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-By 
SOMAK HAJRA 
M.Sc.-Tech APPLIED GEOPHYSICS 
2012MC0093
SEISMIC ATTRIBUTES 
-AN INTRODUCTION 
 “Seismic Attributes are all the information obtained from 
seismic data, either by direct measurements or by logical or 
experience based reasoning”. 
 Seismic attributes may also be defined as all of the measured, 
computed or implied quantities obtained from the seismic 
surveys which provide a link between rock properties and 
seismic data. 
 E.g. Reflection strength, apparent polarity, instantaneous 
frequency, instantaneous phase etc.
CLASSIFICATION OF ATTRIBUTES 
 PRE-STACK - AVO, velocity & 
azimuthal variations. 
 INSTANTANEOUS – Trace 
envelope, instantaneous frequency 
& phase. 
 PHYSICAL - These relate to physical 
qualities & quantities like lithology 
& wave propagation. 
 WINDOW- summarizing 
information from vertical 
window of data. 
 FOURIER- obtained in freq. 
domain through Fourier 
analysis, like spectral 
decomposition. 
 POST-STACK – Attributes of CDP 
stacked/ migrated data. 
 WAVELET – Instantaneous 
frequency at the peak of the 
envelope equals the mean frequency 
of the wavelet amplitude spectrum. 
 GEOMETRICAL - Geometrical 
attributes describe the spatial and 
temporal relationship of all other 
attributes & include lateral 
information's like dip and azimuth. 
 MULTI-TRACE- calculated using 
more than one seismic traces to give 
lateral variations in data. 
E.g. Volumetric curvature, dip etc.
FLOWCHART SHOWING BRIEF CLASSIFICATION OF ATTRIBUTES
WHAT IS A COMPLEX TRACE? 
 Complex trace analysis treats a 
seismic trace as a real part of 
analytical signal: 
 F(t)=f(t)+jf*(t), where j= √-1 
 The quadrature component f *(t) 
is determined either by a linear 
convolution (Hilbert Transform) 
or by a phasor representation. 
 If Y(t) be the time-varying signal 
composed of real & imaginary 
parts, we have:
COMPONENTS OF A COMPLEX TRACE 
 If A(t) & θ(t) be the 
Amplitude & time-dependent 
phase 
respectively, then the 
real seismic trace can be 
written as: 
f(t)= A(t).cos θ(t) 
 So, f*(t)=A(t).sin θ(t) 
 Thus, 
F(t)= A(t).e^(jθ(t))
ANALYSIS OF SEISMIC ATTRIBUTES 
SINGLE TRACE TYPE 
 Seismic attributes which are calculated 
using single seismic trace as input. 
 The classes of seismic attributes are: 
Horizon (loop) Horizon A 
•Peak amplitude 
•Duration 
•Symmetry 
Sample (volume, instantaneous) 
•Amplitude 
•Time 
•Frequency 
Interval 
•Average amplitude 
•Maximum (Minimum) Duration 
•Isochron
COLOUR CODING OF SEISMIC ATTRIBUTES
REFLECTION STRENGTH 
 Reflection strength is the amplitude of the 
envelope & is given by the equation: 
 A(t)=|F(t)|= √{(f(t)^2)+(f *(t)^2)} 
 The envelope represents the instantaneous 
energy of the signal and is proportional in 
its magnitude to the reflection coefficient. 
 The envelope is useful in highlighting 
discontinuities, changes in lithology, faults, 
changes in deposition, tuning effect, and 
sequence boundaries. 
 Hydrocarbon accumulations, like gas, 
shows high amplitude reflections or, 
‘bright spots’.
INSTANTANEOUS PHASE 
 Instantaneous phase is the angle of lag or 
lead of the harmonic components of a 
seismic pulse with respect to a reference. 
 For example, a zero-phase wave would be 
symmetric whereas a 90° phase wave 
would be perfectly asymmetric. 
 It is represented as: 
θ(t)= arc tan [f*(t)/f(t)] 
 Phase is independent of amplitude but is 
related to instantaneous frequency and 
hence makes weakly coherent events 
clearer. 
 It is also the best indicator of lateral 
continuity.
INSTANTANEOUS FREQUENCY 
 It is the time derivative of instantaneous phase & 
is represented as: W(t)= d θ(t)/dt 
 Reflection events are composite of individual 
reflections from a number of closely spaced 
reflectors, the superposition of which produces a 
characteristic frequency pattern. 
 Variations like pinch-outs or hydrocarbon-water 
interfaces tend to change the instantaneous 
frequency value more rapidly. 
