American Oil and Gas Reporter - January 2012 - 139

Tech Trends 2012
the absence of rich contextual data such
as 3-D seismic, the overall acoustic response
to the frac is often "shrink wrapped" interpretatively as a proxy for the stimulated
reservoir volume.
However, this interpretive quantification
does not always correlate well with production performance. It turns out that in
some cases, significant amounts of the
acoustic energy created by pressure pumping are the result of repeatedly releasing
stress along a pre-existing fault. In such
cases, the abundance of microseismic
hypocenters likely does not indicate a
successful stimulation of reservoir rock.
For example, a relatively poor performing well (based on maximum monthly
production) was selected from an Eagle
Ford study where seismic and microseismic data were analyzed jointly. The signature of faulting was clearly evident
from curvature analysis of the base Eagle
Ford close to the horizontal well. It was
noted that the hypocenter events viewed
in isolation exhibited significant acoustic
emissions all along the well bore, suggesting a uniform and successful frac application.
However, integrated analysis of key seismic attributes with the microseismic data
suggested a different outcome (Figure 5B).
Where the frac intersected zones of
high azimuthal anisotropy (an open fracture
proxy), many hypocenters were observed,
suggesting induced fractures connecting
with a natural fracture network. However,
toward the toe, where the well crossed a
large fault, it appears the abundance of

hypocenters may be a product of stress
released along the fault. In that scenario,
the frac may not have stimulated significant
hydrocarbon production from the nearby
formation, and the fault may also have
acted as a thief zone for the frac fluid.
Changing The Game
Although incorporating 3-D seismic
data into the shale exploitation workflow
is having an impact on the activities described, the new availability of high quality
seismic has yet to dramatically alter the
way engineers manage shale field development.
Many integrated studies have provided
useful insight into the heterogeneity of
shale reservoirs and suggest interesting relationships to observed well performance.
However, without demonstrating a more
direct relationship of the rock and geomechanical properties to drilling and completions engineering data, the ability to employ
integrated information to predict well and
reservoir performance is still lacking.
But adapting multivariate statistics
techniques to more effectively combine
the myriad seismic, petrophysical and
engineering attributes now available is
changing the game, and is capturing the
attention of the engineers.
To highlight the predictive capacity
of this technique for well performance,
Global Geophysical undertook a 50,000acre study within its Eagle Ford Basin 3D library. The goal was to more directly
inform drilling and completion decisions
by deriving a single predictive model

FIGURE 5A
Eagle Ford Integrated 3-D Seismic, Spectral
Decomposition and Microseismic

from a nonlinear combination of seismic
and engineering variables.
Production and engineering data were
loaded for a dozen wells within this area.
Maximum monthly production was chosen
as an appropriate measure of comparative
well performance. Engineering variables
such as length of the horizontal wells,
lateral depth, and lateral azimuth were
loaded into the software, along with approximately 40 seismic attributes at the
Eagle Ford level, ranging from simple
post-stack measurements such as spectral
decompositions, amplitude and phase derivatives to surface curvature and incoherence. Importantly, specialized prestack
attributes such as Young's Modulus, azimuthal anisotropy, and others were incorporated as well.
Linear correlations computed for all
the seismic and engineering attributes as
well as maximum monthly production
were used to screen for the best relationships,
and a handful of variables that had notably
higher values were selected to build a
small portfolio of indicators to drive the
multivariate statistics workflow. As expected,
none of the linear correlations was much
above 0.60, so clearly there was no "magic
bullet" attribute in this case.
Predictive Attribute
We selected five variables: well bore
length, Young's Modulus (brittleness),
azimuthal anisotropy (open fracture proxy),
and both 10-hertz and 32-hz spectral decomposition. While it makes intuitive
sense that longer well bores provide more

FIGURE 5B
Contextual Map of Microseismic Response
and Azimuthal Anisotropy

In-line
Fewer, weaker
microseismic
events in low
anisotropy area

Approximate trace of
fault on Buda horizon

Microseismic event cluster in
high anisotropy area

Microseismic event cluster near fault,
even though anisotropy is low

JANUARY 2012 139

American Oil and Gas Reporter - January 2012

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