Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented...Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented in oil shale exploitation.However,accurately capturing the intricate flow dynamics of ICP requires a large number of fine-scale grid-blocks,which renders ICP simulations computationally expensive.Apart from that,plenty of oil shale reservoirs contain natural fractures or require hydraulic fracturing to enhance fluid mobility,creating further challenges in modeling pyrolysis reactions in both rock matrices and fractures.Targeted at the above issues,this work proposes a novel dual-model dualgrid upscaling(DDU)method specifically designed for solid-based thermal-reactive-compositional flow simulations in fractured porous media.Unlike existing upscaling techniques,the DDU method incorporates the upscaling of fracture grids using the embedded discrete fracture modeling(EDFM)approach and introduces a new concept of simplified models to approximate fine-scale results,which are used to correct reaction rates in coarse-scale grids.This method uniquely achieves efficient upscaling for both matrix and fracture grids,supports both open-source and commercial simulation platforms without modifying source codes,and is validated through 3D ICP models with natural fractures.The results indicate that the application of the DDU method can provide a close match with the fine-scale simulation results.Moreover,the DDU method has drastically improved the computational efficiency and speeded up the fine-scale simulation by 396-963 times.Therefore,the proposed DDU method has achieved marked computational savings while maintaining high simulation accuracy,which is significant for the development efficiency and production forecasting of oil shale reservoirs.展开更多
基金the financial support from the National Science Foundation of China(No.52374063 and No.52204065)the Natural Science Foundation of Shandong Province,China(No.ZR2023ME049 and No.ZR2021JQ18)the Fundamental Research Funds for the Central Universities,China(24CX06017A)。
文摘Simulation of thermal-reactive-compositional flow processes is fundamental to the thermal recovery of ultra-heavy hydrocarbon resources,and a typical oilfield practice is the in-situ conversion process(ICP)implemented in oil shale exploitation.However,accurately capturing the intricate flow dynamics of ICP requires a large number of fine-scale grid-blocks,which renders ICP simulations computationally expensive.Apart from that,plenty of oil shale reservoirs contain natural fractures or require hydraulic fracturing to enhance fluid mobility,creating further challenges in modeling pyrolysis reactions in both rock matrices and fractures.Targeted at the above issues,this work proposes a novel dual-model dualgrid upscaling(DDU)method specifically designed for solid-based thermal-reactive-compositional flow simulations in fractured porous media.Unlike existing upscaling techniques,the DDU method incorporates the upscaling of fracture grids using the embedded discrete fracture modeling(EDFM)approach and introduces a new concept of simplified models to approximate fine-scale results,which are used to correct reaction rates in coarse-scale grids.This method uniquely achieves efficient upscaling for both matrix and fracture grids,supports both open-source and commercial simulation platforms without modifying source codes,and is validated through 3D ICP models with natural fractures.The results indicate that the application of the DDU method can provide a close match with the fine-scale simulation results.Moreover,the DDU method has drastically improved the computational efficiency and speeded up the fine-scale simulation by 396-963 times.Therefore,the proposed DDU method has achieved marked computational savings while maintaining high simulation accuracy,which is significant for the development efficiency and production forecasting of oil shale reservoirs.
