The main objective of this study is to apply spectral decomposition (SD) and spectral inversion (SI) as seismic attributes to enhance stratigraphic and structural elements on a 3D seismic data located in Fort Worth basin. By applying these techniques it is possible to improve the vertical resolution of seismic data to better understand the characteristics on this region, and to define geological elements that cannot be seen in conventional seismic data. SD and SI contributed to a more precise interpretation and characterization (mapping, layer thickness determination, and stratigraphic visualization) of reservoirs plays along the stratigraphic column. Spectral decomposition and spectral inversion contributed to a more precise interpretation and characterization of reservoirs plays along the stratigraphic column. Spectral decomposition was performed using constrained least-squares spectral analysis (CLSAA), which has better temporal resolution than both the Fourier Transform (FT) and the Continuous Wavelet Transform (CWT). The spectral inversion was accomplished by inverting the time-frequency analysis for a sparse-layer reflectivity series. Conclusions - These methods provided higher resolution images of geological features than conventional seismic data had done, and improved identification and delineation of this features that are important for production of unconventional gas. - Visualization was improved using RGB overlays of the spectral decomposition data and by the application of coherence attributes to the spectral inversion results. - Using these high resolution spectral methods, vertical resolution was improved from 115 ft. to 50 ft.

1. Lorenzo A. Izarra
Enhancement of geological features in the Fort Worth Basin by the application of
Spectral Decomposition and Spectral Inversion, Shackelford County, Texas, USA
Introduction
The main objective of this study is to apply spectral
decomposition (SD) and spectral inversion (SI) as seismic
attributes to enhance stratigraphic and structural elements on
a 3D seismic data located in Fort Worth basin.
By applying these techniques it is possible to improve the
vertical resolution of seismic data to better understand the
characteristics on this region, and to define geological
elements that cannot be seen in conventional seismic data.
SD and SI contributed to a more precise interpretation and
characterization (mapping, layer thickness determination, and
stratigraphic visualization) of reservoirs plays along the
stratigraphic column.
Shackelford County, TX
120 mi² of
3D seismic data
Acknowledgement
Dick Willingham - BBW Energy who provided the
data for this study.
Lumina Geophysical for their invaluable help.
For more information
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Study area
The study area is located on North central part of the state of
Texas, eastern part of Shackelford County.
Geological setting
Oil and gas production from
rocks of Ordovician,
Mississippian, and Early
Pennsylvanian age are mostly
carbonate rock reservoir.
Production in the Middle
Pennsylvanian through Lower
Permian part is mostly from
clastic rock reservoirs.
(Pollastro et al., 2003)
The Fort Worth Basin as an
asymmetrical, wedge-
shaped foreland basin with
12,000 ft. of strata preserved
in its deepest northeast
portion and adjacent to the
Muenster Arch and Ouachita
structural belt.
General Workflow
Results
Spectral decomposition
RGB blended images helps identify geological
elements
Channels tune up at certain frequencies, the RGB color-coded
multispectral display allows interpreters to observe the
complete channel system.
Red: 16 Hz; Green: 26 Hz; Blue: 36 Hz
Comparison between (a) the
original seismic data, and (b)
the phase response data at
26 Hz. On the phase data (b)
it is possible to define the
configuration of a carbonate
barrier, not obvious on the
conventional seismic data
(a). Note the interpretation of
this geological feature based
on the phase data (c)
(a)
(b)
(c)
Carbonate features enhanced with variance
cube obtained from inverted cube
(a) (b)
Time slice at 450 ms in 3D of the variance data computed from
the original (a), and inverted seismic data (b). Observe the
presence of carbonate features on the original (red arrows), and
note the inverted data defines with more greater detail those
features, for example, minor pinnacle reefs that are below
seismic resolution (yellow arrows)
Phase cubes help define discontinuities and
internal architecture
Advantage of RGB display
A comparison of different seismic attributes extracted over the
original seismic data. It is evident that the results obtained with
the SD on an RGB overlay are enhanced the presence of
channels not obvious with other seismic attributes calculated
The inverted data
allows the
interpretation of
thinner layer, not
evident with the
original seismic
data. From the
original seismic
data it is difficult to
define the lateral
changes, but using
the inverted seismic
data it is possible to
follow the top, and
define these
changes
Definition of thinner layers with inverted cube
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Conclusions
• Spectral decomposition and spectral inversion contributed
to a more precise interpretation and characterization of
reservoirs plays along the stratigraphic column.
• Spectral decomposition was performed using constrained
least-squares spectral analysis (CLSAA), which has better
temporal resolution than both the Fourier Transform (FT)
and the Continuous Wavelet Transform (CWT).
• The spectral inversion was accomplished by inverting the
time-frequency analysis for a sparse-layer reflectivity
series.
• These methods provided higher resolution images of
geological features than conventional seismic data had
done, and improved identification and delineation of this
features that are important for production of
unconventional gas.
• Visualization was improved using RGB overlays of the
spectral decomposition data and by the application of
coherence attributes to the spectral inversion results.
• Using these high resolution spectral methods, vertical
resolution was improved from 115 ft. to 50 ft.
1
Spectral inversion
Comparison of original and inverted cube
Synthetic seismogram for well Richter 34-1, comparing
conventional seismic data and inverted data. The inverted data
displays more reflections related to thinner layer that cannot be
differentiated with conventional seismic data. Although, the
correlation coefficient, for the well tie, is low; the inverted data
exhibits a better correlation compared to the original