There are many known fractured reservoirs
worldwide that have been profitably produced — but it is safe to
say that none of them have been depleted efficiently.
As production costs rise and our industry focuses
more on production and development, it is becoming crucial to recognize
the influence of fractures early in the life of a field for optimal
reservoir management. An important part of this management begins
with the classification of fractured reservoirs based on production
issues, such as rates and reserves.
Fractures have a significant effect on permeability,
resulting in preferred directions of flow, and are probably more
common than we think.
A key strategy for fractured reservoir management
is an accurate description of the geological, geophysical and petrophysical
attributes of fractures within the reservoir. Traditionally this
information comes from well data and, to some extent, large-scale
seismic features (observable faults).
This article describes how sub seismic attributes
of azimuthal anisotropy can potentially add to this characterization
of a fractured reservoir.
Converted waves (PS-waves), created by traditional
downgoing compressional waves (P-waves) that reflect as shear-waves
(S-waves), provide us with a unique ability to measure anisotropic
seismic attributes that are sensitive to fractures.
Solutions that PS-wave anisotropy can bring to fractured
reservoir management are:
- Sweet-spot detection.
- Improved models for reservoir simulation.
- Production history matching.
- Time-lapse behavior of fracture properties
over the life of a field (most important for dynamic management).
The goal, of course, is to reduce the total production
costs for reservoir depletion by using fracture information as early
Fractured Reservoir Types
It is well known that porosity and permeability are
key factors used to describe fractured reservoirs. As a motivation
for the need of azimuthal anisotropy measurements, figure
1 shows a schematic distribution of different reservoir types
in terms of percent total porosity and total permeability (Nelson,
A Type I fractured reservoir is where fractures dominate
both porosity and permeability. Most of the reserves are stored
in the fractures and flow is confined within them. These are very
heterogeneous and anisotropic reservoirs.
At the other end of this distribution are Type IV
reservoirs, where fractures provide no additional permeability or
porosity. Ideally this would be a homogeneous "tank" reservoir when
no fractures are present — but when they are present, fractures
can sometimes be a problem and act as barriers to flow.
Type II and Type III fractured reservoirs are of
an intermediate nature where fractures control permeability and
assist permeability, respectively. In these two cases, more reserves
are stored within the matrix but fractures still have an impact
and can result in anisotropic permeability and unusual response
to secondary recovery (elliptical drainage).
Bottom line: In going from Type IV to Type I there
is an increasing effect of fractures.
Fractures and PS-Wave Seismic Data
Fracture properties are fractal by nature, as illustrated
in figure 2.
Cores and image logs typically provide the small-scale
features of the reservoir and surface-seismic data can provide the
largest scale features like faults with large displacements. Each
tool yields a portion of the total fracture network — however,
it is clear that these end members alone do not control production.
If they did, reservoir models and fluid simulations would be perfect.
Fracture properties over the intermediate range of
scales in figure 2 are missing. Traditionally
this has been filled with paleo-strain fields that relate to possible
fracture directions and intensities, inferred from geomechanical
modeling by palinspastic reconstruction.
This method, however, can be highly non-unique and
uncertain in the presence of unconformities.
Azimuthal anisotropy measurements can be used for
this sub-seismic resolution. Although fractures are smaller than
a seismic wavelength and individual fractures are not directly observed,
we do get an average response. This averaging leads to a directional
dependence, i.e. our velocities are azimuthally anisotropic.
We can measure anisotropy at the borehole with vertical
seismic profiles (VSPs) and with P-wave surface seismic data, but
I want to focus on the use of PS-waves.
Figure 3 illustrates
a typical PS-wave source-receiver geometry. The most important property
is the azimuth or the propagation direction from source to receive.
We need to sample a full range of azimuths over 360
degrees for azimuthal anisotropy measurements.
In addition to the P-waves that reflect at a common
midpoint (CMP), we detect PS-waves that convert at common-conversion
points (CCP) using three-component (3C) geophones. The source to
detector azimuth controls the direction of polarization of the created
S-wave, but this upgoing S-wave immediately splits and travels to
the surface as two orthogonally polarized S-waves.
Figure 4 shows a more
detailed view of S-wave splitting for a single set of vertical fractures,
simulated by a grid that is oriented north-south. The upgoing converted
S-wave travels as a fast and slow component that is polarized parallel
and perpendicular to the fractures, respectively.
The time difference between them depends on the percent
S-wave anisotropy, and is proportional to fracture density.
PS-Wave Data Example: North Sea Subsidence Stress
The algorithm used for fracture characterization
is a layer stripping method that consists of first finding an optimal
rotation of the horizontal components to separate fast and slow
S-waves by Alford rotation. This provides the fast S-wave direction
(fracture orientation). Then correlation of the fast and slow S-wave
provides time delays for estimates of the amount of splitting and
fracture density information.
Figure 5 shows the results
from the shallow overburden at the Valhall Field in the North Sea.
A 3-D ocean bottom cable (OBC) survey was acquired there in 1998
using wide-azimuth source-receiver geometry to provide a full range
of azimuth data.
The small vectors show the orientation of the fast
shear-wave direction measured along the receiver lines, which was
oriented NNW by SSE, and the length of these vectors is proportional
to the time lag or percent anisotropy (maximum is about 3 percent).
A simple interpretation of this display is that the
vectors represent a single set of vertical fractures seen from above.
Note the interesting concentric pattern centered
on the production platform (red triangle). This is a dramatic example
where man-made alterations of the subsurface have induced horizontal-stress
perturbations near the surface.
The pattern of S-wave splitting correlates precisely
with subsidence at the platform due to collapse of the reservoir.
In the center where there has been four meters of
subsidence the anisotropy is relatively small — but as one moves
away from the center, there is an increase in the anisotropy along
the flanks of the subsidence where radial extension is occurring.
Here is where the minimum horizontal stress direction is radial
and the maximum horizontal stress direction is transverse.
This agrees exactly with the fast S-wave orientation,
and is a good example showing that the fast S-wave direction is
highly sensitive to the maximum horizontal stress direction.
Next month, we will see advanced applications of seismic
azimuthal anisotropy, which maps fracture orientations across productive
fields in Italy and Wyoming.
The author thanks Rich Van Dok, Richard Walters
and Bjorn Olofsson from WesternGeco, for their expertise in data
processing of the Madden, Emilio and Valhall studies, respectively;
and also Lynn Inc., Eni/Agip division, BP and WesternGeco for
their support and permission to publish this material.