER RESIDUAL STATICS

STAT 5

After residual statics

STACK before & after residual staticsSTACK before & after residual statics

Before residual statics

153

STACK before & after residual staticsSTACK before & after residual statics

154

THE END OFSEISMIC DATA PROCESSING

PART I

handout processing 1

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