Flow Optimization for Wormhole Regions of Post-CHOPS Reservoirs

This project aims to provide Canadian petroleum companies a comprehensive big-data-analytics tool that concludes the essential controlling parameters which enable successful experimental and numerical studies on CO2-based solvent injection processes in post-CHOPS reservoirs. The proposed database includes relevant experimental research work that expand through multiple experimentation scales, as well as relevant numerical research work that cover from pore network simulation, Darcy-scale reservoir simulation, CFD simulation etc. From experimental database, relevance between physical controlling parameters and recovery performances will be investigated. This enables the selection of the optimum operating schemes in oil field development. From numerical database, the most frequently tuned parameters in Darcy-scale reservoir simulations which facilitate successful history matching can be extracted so as to narrow down the parameters’ adjustment range and thus enhance the efficiency of field-scale simulation and production prediction. Meanwhile, foamy oil stability enhancement, residual oil remobilization, and high-permeability wormhole blockage will be investigated by a state-of-the-art microfluidics laboratory, and such findings will be added into the big data analytics tool for deeper and continuous training and validation. Altogether, flow optimizations for wormhole regions of post-CHOPS reservoirs will be realized.

Intern: 
Aria Rahimbakhsh
Faculty Supervisor: 
Farshid Torabi
Province: 
Saskatchewan
Partner University: 
Program: