Japan Geoscience Union Meeting 2018

Presentation information

[JJ] Oral

H (Human Geosciences) » H-SC Social Earth Sciences & Civil/Urban System Sciences

[H-SC05] CCUS (Carbon Dioxide Capture, Utilization, and Storage) for Climate Mitigation

Wed. May 23, 2018 9:00 AM - 10:30 AM 201B (2F International Conference Hall, Makuhari Messe)

convener:Masao Sorai(Institute for Geo-Resources and Environment, National Institute of Advanced Industrial Science and Technology), Ziqiu Xue(Research Institute of Innovative Tech for the Earth), Masaatsu Aichi(東京大学大学院新領域創成科学研究科), Chairperson:Xue Ziqiu(Research Institute of Innovative Technology for the Earth)

9:15 AM - 9:30 AM

[HSC05-02] A parallel scheme for accelerating optimization of well placement for geologic CO2 storage

*MIYAGI ATSUHIRO1, Hajime YAMAMOTO1, Youhei AKIMOTO2, Ziqiu XUE3 (1.Taisei Corporation , 2.Shinshu University , 3.Reserch Institute of Innovative Technology for the Earth)

Keywords:Carbon dioxides Capture and Storage, Well placement, Covariance Matrix Adaptation Evolution Strategy, Oakforest-PACS

Carbon dioxides Capture and Storage (CCS) is a viable technique for reducing the amount of CO2 emitted to the atmosphere by injecting captured CO2 into reservoirs underground. When we consider commercial-scale CCS with more than 1Mt/y injection rate, the placement strategy of multiple injection wells is significant to sequestrate required volume of CO2 in the reservoir. In addition, pressure relief well might be effective to mitigate build-up pressure in the reservoir due to the large volume injection. These well locations should be determined effectively because it affects allowable volume of CO2 injection and project cost. However, selecting optimum solution from a huge number of simulations by manually changing well locations is not realistic. Therefore, automatic and efficient optimization methods that can reduce number of reservoir simulations and obtain beneficial solution will be essential.

In this study, we developed a new tool by combining an optimization algorithm, Covariance Matrix Adaptation Evolution strategy (CMA-ES), with a parallel reservoir simulator TOUGH2-MP. However, a few thousands of the reservoir simulations for solution candidates are usually needed to obtain an optimum solution. Thus it is often difficult to find an optimum solution within realistic time. Therefore, we implemented our optimization tool on a supercomputer (Oakforest-PACS) for reducing the computational time of optimization by running reservoir simulations for many solution candidates concurrently utilizing thousands of CPU cores in parallel. The performance of the tool was investigated and demonstrated through an optimization problem of placement of multiple wells for injection and pressure-relief on a hypothetical reservoir model with heterogeneous properties.