Numerical Error Quantification of Agent-Based Models as Applied to Oil Reservoir Simulation
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Agent-based models (ABMs) provide a fast alternative to traditional oil reservoir models by applying localized inexpensive simulations, rather than solving a partial differential equation at every time-step. However, while there have been theoretical and numerical results obtained with ABMs in social science applications, the accuracy of ABMs has not been analyzed in the context of oil reservoir modeling. My project quantifies the accuracy of a specific ABM by comparing its results to a widely accepted reservoir model, based on Darcy's law. I show that while modeling single phase flow with a variety of reservoir scenarios, this ABM matches results given by the traditional simulator with less than 5.4% difference. I propose extensions of my work, including modeling two and three phase flow, and obtaining an accurate correlation between the ABM and traditional simulator parameters; such results would provide significant motivation in the extended use of ABMs in oil reservoir modeling.
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Doyle, Bryan. "Numerical Error Quantification of Agent-Based Models as Applied to Oil Reservoir Simulation." (2018) Master’s Thesis, Rice University. https://hdl.handle.net/1911/105634.