Speaker
Description
We developed a new methodology to compute hydraulic transmissibility between karst-conduits and rock matrix in carbonate reservoirs. Such a parameter quantifies the mass exchange between these two geological objects and can be explored in EDKM-type models (Embedded Discrete Karst Model) via non-neighboring connections. The upscaling procedure adopted hinges on the karst index concept, whose underlying physics relies on the generalization of the traditional Peaceman’s theory of well index to more complex scenarios of coupled flow in karst conduit systems displaying general non-circular cross sections. Within the proposed procedure, we adopt the flow-based upscaling method to compute mass transfer between conduits and matrix for several configurations of conduits lying within cells of a coarse grid. The corresponding transmissibility value associated with each scenario is stored in a database. Subsequently, a machine learning model is trained on the numerical results in the dataset, using information related to the geometry of the karst-conduits as input attributes, and the transmissibilities computed with numerical simulations as target values. Numerical experiments are carried-out exhibiting the magnitude of the transmissibility for certain conduit arrangements, along with the magnitude determined by the machine learning algorithm. The results illustrate the potential of the methodology proposed herein. The novel approach can be applied to both aquifers and carbonate reservoirs, providing more accurate predictions and enhancing the management of such resources.
| Country | Brazil |
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