TY - DATA
AB - This report describes the development of a preliminary 3D seismic velocity model at the Utah FORGE site and first results from estimating seismic resolution in the generated fracture volume during Stage 3 of the April 2022 stimulation.
A preliminary 3D velocity model for the larger FORGE area was developed using RMS velocities of the seismic reflection survey and seismic velocity logs from borehole measurements as an input model. To improve the accuracy of the model in the shallow subsurface, travel times phase arrivals of the direct propagating P-waves were determined from the seismic reflection data, using PhaseNet, a deep-neural-network-based seismic arrival time picking method. The travel times were subsequently inverted using the input velocity model. The results showed that the input velocity model needs improvement as the resulting model appears too fast in the easter region of the FORGE area. During the next phase of this work, we will update the input velocity model and generate P-wave arrival times for additional seismic source locations, to improve the horizontal resolution in the sedimentary layer and to obtain a model that better matches the sedimentary layer and the travel time observations.
AU - Gritto, Roland
DB - Open Energy Data Initiative (OEDI)
DP - Open EI | National Renewable Energy Laboratory
DO -
KW - geothermal
KW - energy
KW - 3D seismic velocity model
KW - seismic resolution
KW - seismic
KW - geophysics
KW - reservoir
KW - model
KW - velocity
KW - FORGE
KW - Utah FORGE
KW - EGS
KW - characterization
KW - report
KW - preliminary
KW - Milford
KW - PhaseNet
KW - neural networking
KW - machine learning
KW - deep learning
LA - English
DA - 2023/01/30
PY - 2023
PB - Array Information Technology
T1 - Utah FORGE LBNL 3-2535 Preliminary Report on Development of a Reservoir Seismic Velocity Model
UR - https://data.openei.org/submissions/
ER -