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Aug 18, 2023

LLNL computational geoscientist Chris Sherman (left) and seismologist Kayla Kroll demonstrate the Operational FoRecasting for Induced Seismicity (ORION) toolkit that was funded by the Department of Energy Office of Fossil Energy and Carbon Management under the National Risk Assessment Partnership and the Science-Informed Machine Learning for Accelerating Real-Time Decision in Subsurface Application Initiative. ORION is a physics-based seismic-forecasting software platform to help operators and regulators better understand and manage seismic hazards at carbon storage sites.

(Photo by Blaise Douros)

Lawrence Livermore National Laboratory (LLNL) has partnered with another national lab and a seismic instrumentation monitoring company to develop a physics-based seismic-forecasting software platform to help operators and regulators better understand and manage seismic hazards at carbon storage sites.

LLNL scientists have worked with researchers from Lawrence Berkeley National Laboratory (LBNL) and Ottawa, Canada-based Nanometrics, Inc. to develop the Operation FoRecastingof Induced Seismicity (ORION) toolkit, an open-source software platform. Commercial-scale carbon-storage operations face significant risk of inducing seismicity when fluids are disposed of in the Earth’s subsurface. Induced earthquakes, or seismic events generated by anthropogenic activities, may damage property and threaten the integrity of shallower sealing units, allowing carbon dioxide, or CO2, to escape. While most operations will experience low-level tremors, it is possible that larger-magnitude earthquakes may occur. Such events can lead to interruption of CO2 injection at a single storage site or erode confidence in the entire industry. To manage these risks, individual operators must understand both the current and future seismic hazards at a storage site and regulators must be able to evaluate the seismic hazard on the basin-scale. “CO2 storage is an essential component of effective climate mitigation and induced seismicity must be managed to enable large-scale deployment,” said Joe Morris, associate leader for the LLNL Subsurface Energy Program. “ORION puts the power of statistical and machine-learning techniques in the hands of operators, enabling them to manage these subsurface systems more safely and efficiently. The complex combination of technologies and expertise contained within ORION would not have been possible without national lab leadership.” LLNL Energy Program Leader Dan Flowers agreed with Morris’s assessment of the importance of the national labs working on this problem. “ORION leverages decades of national lab leadership in high-fidelity measurements and physics-based simulations of seismological processes in the subsurface. I am thrilled that the open-source release of ORION will provide industry and decision makers with a powerful tool to help accelerate deployment of CO2 storage at scale,” Flowers said. ORION incorporates independent physics-, statistics- and machine-learning-based forecasts supported by analytic, observational and physics-based estimates of the evolution of pressure and stress related to injection. ORION also provides analysis of the seismic hazard before, during and after injection and can gauge the effectiveness of potential mitigation strategies, such as reducing the volume of fluid injected into a well, or modulating injection rates in several wells to manage risks where induced earthquakes have exceeded tolerance thresholds. The ORION toolkit provides an easy-to-use interface for forecast generation and visualization of seismic hazard. Basic functionalities provide the user with estimates of the seismic hazard at a location based on publicly available data sources from the United States Geological Survey and state regulatory agencies. Advanced capabilities allow users to upload local, high-precision earthquake catalogs, projected injection profiles and/or spatiotemporal estimates of pressure and stress and various rock and fluid property parameters. ORION then produces a spatial, temporal ensemble forecast of seismicity or probability of inducing an earthquake during the forecast period. ORION also generates a distribution of a statistically derived maximumpossible earthquakemagnitude expected. ORION also proposes operational management strategies, such as reducing injection volumes at specific wells, based on the hazard level. Development of ORION leverages multi-disciplinary technical expertise at LLNL and LBNL including earthquake physics and nucleation, statistical seismology, reservoir geomechanics, machine learning and software engineering. ORION was funded jointly through two U.S. DOE Office of Fossil Energy and Carbon Management-sponsored, Bipartisan Infrastructure Law-funded applied research projects: the National Risk Assessment Partnership and the Science-informed Machine Learning to Accelerate Real-Time Decisions in Subsurface Applications Initiative. ORION was developed by LLNL seismologist Kayla Kroll, LLNL’s Christopher Sherman, who specializes in computational geomechanics; and former LBNL geophysicist Keurfon Luu.

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