 A low frequency shift (“low frequency shadow”) 
occurs due to reflections from reflectors below gas 
sands, condensates or oil reservoirs. 
 The adjacent seismic (a) & the corresponding 
frequency(b) section shows low frequency anomaly 
at shallow depths indicating presence of shallow 
gas.
WEIGHED AVERAGE FREQUENCY APPARENT POLARITY 
 Weighed average frequency 
emphasizes the frequency of 
stronger reflection events & 
smoothes irregularities caused 
by noise. 
 It is given by the equation: 
where, freq(t)=w(t-T) & 
env (t)=A(t-T).L(T) 
L(T) being the low pass filter. 
 It is an excellent tool for 
enhancing reflection continuity. 
 Apparent polarity is the sign of 
f(t) when A(t) is maximum and 
are especially sensitive to data 
quality. 
 ‘Bright Spots’ associated with 
gas accumulations show 
negative polarity for reservoir 
top reflections. 
 ‘Flat Spots’ associated with 
reflections from gas-oil or gas-water 
interfaces show positive 
polarity. 
 The +ve or –ve sign is assigned 
assuming a zero phase wavelet.
SOME OTHER DERIVED ATTRIBUTES 
 Amplitude Derivative (RE)=dA(t)/dt which highlights the change in reflectivity and is 
also related to the absorption of energy. 
 Second Derivative of Envelope (DDE)=d2A(t)/dt2 which indicates all reflecting 
interfaces visible within seismic band-width showing sharpness of events & changes in 
lithology. 
 Cosine of Instantaneous Phase C(t)=cos θ(t) which gives detailed visualization of 
bedding configurations. 
 Instantaneous Acceleration AC(t)=d(F(t))/dt which accentuates bedding differences. 
 Thin Bed Indicator TB(t)=F(t)-F’(t) which highlights the location where the 
instantaneous frequency jumps in the reverse direction due to very close reflectors, i.e., 
thin beds. Computed from large spikes of instantaneous frequency, indicating 
overlapped events. 
 Instantaneous Bandwidth B(t)={d(E(t))/dt}/2*pi*E(t). It shows overall effects of 
absorption and seismic character changes. 
 Instantaneous Q=pi*(instantaneous frequency) * (envelope)/derivative of 
envelope. It May indicate liquid content by ratio of pressure versus shear wave section Q 
factors. 
 Relative Acoustic Impedance which calculates the running sum of the trace to which a 
low cut filter is applied. It is an indicator of impedance changes, in a relative sense.
MULTI-TRACE TYPE 
Seismic attributes which are calculated 
using more than a single seismic trace as 
input are known as multi-trace type. 
It is based on the correlation of two or 
more seismic traces.
SPECTRAL DECOMPOSITION 
The spectral analysis is a procedure that decomposes a time 
series into a spectrum of cycles of different lengths. It is also 
known as frequency domain analysis. The spectral analysis 
describes the distribution of the power at a specific 
frequency of a signal, based on a finite set of data. It 
replaces the single input trace with a gather of traces 
corresponding to the spectral decomposition of the 
input attribute. Creating spectral decomposition attributes 
enables us to illuminate the structures with different 
frequency bands to see if any of them gives us better 
resolution. 
In spectral decomposition we use complex traces. 
Basically a single trace is convolved with the first real 
wavelet to get the real trace for the first frequency, and 
the input trace is convolved with the first wavelet of 
the imaginary part to get the imaginary trace. Then a 
complex trace attribute is constructed, such as 
envelope, phase, etc. This step is repeated for each 
filtered wavelet operating on the same trace and obtain 
band limited traces.
CONCLUSION 
Our increasing reliance on seismic data requires that we extract the most 
information available from the seismic response. Seismic attributes are 
important because they enable interpreters to extract more information from 
seismic data. Applications of attributes include: 
 Hydrocarbon play evaluation, prospect identification and risking, reservoir 
characterization, well planning and field development. 
 Description of shape or other characteristics of a seismic trace over specific 
intervals or at specific times. 
 They are used for qualitative analysis (e.g., data quality, seismic facies 
mapping) and quantitative analysis (e.g., net sand, porosity prediction). 
It may be noted that these attributes are very useful tools analysis of a single 
attribute may not provide a conclusive definitive information. Instead, useful 
conclusions can be drawn by using a combination of attributes together.
