Improving
reservoir performance and enhancing hydrocarbon recovery are critical
to the future of the petroleum industry -- and to do this, it must be
possible to characterize reservoir parameters, including fluid properties,
their movement and pressure changes with time.
Multi-component,
time-lapse seismology has great potential for monitoring fluid movements
in reservoirs. The main reason is simply the presence of fluid-filled
fractures.
Shear waves (S-waves)
are much more sensitive than compressional waves (P-waves) to the presence
of fractures or microfractures and the fluid content within the fracture
network. Seismic shear wave anisotropy in the reservoir causes two shear
modes to form (S1 and S2) and to propagate with
different velocities.
The faster mode
(S1) propagates with its particle motion parallel to the open
fracture direction, perpendicular to the minimum horizontal stress (S3)
in the reservoir -- a phenomenon called S-wave splitting, or birefringence
(Figure 1).
Seismic shear
wave anisotropy is key to monitoring fluid property changes in fractured
media.
First 4-D, 9-C
Seismic Survey
The first time-lapse
(4-D), multi-component (9-C) seismic surveys were acquired at Vacuum Field
in Lea County, N.M.
At the Vacuum
Field, shear wave (S-wave) and compressional wave (P-wave) seismic data
were used to monitor reservoir fluid property changes associated with
a carbon dioxide (CO2) tertiary flood in the Permian San Andres
Carbonate. Reservoir fluid properties -- including viscosity, density,
saturation and pressure changes -- occur in response to CO2
injection. Changes are caused by CO2 and oil becoming a miscible
phase with the oil in place.
These fluid property
changes alter the interval velocity and attenuation of S-waves passing
through the reservoir interval by up to 10 percent, but cause little (1
to 2 percent) or no measurable change in P-wave velocity and attenuation
on the surface seismic data.
The Reservoir
Characterization Project of the Colorado School of Mines (RCP) has conducted
two studies at Vacuum Field:
- Phase I efforts centered
on monitoring the injection of CO2 from a single wellbore
(Benson and Davis, 2000).
- Phase II is the dynamic
reservoir characterization of a six-well CO2 injection program,
which includes the Phase-I wellbore (producing during Phase-II) (Wehner,
et al, 2000).
The Vacuum Field
was discovered in 1929 with the drilling of the Socony Vacuum State 1
well in Section 13-T17S-R34E of Lea County.
The Vacuum Field
produces predominately from the San Andres Formation in a shallow-shelf
carbonate depositional setting (Figure 2), which
structurally is positioned on the shelf edge of the Permian Basin's Northwest
Shelf. The structurally high shelf crest is located just west of the RCP
study area.
Porosity and
permeability within the productive zones average 11.8 percent and 22.0
md, respectively.
The San Andres
gross pay zone can reach 600 feet in thickness, and is divided into two
main pay zones: Upper and Lower San Andres.
The Lovington
Sandstone, a silty interval, segregates the two zones.
Reservoir Characterization
At Central Vacuum
Unit (CVU), S-wave splitting is the key to monitoring production processes
associated with carbon dioxide (CO2) flooding.
Fluid property
changes produce variations in the velocities of the split S-waves passing
through the reservoir interval. Reservoir fluids change in response to
CO2 and oil becoming a miscible phase in the presence of in-situ
fluids.
Injected CO2
also can create areas of anomalous reservoir pressure.
Both fluid and
pressure changes are detected by S-wave splitting and velocities, because
they are extremely sensitive to the local stress field caused by the natural
fracturing in all rocks, especially carbonates.
Distinguishing
Injected CO2 From Injected Water
S-wave splitting
can distinguish between effective stress changes associated with abnormal
fluid pressures and fluid property change.
During Phase
I of this study, a prominent S-wave splitting anomaly was detected to
the south of a cyclic CO2 injection well (CVU 97). This anomaly
corresponds to the CO2 flood bank that developed south of this
temporary injection well (Figure 3, Phase I).
Noticeable around
the periphery to this CO2 anomaly are anisotropy anomalies
of opposite sign related to offset wells that were used to contain the
CO2 bank through water injection. The sign change of S-wave
anisotropy occurs because the relative velocities of the split S-waves
reverse.
In the case of
the miscible CO2-oil bank, the S2 velocity increased
and S1 decreased, whereas, in the case of water injection,
the effective stress causes S2 to decrease and S1
to increase.
Similar effects
were observed during the second phase of the monitoring study (Figure
3, Phase II). These results imply that S-wave anisotropy can be used
to monitor secondary (water flooding) as well as tertiary (CO2)
methods in a spatial context beyond the wellbore.
The greatest
need of tertiary recovery operations is to monitor and control the areal
and vertical distribution of injected CO2 in the reservoir.
Controlled injection can maximize contact with the oil and optimize sweep
efficiency so that oil is not bypassed.
A spatial image
of the tertiary flood-front was visualized by observing time-lapse anisotropy
differences. This enables the lateral sweep efficiency of the reservoir
to be monitored.
The vertical
sweep efficiency can be detected through amplitude differentials of split
S-waves. S2 amplitude difference anomalies between the pre-
and post-surveys occur dominantly in the Lower San Andres. This is highly
encouraging, because S-wave anisotropy may provide higher vertical resolution,
enabling a visualization of changes approaching the individual flow-unit
scale.
The time-lapse
seismic interpretation of the Phase II seismic data showed a differential
seismic anisotropy anomaly between the baseline and monitoring survey
that coincides with the tertiary flood bank (Figure
3, Phase II). This anomaly was measured over the entire reservoir
interval, and is shown as a velocity anomaly where S1 velocity
decreased and S2 velocity increased.
Figure
4 shows the correspondence between time-lapse P-wave velocity, time-lapse
S-wave polarization direction and time-lapse S-wave velocity anisotropy
anomalies. Using this information, it is possible to separate the effective
stress changes associated with changing fluid pressure from the fluid
saturation changes associated with the tertiary flood bank.
As a result,
the tertiary flood bank -- and its growth over time -- can be monitored
by this technology.
Conclusions
The study indicated
that shear wave analysis provided higher resolution (than P-wave data)
static reservoir characterization, allowing for visualization of inter-well
distribution of secondary porosity, permeability and fracture zones.
Due to rigidity
changes associated with fluid replacement in the reservoir, dynamic monitoring
with shear wave data provided a means to actively follow the displacement
of reservoir fluids with CO2.
This dynamic
reservoir characterization will provide the industry with the ability
to be more proactive, rather than reactive, in the management of reservoirs.