Speaker
Description
In natural rocks, there exists a trade-off between field of view and resolution, resulting in the presence of sub-resolution pores within the current observational scope. Taking shale as an example, different types of sub-resolution matrix pores exhibit distinct pore structures and flow capacities. Single-scale imaging techniques cannot comprehensively characterize the pore structure of the core. Establishing a method for constructing multi-scale digital cores and simulating flow in shale is crucial for the efficient development of shale oil and gas resources. Therefore, we have developed a multi-scale flow simulation based on coupled free flow and seepage. This approach utilizes machine learning and image classification to construct multi-scale digital cores and employs the single-domain Darcy-Brinkman-Stokes method to achieve multi-scale flow coupling between free flow in macropores and seepage in matrix pores. This model can be further integrated with mineral composition and fluid mass conservation equations to enable multi-scale reactive flow simulation under coupled free flow and seepage conditions. Under deep stress conditions, a multi-scale flow simulation of digital cores considering fluid-solid damage has been implemented based on continuum damage theory, clarifying the effects of different stress conditions on pore structure and apparent permeability of the core. This provides a robust predictive method for flow simulation in the development of deep oil and gas resources.
| Country | China |
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