An Open-Source Tool for Operational Forecasting of Induced Seismicity (Orion)
Forecasting induced seismicity activity is one of the challenges facing the growing fields of geothermal energy production and carbon sequestration. Historically, the forecasting process has required significant effort from experts in seismology, geomechanics, and reservoir engineering in order to manage data, evaluate models of subsurface processes, and to calibrate and interpret the results from a range of forecasting models. The Operational Forecasting of Induced Seismicity (ORION) toolkit is an open-source, observation-based forecasting toolkit that is being co-developed by the National Risk Assessment Partnership (NRAP) and the Science-informed Machine Learning for Accelerating Real Time Decisions in Subsurface Applications (SMART) Initiative to address these issues. One of the major design goals for ORION was to build a tool that is responsive to the needs of users ranging from site operators to expert seismologists. The code is written in python and is composed of a desktop graphical user interface (GUI) and an underlying forecasting engine. The forecasting engine takes available reservoir property, well and fluid injection, and observed seismic catalog data as inputs and produces a set of temporal and spatio-temporal seismic forecasts.
The in-situ fluid pressurization rate (dpdt) is one of the key factors that drives the forecast model predictions. Rather than evaluating a full-physics model of the reservoir, ORION has options that allow the user to estimate dpdt using efficient closed-form solutions (e.g. the Theis model), machine learning models, other reduced order models, or to interpolate pre-computed results from external tools. The forecasting engine implements multiple, redundant forecasting methods that are based on statistical principles and/or physical models. ORION uses a decision-tree model to mediate between these different forecasts and produce an ensemble model.
This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract DE-AC52-07NA27344.
Session: Seismic Monitoring, Modelling and Management Needed for Geothermal Energy and Geologic Carbon Storage - I
Type: Oral
Room: Tikahtnu Ballroom A
Date: 5/2/2024
Presentation Time: 08:30 AM (local time)
Presenting Author: Kayla Kroll
Student Presenter: No
Additional Authors
Kayla Kroll Presenting Author Corresponding Author kroll5@llnl.gov Lawrence Livermore National Laboratory |
Christopher Sherman sherman27@llnl.gov Lawrence Livermore National Laboratory |
Gina-Maria Geffers geffers1@llnl.gov Lawrence Livermore National Laboratory |
Chaoyi Wang wang140@llnl.gov Lawrence Livermore National Laboratory |
David He he12@llnl.gov Lawrence Livermore National Laboratory |
Corinne Layland-Bachmann cebachmann@lbl.gov Lawrence Berkeley National Laboratory |
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An Open-Source Tool for Operational Forecasting of Induced Seismicity (Orion)
Category
Seismic Monitoring, Modelling and Management Needed for Geothermal Energy and Geologic Carbon Storage
Description