REFERENCES: 
 D. Subrahmanyam & P. H. Rao, Seismic Attributes- A Review; International 
Conference & Exposition on Petroleum Geophysics; Pg-398 
 M. T. Taner, F. Koehler, and R. E. Sheriff, Geophysics; Complex Seismic Trace Analysis; 
44 (6), 1041 (1979). doi:10.1190/1.1440994 
 M. Turhan Taner, SEISMIC ATTRIBUTES 
 S. M. Rahman; Constraint of Complex Trace Analysis for Seismic Data Processing; 
J. Sci. Res. 3 (1), 65-73 (2011) 
 Schroeder, Using Seismic Attributes ;AAPG 
 http://en.wikipedia.org/wiki 
THANK YOU

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Seismic attribute analysis using complex trace analysis

  • 1. -By SOMAK HAJRA M.Sc.-Tech APPLIED GEOPHYSICS 2012MC0093
  • 2. SEISMIC ATTRIBUTES -AN INTRODUCTION  “Seismic Attributes are all the information obtained from seismic data, either by direct measurements or by logical or experience based reasoning”.  Seismic attributes may also be defined as all of the measured, computed or implied quantities obtained from the seismic surveys which provide a link between rock properties and seismic data.  E.g. Reflection strength, apparent polarity, instantaneous frequency, instantaneous phase etc.
  • 3. CLASSIFICATION OF ATTRIBUTES  PRE-STACK - AVO, velocity & azimuthal variations.  INSTANTANEOUS – Trace envelope, instantaneous frequency & phase.  PHYSICAL - These relate to physical qualities & quantities like lithology & wave propagation.  WINDOW- summarizing information from vertical window of data.  FOURIER- obtained in freq. domain through Fourier analysis, like spectral decomposition.  POST-STACK – Attributes of CDP stacked/ migrated data.  WAVELET – Instantaneous frequency at the peak of the envelope equals the mean frequency of the wavelet amplitude spectrum.  GEOMETRICAL - Geometrical attributes describe the spatial and temporal relationship of all other attributes & include lateral information's like dip and azimuth.  MULTI-TRACE- calculated using more than one seismic traces to give lateral variations in data. E.g. Volumetric curvature, dip etc.
  • 4. FLOWCHART SHOWING BRIEF CLASSIFICATION OF ATTRIBUTES
  • 5. WHAT IS A COMPLEX TRACE?  Complex trace analysis treats a seismic trace as a real part of analytical signal:  F(t)=f(t)+jf*(t), where j= √-1  The quadrature component f *(t) is determined either by a linear convolution (Hilbert Transform) or by a phasor representation.  If Y(t) be the time-varying signal composed of real & imaginary parts, we have:
  • 6. COMPONENTS OF A COMPLEX TRACE  If A(t) & θ(t) be the Amplitude & time-dependent phase respectively, then the real seismic trace can be written as: f(t)= A(t).cos θ(t)  So, f*(t)=A(t).sin θ(t)  Thus, F(t)= A(t).e^(jθ(t))
  • 7. ANALYSIS OF SEISMIC ATTRIBUTES SINGLE TRACE TYPE  Seismic attributes which are calculated using single seismic trace as input.  The classes of seismic attributes are: Horizon (loop) Horizon A •Peak amplitude •Duration •Symmetry Sample (volume, instantaneous) •Amplitude •Time •Frequency Interval •Average amplitude •Maximum (Minimum) Duration •Isochron
  • 8. COLOUR CODING OF SEISMIC ATTRIBUTES
  • 9. REFLECTION STRENGTH  Reflection strength is the amplitude of the envelope & is given by the equation:  A(t)=|F(t)|= √{(f(t)^2)+(f *(t)^2)}  The envelope represents the instantaneous energy of the signal and is proportional in its magnitude to the reflection coefficient.  The envelope is useful in highlighting discontinuities, changes in lithology, faults, changes in deposition, tuning effect, and sequence boundaries.  Hydrocarbon accumulations, like gas, shows high amplitude reflections or, ‘bright spots’.
  • 10. INSTANTANEOUS PHASE  Instantaneous phase is the angle of lag or lead of the harmonic components of a seismic pulse with respect to a reference.  For example, a zero-phase wave would be symmetric whereas a 90° phase wave would be perfectly asymmetric.  It is represented as: θ(t)= arc tan [f*(t)/f(t)]  Phase is independent of amplitude but is related to instantaneous frequency and hence makes weakly coherent events clearer.  It is also the best indicator of lateral continuity.
  • 11. INSTANTANEOUS FREQUENCY  It is the time derivative of instantaneous phase & is represented as: W(t)= d θ(t)/dt  Reflection events are composite of individual reflections from a number of closely spaced reflectors, the superposition of which produces a characteristic frequency pattern.  Variations like pinch-outs or hydrocarbon-water interfaces tend to change the instantaneous frequency value more rapidly.  A low frequency shift (“low frequency shadow”) occurs due to reflections from reflectors below gas sands, condensates or oil reservoirs.  The adjacent seismic (a) & the corresponding frequency(b) section shows low frequency anomaly at shallow depths indicating presence of shallow gas.
