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1
SEISMICDATAPROCESSING(PART I)
2
• 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
CMP Processing Sequence (Continued)
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.
CMP Processing Sequence (Continued)
10
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.
CMP Processing Sequence (Continued)
� 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
35
• 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
36
• Reflection and transmission at an interface.
• Geometrical spreading.
• Absorption.
• Receiver response.
• Measurement system
Loss of Amplitude
Loss of amplitude due to:
37
• 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.
Automatic Gain Control (AGC)
47
Automatic Gain Control (AGC)
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
Raypaths associated with
Common Mid-Point Gather
Raypaths associated with
Common Offset Gather
Raypaths associated with
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.
Constant Velocity Stack (CVS)
140
Same as Previous Color Panels with Velocity Range NowHalved to Better Pick Correct Velocities.
Constant Velocity Stack (CVS)
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