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The scale up of carbon capture and storage (CCS) technology is critical in nearly every modeled energy pathway to net zero. According to the IEA’s net-zero pathway we will need to capture 7.6 billion tonnes of CO2 a year by 2050 – which is over 190 times what is captured and stored today (44 million tonnes).
Digital technologies will be critical in helping deliver the required growth in the most cost-efficient manner by enabling companies to plan and implement end-to-end integrated CCS systems. SLB has over 20 years’ experience working with customers to plan and operate CCS projects, and have spent over 40 years designing and delivering subsurface digital modeling and simulation solutions to customers around the world. Our digital solutions can help you complete comprehensive CO2 storage site assessment and do long term monitoring.
Ideal CO2 storage sites share many of the same characteristics as oil and gas reservoirs–high porosity, high permeability rock types are optimal with a structural and/or stratigraphic trap in place. Proximity to existing transport infrastructure, and to the capture site(s), are also key considerations for screening and ranking potential CO2 storage sites.
The digital tools used in oil and gas workflows, to interpret and model the subsurface for existing infrastructure, are applicable to CO2 site assessment workflows, with a few adjustments. From well log interpretation and 3D model building to volumetric assessments and dynamic CO2 flow simulation, SLB digital technology enables you to complete a comprehensive assessment of potential CO2 storage sites.
A critical component of evaluating a potential CO2 storage complex is to ensure long-term storage integrity, as these reservoirs are expected to contain CO2 over extended periods of time. After constructing a geological model of the reservoir, the reservoir engineer will typically conduct flow simulation evaluations to understand the various trapping mechanisms, evaluate the risk of CO2 migration, and ensure caprock integrity. Studies may include coupling reservoir simulation with geomechanics simulations to further understand the reservoir and ensure its integrity.
A volumetric assessment of a CO2 storage site is a basic component to assess its suitability. Understanding how quickly a desired volume can be injected, without compromising the integrity of the injector well and the storage unit, is critical for a successful operation and for safe long-term containment.
Simulating the flow of CO2 through the storage unit and understanding the complex physical and chemical interactions between the injected CO2 and the reservoir, is essential to answer these questions. The understanding of the system response can be enhanced by looking at coupled solutions that include wellbore multiphase flow, as well as dynamic flow and geomechanical model.
SLB has robust and proven solutions to simulate and evaluate the feasibility of CCS projects. This includes a rich set of dynamic simulation options for CO2 storage in saline aquifers in depleted gas reservoirs or for storage in depleted oil reservoirs. Our powerful simulation capabilities offer a thorough understanding of how the storage unit will behave when CO2 is injected. Even in complex compositional cases requiring fine-resolution grids, this level of detail can be achieved without sacrificing speed. Additional controls and set-ups can be implemented with Python extensibility, enabling tailored and customized workflows.
CO2 storage sites will not always have a lot of data available to help quantify the storage capacity, determine the optimal injection rate and predict the flow of CO2 once injected. These uncertainties affect the subsurface analysis and resulting field development plan, and thus must be carefully considered.
One way to do this is to embed uncertainty analysis in every step of the storage assessment workflow from modeling to CO2 simulation and field development optimization. A second option is to capture the full range of uncertainties by working with an ensemble of realizations throughout the study. Instead of considering a couple of base cases - P10, P50 and P90 - as per traditional workflows, by leveraging cloud compute capacity you can now evaluate the full spectrum of cases and capture the entire range of uncertainty.
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