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FluidTrack    is a newly developed technology that can monitor the spatial distribution of injected CO2 in near real-time using geophysical field measurement data. It provides critical information for agile decision-making to mitigate risks such as CO2 leakage and fault reactivation, as well as to improve storage utilization efficiency. This is achieved by integrating rock physics modeling with advanced machine learning algorithms. The workflow built within FluidTrack has broad applicability for subsurface monitoring of pore fluid evolution associated with physical relationships and rock properties.

For example, in the contexts of CCS (carbon capture and storage) and plume migration, we predict that our workflow, with minor updates, will successfully identify the evolution of fluid pathways during geothermal production. This information can help optimize heat sweep efficiency, thereby maximizing operational economics.


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