Insights of using Control Theory for minimizing Induced Seismicity in Underground Reservoirs
Deep Geothermal Energy, Carbon Capture, and Storage and Hydrogen Storage have significant potential to meet the large-scale needs of the energy sector and reduce the CO$_2$ emissions. However, the injection of fluids into the earth's crust, upon which these activities rely, can lead to the formation of new seismogenic faults or the reactivation of existing ones, thereby causing earthquakes. In this study, we propose a novel approach based on control theory to address this issue. First, we obtain a simplified model of induced seismicity due to fluid injections in an underground reservoir using a diffusion equation in three dimensions. Then, we design a robust tracking control approach to force the seismicity rate to follow desired references. In this way, the induced seismicity is minimized while ensuring fluid circulation for the needs of renewable energy production and storage. The designed control guarantees the achievement of the control objectives even in the presence of system uncertainties and unknown dynamics. Finally, we present simulations of a simplified geothermal reservoir under different scenarios of energy demand to show the reliability and performance of the control approach, opening new perspectives for field experiments based on real-time regulators.
Code (0)
등록된 구현이 없습니다.
Methods 이 논문이 사용한 방법론
Similar Papers 제목 키워드 기반
AI-Driven approach for sustainable extraction of earth's subsurface renewable energy while minimizing seismic activity
Deep Geothermal Energy, Carbon Capture and Storage, and Hydrogen Storage hold considerable promise for meeting the energy sector's large-scale requirements and reducing CO$_2$ emissions. However, the injection of fluids …
reinforcement-learningReinforcement LearningRobust Output Tracking for an Uncertain and Nonlinear 3D PDE-ODE System: Preventing Induced Seismicity in Underground Reservoirs
This paper presents a robust control strategy for output tracking of a nonlinear 3D PDE-ODE system, where the ODE has logistic-like dynamics. The output feedback control was developed by bounding the solution and its tim…
continuous-controlContinuous ControlJuxtaposition of Shallow Reservoir-Triggered Seismicity and Deep Tectonic Locking in the Qiaojia-Dongchuan Seismic Gap
Identifying the critical state of mature seismic gaps is challenging, especially when anthropogenic stress perturbations, such as reservoir impoundment, superimpose on tectonic loading. Here, utilizing a high-resolution …
Controlling earthquake-like instabilities using artificial intelligence
Earthquakes are lethal and costly. This study aims at avoiding these catastrophic events by the application of injection policies retrieved through reinforcement learning. With the rapid growth of artificial intelligence…
Deep Reinforcement Learningreinforcement-learningReinforcement LearningReinforcement Learning (RL)Machine learning for sustainable geoenergy: uncertainty, physics and decision-ready inference
Geoenergy projects (CO2 storage, geothermal, subsurface H2 generation/storage, critical minerals from subsurface fluids, or nuclear waste disposal) increasingly follow a petroleum-style funnel from screening and appraisa…
Continual Learning