Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study

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This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model 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 seismic resolution study used borehole and surface seismic sensors as well as the seismicity observed during the April 2022 stimulation experiment to estimate the seismic resolution in the activated fracture reservoir.

The data contain a 3D P- and S-wave velocity model for the larger FORGE area.

Citation Formats

TY - DATA AB - This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model 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 seismic resolution study used borehole and surface seismic sensors as well as the seismicity observed during the April 2022 stimulation experiment to estimate the seismic resolution in the activated fracture reservoir. The data contain a 3D P- and S-wave velocity model for the larger FORGE area. AU - Vasco, Don A2 - Chan, Coral DB - Geothermal Data Repository DP - Open EI | National Renewable Energy Laboratory DO - 10.15121/1989942 KW - geothermal KW - energy KW - seismic velocity model KW - seismic resolution KW - 3D P-wave KW - 3D S-wave KW - seismic KW - raw data KW - processed data KW - well 16A-32 KW - Utah FORGE LA - English DA - 2022/04/30 PY - 2022 PB - Array Information Technology T1 - Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study UR - https://doi.org/10.15121/1989942 ER -
Export Citation to RIS
Vasco, Don, and Coral Chan. Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study. Array Information Technology, 30 April, 2022, Geothermal Data Repository. https://doi.org/10.15121/1989942.
Vasco, D., & Chan, C. (2022). Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study. [Data set]. Geothermal Data Repository. Array Information Technology. https://doi.org/10.15121/1989942
Vasco, Don and Coral Chan. Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study. Array Information Technology, April, 30, 2022. Distributed by Geothermal Data Repository. https://doi.org/10.15121/1989942
@misc{GDR_Dataset_1496, title = {Utah FORGE: Development of a Reservoir Seismic Velocity Model and Seismic Resolution Study}, author = {Vasco, Don and Chan, Coral}, abstractNote = {This is data from and a final report on the development of a 3D velocity model for the larger FORGE area and on the seismic resolution in the stimulated fracture volume at the bottom of well 16A-32. The velocity model 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 seismic resolution study used borehole and surface seismic sensors as well as the seismicity observed during the April 2022 stimulation experiment to estimate the seismic resolution in the activated fracture reservoir.

The data contain a 3D P- and S-wave velocity model for the larger FORGE area.}, url = {https://gdr.openei.org/submissions/1496}, year = {2022}, howpublished = {Geothermal Data Repository, Array Information Technology, https://doi.org/10.15121/1989942}, note = {Accessed: 2025-05-07}, doi = {10.15121/1989942} }
https://dx.doi.org/10.15121/1989942

Details

Data from Apr 30, 2022

Last updated Aug 22, 2024

Submitted Apr 24, 2023

Organization

Array Information Technology

Contact

Roland Gritto

510.704.1848

Authors

Don Vasco

Lawrence Berkeley National Laboratory

Coral Chan

University of California Berkeley

DOE Project Details

Project Name Utah FORGE

Project Lead Lauren Boyd

Project Number EE0007080

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