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S-Waves Detect Reservoir Flows

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.

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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.

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