Journal
NATURAL RESOURCES RESEARCH
Volume 30, Issue 3, Pages 2543-2559Publisher
SPRINGER
DOI: 10.1007/s11053-021-09837-1
Keywords
Gravity drainage; Naturally fractured reservoir; Scaling equations; Inspectional analysis; Dual-porosity simulation; Transfer function in naturally fractured reservoirs
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This paper discusses the complex interactions and transfer functions in the production mechanism of naturally fractured reservoirs, proposing a new scaling equation for predicting oil production recovery.
During production from naturally fractured reservoirs, complex interactions exist between matrix blocks and gas-filled fractures in the gas invaded zone. Considerable efforts such as defining complicated transfer functions between matrix blocks and the fractured medium have been made for a sensible description of this production mechanism. In addition, several studies have revealed that scaling equations can be an efficient method for proper description of these complex phenomena in naturally fractured reservoirs. In this paper, some limitations of the existing transfer functions are illustrated first. Then, by using inspectional analysis, a new dimensionless scaling equation is proposed to scale and predict recovery of oil production from a matrix block during the gravity drainage process. Employing the presented scaling equation, for various test cases with different properties, shows significant applicability to scale the curves of ultimate recoveries into one single curve. As a result, the drainage rate of matrix blocks under gravity drainage could be scaled and predicted. One usage of the findings of this work could be improving the result of the dual-medium simulations in the naturally fractured reservoirs. Moreover, the findings prove that using the presented scaling equation as a transfer function in the dual-medium approach remarkably enhances the prediction of oil recovery compared with some other well-known transfer functions. Using a statistical method showed that applying the new presented scaling equation in the dual-medium approach reduces the error amount by at least 22.62%.
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