Phone
+1 510-522-0700
email

Monitoring CO2 Injection Volumes in the Subsurface—The Sleipner Field

Subsurface CO2 injection and storage is a proven technology for keeping carbon dioxide out of the atmosphere and helping to achieve net zero goals. However, robust monitoring of the injection process is critical to ensure and verify that there is no leakage or unexpected movement of the carbon dioxide post-injection.

The CoViz 4D software from Dynamic Graphics is ideally suited for the CO2 monitoring challenge. Numerous diverse data streams and subsurface models can capture the past, present, and future fluid distributions in Carbon Capture & Storage (CCS) situations. This data integration, combined with robust quantitative and reporting tools allows the CoViz 4D platform to be an end-to-end solution for monitoring, communicating, and reporting on subsurface CCS activities.

The CCS dataset for the Sleipner field in the Norwegian North Sea have been released by Equinor (Figure 1) and includes well logs, reservoir models, seismic volumes, and structural interpretations, in addition to historic records of CO2 injected volumes since sequestration began in 1996. All of these data were provided in different third-party formats but were easily ingested via the CoViz 4D Data Registry. DGI’s EarthVision software was then used to rapidly build a stratigraphic model which is shown alongside the reservoir flow model and other data.
Figure 1. Integration and animation of diverse third-party data from the Sleipner field. Sleipner CO2 reference dataset, published via the CO2 DataShare online portal administrated by SINTEF AS (https://co2datashare.org).

The temporal tools in CoViz 4D reveal the evolution of the injected plume behavior with time as expressed in the seismic reflection data. In Figure 2, note the upward migration in the early history around the sole injector well, followed by a rapid lateral spread at later time points. Noteworthy is the lack of any significant 4D seismic signature above the top of the targeted Utsira container; this gives us some confidence in the integrity of the shale caprock. Tools exist within CoViz 4D to estimate cap rock integrity and fault zone transmissibility – algorithms which can be applied to the available geologic and rock physics model.

Figure 2. Animation showing initial upward migration of CO2 and rapid lateral spread at later time points.

The clear dynamic presentations from the CoViz 4D software makes it an ideal tool for communicating to non-subject matter expert stakeholders who are often deeply invested in these projects. Furthermore, the 4D capabilities of the software make it perfect for displaying any associated induced seismicity, or other dynamic data. And the DGI software can take the analysis much further than just qualitative presentations. Quantitative analysis of the seismic data and reservoir starts with volumetric assessment and storage potential.

Plotting the gas injection history with time (Figure 3) we see how it tracks the volume of the plume detected by the 4D seismic. Likewise, careful consideration of the 4D seismic signature may be able to reveal the concentrations or density of the gas within the detected plume. Taking this further, the CoViz 4D Sim2Seis workflow can forward model the seismic response of the reservoir under CO2 injection and reveal the feasibility of using 4D seismic to detect CO2 into the future.

Figure 3. Animation showing 2D time series plot alongside the 4D display showing how the gas injection history tracks the volume of the plume detected by the seismic.

Limitations in the sensitivity of seismic data, as well as the relatively high cost, often leads operators to use electromagnetic or other potential field data to try and track the CO2. The Sleipner gravity station locations on the seabed are colored and scaled here by the 4D gravity change observed between adjacent gravity surveys which primarily results from the lower density injected CO2 replacing brine.
DGI tools allow for easy forward modeling of the measured gravity response. A gravity analysis Jupyter Notebook (Figure 4) allowed the DGI Developers’ Toolkit to be combined with the best of the Python ecosystem, enabling rapid iterations and easy documentation of outputs from the workflow. The modeled gravity response using different CO2 density distributions was compared to the gravity observations, providing an additional constraint on the possible size, shape, and density of the CO2 plume.

Figure 4. Gravity analysis conducted in a Jupyter Notebook which enables the DGI Developers’ Toolkit to be combined with the best of the Python ecosystem.

In summary CoViz 4D integrates available data to present the history and current state of the reservoir, and can be used to visualize the future predictive reservoir model. Geologic data, injection data and time lapse seismic data can be integrated into a common environment for improved collaboration and understanding. With these tools, the migration of CO2 through the reservoir can be monitored over time.

But beyond these qualitative outcomes the software offers a quantitative platform for integrating injected volumes, seismic signatures, gravity response and so forth. Thus creating an integrated multiphysics earth model for injection verification and compliance monitoring which could be further connected to the appropriate reporting and legislative frameworks.

See the CoViz 4D Reservoir Monitoring page for more information.

Data Sources/Credits:

Sleipner CO2 reference dataset, published via the CO2 DataShare online portal administrated by SINTEF AS (https://co2datashare.org).

FURTHER READING

No Results Found

The page you requested could not be found. Try refining your search, or use the navigation above to locate the post.

FOLLOW US