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GOOML Big Kahuna Forecast Modeling and Genetic Optimization Files

Jun 30, 2021
13.6 MB
Publicly accessible
This submission includes example files associated with the Geothermal Operational Optimization using Machine Learning (GOOML) Big Kahuna fictional power plant, which uses synthetic data to model a fictional power plant. A forecast was produced using the GOOML data model framework ...
Authors
Buster, G. et al Upflow
geothermalenergymachine learningoptimizationoperationssynthetic datapower plantbig kahunagoomlgenetic optimizationforecastinputsoutputsconfigurationexamplephygnnphysics guided neural networkssteamfieldsteam fieldwellsflash plantsneural networkdataprocessed datacodepythonsimulationmodel

GOOML Kahunanui Data Curation, Historical Modeling, Forecast Modeling, and Genetic Optimization Examples

Jan 30, 2023
725.34 MB
Awaiting release
This dataset contains example files and Jupyter Notebooks associated with the Geothermal Operational Optimization using Machine Learning (GOOML) framework, specifically for the fictional Kahunanui (KHN) geothermal power plant. The dataset includes synthetic time series data, confi...
Authors
Taverna, N. et al Upflow
geothermalenergymachine learninggoomlpower plantoptimizationgenetic optimizationregressionneural networkoperationssynthetic datakahunanuiforecasthindcastdata curationinputsoutputsconfigurationexamplephygnnphysics guided neural networkssteamfieldsteam fieldwellsflash plantsprocessed datapythonjupyter notebookmodelmodelingcode

Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments

May 05, 2021
Size unavailable
Publicly accessible
Active source ultrasonic data from lab experiments p5270 and p5271 including raw waveforms (WF) and mechanical data (mat). From the PSU team working on the "Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties" project. The fric...
Authors
Marone, C. Pennsylvania State University
geothermalenergyseismicactive sourcelaboratoryfriction experimentultrasonicgeophysicsmicroseismicitylab dataraw datawaveformsmechanical datapreprocessedmatlabacousticsacousticbiaxial testing apparatusultrasonic acoustic monitoring systemmachine learningdeep learningaiartificial intelligenceseismic forecastingearthquake forecastingfault

Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

May 14, 2021
6.01 MB
Publicly accessible
Machine learning can be used to predict fault properties such as shear stress, friction, and time to failure using continuous records of fault zone acoustic emissions. The files are extracted features and labels from lab data (experiment p4679). The features are extracted with a n...
Authors
Marone, C. et al Pennsylvania State University
geothermalenergymatlabgeophysicsseismiccodeprocessed datamicroseismicityaiartificial intelligencedeep learningmachine learningacousticsacoustic emissionsseismic forcastingseismic predictionfaultfault propertiesshear stresstime to failureexperimentexperimental datalab databiaxial shear experimentbiaxial shear apparatusfriction

Machine Learning-Assisted High-Temperature Reservoir Thermal Energy Storage Optimization: Numerical Modeling and Machine Learning Input and Output Files

Apr 15, 2022
113.79 MB
Publicly accessible
This data set includes the numerical modeling input files and output files used to synthesize data, and the reduced-order machine learning models trained from the synthesized data for reservoir thermal energy storage site identification. In this study, a machine-learning-assiste...
Authors
Jin, W. et al Idaho National Laboratory
reservoir thermal energy storagestochastic simulationgeotesmachine learningmodelingtesht-rtescharacterizationnumerical modelstochastichydrogeologic formationsimulated datasimulation datahigh-temperaturethermal energy storageoptimizationartificial neural network regressionannneural networkoperation scenariosseasonal-cyclepareto frontsseasonal operationcontinuous operationfalconmoose

Source Code for QuakeCastNet: Probabilistic Multi-Horizon Spatiotemporal Forecasting of Injection-Induced Seismicity

Sep 20, 2026
16.21 MB
Curated
This submission houses the companion code for the manuscript by Zhengfa Bi (Lawrence Berkeley National Laboratory) and Nori Nakata (Lawrence Berkeley National Laboratory; MIT). Both the companion code and manuscript are included in the resources section of this submission. Fluid ...
Authors
Nakata, N. and Bi, Z. Lawrence Berkeley National Laboratory
geothermalenergyutah forgeseismicitydeep learningthe geysersforecastegsinduced seismicityseismicity forecasting
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