American Oil and Gas Reporter - July 2020 - 51

SpecialReport: Geophysics & Computing
In any case, to reduce these risks, it is
essential to identify formation water distribution, H2S-generating lithologies (e.g.,
Ochoan evaporites), and relevant structural
elements. A study was initiated in the
Delaware Basin to identify those structures,
correlate excess water production to basin
lineaments, and determine the connection
of lateral wells to water-saturated formations using 3-D data. Seismic analysis of
faulting and natural fracturing can reveal
crucial insights to reduce produced water
and H2S volumes, optimize recovery efficiency, and decrease production costs.
The objectives of the Delaware Basin
study were to better understand the fault
and fracture network distribution within,
below and above the Wolfcamp formation.
The resulting fault risk map allowed for
the comparison of water production volumes from Wolfcamp lateral wells with
their relationships to the basin lineaments
identified from analyzing seismic reservoir
characterization.
The study utilized a data subset of a
multiclient 3-D seismic survey located
in Reeves County, Tx. The interval from
the Permian to the Devonian was imaged
for subsurface discontinuities.
Conditioning And Filtering
Conditioning and filtering the seismic
data is an important first step to creating a
good understanding of the size, distribution,
continuity, and connectivity of faults and
fractures. Delaware Basin seismic data is
noisy in nature because of distortions such
as subsurface interference, shallow geological features, formation composition,
acquisition footprint resulting from shot
point/receiver grid, and other factors.
Conditioning the seismic and filtering
the data for unwanted artifacts help increase
the effectiveness of the seismic reservoir
characterization methods applied later in
the data, and reduce the time it takes to
run the necessary processes. Conditioning
includes filtering out noise that creates
distorted or discontinuous seismic amplitudes, removing artifacts created by the
orientation of how the seismic was shot,
and balancing amplitudes in areas that
may have a lower or higher signal-tonoise ratio than the areas around it.
This process consists of several steps
and is iterative in order to make sure that
as many artifacts as possible are removed
before starting to map seismic discontinuities (faults). While this does not remove
the seismic data necessary for identifying
the faults, it does help to remove many

erroneously interpreted faults that could
be generated from anomalous artifacts,
such as the shooting orientation of the
seismic data.
Fault Extraction
Extracting the fault and fracture data
from the seismic volume can be done at
several scales and for any interval. However, with variations in seismic amplitude
responses, such as a carbonate interval
versus a clastic interval, seismic data
should be split into intervals with similar
seismic characteristics in order to achieve
a better dynamic range for characterizing
small-scale faults and fractures. This ensures a more consistent extraction of
faults and fractures from the data.
In this project, the extraction of faults
and fractures was divided based on formation:
· Brushy Canyon formation to Avalon
formation;
· Avalon to Bone Spring;
· Bone Spring to Wolfcamp;
· Wolfcamp to Strawn;
· Strawn to Woodford; and
· Woodford to base Woodford (top
Devonian).
Within these six intervals, faults and
fractures were extracted using amplitude
discontinuities in the seismic data. These
variations are often minute and not easily
recognizable by the interpreter, especially
in the case of the fractures. These were
identified using additional seismic condi-

tioning processes to eliminate extraneous
information in the seismic volume and to
remove the seismic discontinuities that represent continuous sedimentary deposition.
Once these points of amplitude variation have been identified, they are connected to form faults and fractures. Any
remaining discreet and disconnected points
are filtered out of the dataset. This shows
the importance of conditioning the seismic
volume; the better it has been conditioned,
the fewer extraneous points there will be
to filter out during this process.
Figure 1 illustrates a 3-D view of the
results of this process from the Bone
Spring to the Wolfcamp, and from the
Wolfcamp to the Strawn. The faults and
fractures were separated based on the
continuity through different intervals and
color-coded accordingly:
· Blue represents faults and fractures
contained within a single interval.
· Red represents faults and fractures
penetrating the interval above it.
· Green represents faults and fractures
penetrating the interval below it.
· Dark red represents faults penetrating multiple intervals.
Features in the blue "intra-interval"
typically vary in size from very small to
large with significant variability in vertical
and lateral continuity. These are the faults
and fractures that have the greatest potential for interconnectivity with other
faults and fractures, since they are the
most abundant.

FIGURE 1
Faults and Fractures in Bone Spring and Wolfcamp Formations

Bone Spring

Wolfcamp

Strawn

Legend
Intra-Formational faults
Upper intersecting faults
Lower intersecting faults
Multi-Interval faults

JULY 2020 51

American Oil and Gas Reporter - July 2020

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