  • 12. WEIGHED AVERAGE FREQUENCY APPARENT POLARITY  Weighed average frequency emphasizes the frequency of stronger reflection events & smoothes irregularities caused by noise.  It is given by the equation: where, freq(t)=w(t-T) & env (t)=A(t-T).L(T) L(T) being the low pass filter.  It is an excellent tool for enhancing reflection continuity.  Apparent polarity is the sign of f(t) when A(t) is maximum and are especially sensitive to data quality.  ‘Bright Spots’ associated with gas accumulations show negative polarity for reservoir top reflections.  ‘Flat Spots’ associated with reflections from gas-oil or gas-water interfaces show positive polarity.  The +ve or –ve sign is assigned assuming a zero phase wavelet.
  • 13. SOME OTHER DERIVED ATTRIBUTES  Amplitude Derivative (RE)=dA(t)/dt which highlights the change in reflectivity and is also related to the absorption of energy.  Second Derivative of Envelope (DDE)=d2A(t)/dt2 which indicates all reflecting interfaces visible within seismic band-width showing sharpness of events & changes in lithology.  Cosine of Instantaneous Phase C(t)=cos θ(t) which gives detailed visualization of bedding configurations.  Instantaneous Acceleration AC(t)=d(F(t))/dt which accentuates bedding differences.  Thin Bed Indicator TB(t)=F(t)-F’(t) which highlights the location where the instantaneous frequency jumps in the reverse direction due to very close reflectors, i.e., thin beds. Computed from large spikes of instantaneous frequency, indicating overlapped events.  Instantaneous Bandwidth B(t)={d(E(t))/dt}/2*pi*E(t). It shows overall effects of absorption and seismic character changes.  Instantaneous Q=pi*(instantaneous frequency) * (envelope)/derivative of envelope. It May indicate liquid content by ratio of pressure versus shear wave section Q factors.  Relative Acoustic Impedance which calculates the running sum of the trace to which a low cut filter is applied. It is an indicator of impedance changes, in a relative sense.
  • 14. MULTI-TRACE TYPE Seismic attributes which are calculated using more than a single seismic trace as input are known as multi-trace type. It is based on the correlation of two or more seismic traces.
  • 15. SPECTRAL DECOMPOSITION The spectral analysis is a procedure that decomposes a time series into a spectrum of cycles of different lengths. It is also known as frequency domain analysis. The spectral analysis describes the distribution of the power at a specific frequency of a signal, based on a finite set of data. It replaces the single input trace with a gather of traces corresponding to the spectral decomposition of the input attribute. Creating spectral decomposition attributes enables us to illuminate the structures with different frequency bands to see if any of them gives us better resolution. In spectral decomposition we use complex traces. Basically a single trace is convolved with the first real wavelet to get the real trace for the first frequency, and the input trace is convolved with the first wavelet of the imaginary part to get the imaginary trace. Then a complex trace attribute is constructed, such as envelope, phase, etc. This step is repeated for each filtered wavelet operating on the same trace and obtain band limited traces.
  • 16. CONCLUSION Our increasing reliance on seismic data requires that we extract the most information available from the seismic response. Seismic attributes are important because they enable interpreters to extract more information from seismic data. Applications of attributes include:  Hydrocarbon play evaluation, prospect identification and risking, reservoir characterization, well planning and field development.  Description of shape or other characteristics of a seismic trace over specific intervals or at specific times.  They are used for qualitative analysis (e.g., data quality, seismic facies mapping) and quantitative analysis (e.g., net sand, porosity prediction). It may be noted that these attributes are very useful tools analysis of a single attribute may not provide a conclusive definitive information. Instead, useful conclusions can be drawn by using a combination of attributes together.
  • 17. REFERENCES:  D. Subrahmanyam & P. H. Rao, Seismic Attributes- A Review; International Conference & Exposition on Petroleum Geophysics; Pg-398  M. T. Taner, F. Koehler, and R. E. Sheriff, Geophysics; Complex Seismic Trace Analysis; 44 (6), 1041 (1979). doi:10.1190/1.1440994  M. Turhan Taner, SEISMIC ATTRIBUTES  S. M. Rahman; Constraint of Complex Trace Analysis for Seismic Data Processing; J. Sci. Res. 3 (1), 65-73 (2011)  Schroeder, Using Seismic Attributes ;AAPG  http://en.wikipedia.org/wiki THANK YOU