CO2 Injection Modeling in Saline Aquifers: Strategic Business Decisions - Successful Storage Project
Updated: Oct 25
Deep saline aquifers present the greatest opportunity for the geological storage of anthropogenic CO2 storage. Static geological models and dynamic simulation models are used to predict; the movement of injected CO2 in the aquifer, the CO2 storage mechanisms and the magnitude and extent of the pressure front.
CO2 storage projects are complex undertaking, requiring an integrated multidisciplinary efforts to make the strategic business decisions; from 'Site Screening' in potential regions to 'Site Characterization' of selected areas and maturing them to 'Qualified Sites' ready for permitting. Reservoir modeling can help make all those decisions in each phase:
KEY BUSINESS DECISIONS
Test suitability of the storage reservoir to accept and retain CO2 within the targeted injection zone (Accept | Reject Site).
What additional data is needed for detailed modeling for the UIC well permitting
The extent of CO2 plume and likely Area of Review (AoR) for data gathering
What are Injection strategies and Well systems designs to meet them
The key uncertainties & sensitivity analysis to assess
The MVA strategies in space and temporal domain.
The key risks and how to mitigate them?
Designing, implementing, and analyzing field tests
Site closure decisions
SITE SELECTION PHASE
At this stage, the models are reasonably simple. Initial geologic models are developed for use in later dynamic simulations. They will be further refined if a site matures to ‘Site Characterization’ stage.
During Site Selection, we determine:
The magnitude of the pressure front resulting from injection and determine if this pressure front can be measured via MVA strategies.
We focus on using existing data. However, further studies to collect additional data are necessary for updating the models, should be highlighted.
The project team must coordinate and integrate MVA program to acquire and asses the data that is generated from the dynamic models for permitting, successful operation and site closure.
SITE CHARACTERIZATION PHASE
At this stage reservoir modeling is more detailed. It is used to optimize the design of the injection plan and forecast lifecycle risks during the project (ex: seal failure, leakage through faults or abandoned wells, and potential contamination of other resources, such as USDWs).
Specific modeling applications for CO2 geologic storage projects include, but are not limited to:
Evaluation of subsurface CO2 storage mechanisms
Structural /Stratigraphic storage in supercritical state
Hysteresis trapping in aquifer
Solubility trapping in the aquifer
Mineral trapping in aquifer
Geo-mehanical effects (pore pressure increase, fracture & seal failure)
The geological framework for the subsurface understanding to build the models.
Engineering and operating geologic CO2 storage project.
Prediction of post-closure CO2 plume behavior
Meet UIC permit application requirements for site qualification
in operation, measurements gained through monitoring can be used to verify that the project actual performance meets predicted performance
Multiple scenario approach is used to manage subsurface uncertainty by building; a static geological model and a dynamic reservoir flow model.
A 3D geological model is essential for integrating geologic, geophysical, geochemical, geo-mechanical, and hydrogeological data of the injection zone at the specific site.
Dynamic reservoir simulators are then used to test various CO2 injection scenarios and to characterize the short and long-term storage capacity, injectivity and containment performance of the reservoir and estimates of any potential leakage.
Test Models Models should be properly calibrated (including well control). Sensitivity analyses is used to assess uncertainties and impacts of different parameters on the model outcome.
INTEGRATE NEW DATA
In addition to the existing data, new data will also be required as saline aquifers generally have sparse data. The integrated and coupled model (geological, geochemical, geo-mechanical and hydrogeological) is essential for assessing the long-term CO2 injection and its storage in the reservoir.
Geological & Geophysical Data Evaluation
All existing geologic framework of the selected injection interval at potential site and the new data must be analyzed and included in the model (eg. 2D, new 3D seismic, well logs, cores).
Geochemical Data Evaluation
Fluid property data (composition, pH, and conductivity), can be combined with data on reservoir and cap-rock mineralogy to model-Brine-CO2 formation reactions that may occur within the injection zone and at the confining zone interface. Such dynamic modeling is valuable, because chemical reactions induced by CO2 injection may cause changes in reservoir porosity and permeability over time.
Geo-mechanical Data Evaluation
Cap-rock leakage and induced seismicity due to pore pressure increase and subsequent seal failure are the main subsurface risks. Modeling the mechanical effects of CO2 injection and storage in the injection zone is essential for understanding the integrity of the confining zone under varying pressure & injectivity and the resulting induced stresses due to pore pressure. Proper geomechanical characterization and management of pressure can reduce the risk of induced seismicity. The Barton-Brandis geo-mechanical failure model coupled with dynamic reservoir model, predicts tensile seal failure, induced fracture permeability and CO2 leakage in cap-rock.
Hydrogeological Data Evaluation
A variety of hydrogeological tests may be conducted to get necessary data for modeling. 'Drill Stem Tests' to determine perforation intervals; 'Injection Fall-off tests' for direct measurement of injectivity and reservoir permeability; 'Multi-well tests' to measure sustained injectivity and pressure response in nearby wells; 'Multi-zone tests' to test the integrity of seal; 'Step-rate' and 'leak-off' injection tests to confirm injectivity and hydraulic fractures stress.
INJECTION /OPERATION PHASE
Data in this phase is used to calibrate (history match) the model against predictions in the characterization phase. The injection rates, the pressures and plume evolution are some parameters used to calibrate adjust the model.