It
has long been recognized that the presence of naturally occurring
fracture networks can lead to unpredictable heterogeneity within
many reservoirs. Conversely, fractures provide high permeability
pathways that can be exploited to extract reserves stored in otherwise
low permeability matrix rock.
One of
the primary difficulties in managing fracture heterogeneity and
the consequent uncertainty is that production rates and volumes
are controlled by fracture network connectivity between the producing
wells, while the primary sources of data on fracture properties
are measured only in the vicinity of wells.
In some
ways this is like trying to predict the size of a schoolyard by
close examination of a single link in the surrounding fence.
Recent
advances in the processing of 3-D seismic data, however, are providing
valuable new tools for the imaging of fracture properties between
wells. Those tools are the analysis of seismic velocities as affected
by raypath direction and offset distance.
Specifically,
adjusting velocities as a function of azimuth (velocity anisotropy)
to improve reflection imaging has produced by-product data volumes
of seismic velocity anisotropy (ANMO) and improved data volumes
of azimuthal changes in amplitude as a function of offset (AVAZ).
These seismic
advances raise the following questions:
- How do fractures
influence these data?
- Geologically, what
should this newly imageable level of fracture heterogeneity look
like?
- How do we interpret
this new data for fracture properties?
- How do we then make
the link between fracture properties and reservoir performance?
In this
first of a two-part series we will examine the first two issues,
with an example from the Wind River Basin.
Theory
of Seismic Response To Fractures
The underlying
theory behind the ANMO and AVAZ processing is quite simple: Most
geophysical processing algorithms assume that all fractures are
approximately vertical, and are locally oriented in a single dominant
direction (figure 1).
The maximum
detectable seismic effect is when the seismic raypath travels perpendicular
to the open fractures, crossing the slow velocity, possibly fluid-filled,
open fracture. A maximum and minimum direction of fracture influence
on P-wave and S-wave velocity can be determined and used to indicate
the dominant fracture orientation.
The difference
between the maximum and minimum effect gives some measure of the
fracture intensity. This same process can be applied in a number
of data volumes where the change in Vp or Vs as a function of azimuth
is measured by the change in stacking velocities (azimuthal NMO)
or the change in reflection coefficients (azimuthal AVO).
The complex
effects of multiple, non-vertical fracture sets will be covered
next month. Thus, an important interpretative step still remains
between the seismic data and using it to predict fracture orientation
and intensity.
Fracture
Orientation In Rocky Mountains
A critical
feature of recently processed AVAZ and ANMO data volumes has been
that the dominant fracture orientation can change dramatically over
short distances.
Recent
work on a project sponsored by the U.S.
Department of Energy (www.fracturedreservoirs.com) shows that
these changes are not only possible, but also highly likely in a
Rocky Mountain compressional setting where the stress field is complex.
The Circle
Ridge Field, in Wyoming's Wind River Reservation, was characterized
through a combination of 2-D cross-sections and 3-D structural reconstructions
based on well and surface data, and fracture data from surface outcrops
and subsurface image logs. The fracture and structural data were
supplemented with data from several transient well tests, a bromide
tracer test and a nitrogen injection test.
The structure
is primarily determined by NE-SW compression, which caused the formation
of a series of imbricate fault blocks along the Red Gully Fault,
including several imbricates to the north (figure
2).
The entire
structure has been characterized as a fault-breached, fault-propagation
fold.
Development
of the structure is likely to have produced the fracturing within
the reservoir units. Fracture development was predicted using strain
calculated through a 3-D palinspastic reconstruction of the field.
Figure
3 shows differences in extensional strain magnitude and orientation
throughout a block of the Tensleep Formation in the hanging wall
of the field's Red Gully Fault. The contours and line lengths represent
the magnitude of the maximum extensional strain due to the initial
folding of the reservoir formations.
The figure's
red lines represent the strike orientation of extensional fractures
that would develop perpendicular to the local direction of maximum
extensional strain. The red lines also show the dominant set; it
is likely that a secondary joint set perpendicular to the set shown
might also develop.
Ninety-degree
changes in dominant fracture orientation across fracture fairways
seen in figure 3 are consistent with
orientation patterns predicted by AVAZ data in nearby reservoirs.
These orientation variations arise due to inhomogeneities in the
stress field and the resulting fracture networks are consistent
with well image log and tracer data.
Similar
changes in fracture orientation occur in nearby outcrop at a much
smaller scale (figure 4). The black
fractures occur only on the left portion of the outcrop, nowhere
else. Red fractures dominate over blue fractures in the left portion,
while blue fracture intensity increases markedly on the right hand
side.
Since seismic
anisotropy can be influenced by the presence of natural fractures
— and that a high degree of variability in fracture orientation
and intensity is to be expected in a Rocky Mountain compressional
setting — interpretation of seismic data requires a sound link
with knowledge of the fracture geology in a region.
Next month:
How the seismic data is interpreted for multiple fracture sets,
and how fracture data is then linked to reservoir performance.