Comparison and optimization of multiple interacting continua (MINC) model parameters

Date

2023-9-5

Author

Demir, Ebru Berna

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In recent years, unconventional reservoirs have become a new trend in the oil industry because of the decrease in conventional hydrocarbon reserves. One of the commonly encountered types is shale gas reservoirs, where gas production can be enhanced with fracturing. Reservoir simulation has been significantly important to have future predictions for a long time. Understanding the transport processes in naturally fractured reservoirs is challenging compared to unfractured reservoirs. While matrix has extremely low permeability, fracture has extremely high permeability. Mainly two numerical conceptual models can be applied to this type of fractured reservoirs which are Continuum Fracture Model (CFM) and Discrete (DFM) Fracture Model (DFM). CFM requires calculation of some specific transfer parameters (shape factors, volume fractions etc.) implicitly to interpret transport processes between the matrix continua and fracture continuum. DFM requires huge computation power and cost to analyze fractures explicitly. Conductivity and connectivity of fractures are taken into account individually. This thesis focuses on parameter estimation of Multiple Interacting Continua (MINC) one of CFM models by taking DFM as a reference solution. The objective function for parameter estimation is mass storage rate deviation from DFM model simulated on a Bristol geometry, located along the Bristol Channel coast in the United Kingdom. The computation cost of MINC model is more efficient compared to DFM model and requires fewer pre-processing efforts for geometry discretization. Volume fractions can be calculated on a representative part of the domain and can be used for the hole reservoir as long as the reservoir has the same fracture distribution as the representative part of the field.

Subject Keywords

Continuum fracture modeling, Discrete fracture network, Multiple interacting continua, Upscaling, Volume fractions

URI

https://hdl.handle.net/11511/105497

Collections

Graduate School of Natural and Applied Sciences, Thesis