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Geothermal exploration and production are challenging, expensive and risky. The GeoThermalCloud uses Machine Learning to predict the location of hidden geothermal resources. This submission includes a training dataset for the GeoThermalCloud neural network. Machine Learning for Di...
This dataset contains seismic-reflection records created in 2010 around the Soda Lake geothermal field near Fallon, Nevada. The data was collected by the power plant operator at the time, Magma Energy (CYRQ Energy in 2024). This was a petroleum-industry-quality three-dimensional ...
In this paper, we present an analysis using unsupervised machine learning (ML) to identify the key geologic factors that contribute to the geothermal production in Brady geothermal field. Brady is a hydrothermal system in northwestern Nevada that supports both electricity producti...
The Imperial Valley Dark Fiber Project acquired Distributed Acoustic Sensing (DAS) seismic data on a ~28 km segment of dark fiber between the cities of Calipatria and Imperial in the Imperial Valley, Southern California. Dark fiber refers to unused optical fiber cables in telecomm...
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...
This report presents a series of numerical experiments investigating the relationships among near-well fracture complexity, in situ stress conditions, and wellbore deviation. Using a phase-field modeling approach, the study explores how factors such as stress regimes, wellbore ori...
Geothermal power plants typically show decreasing heat and power production rates over time. Mitigation strategies include optimizing the management of existing wells increasing or decreasing the fluid flow rates across the wells and drilling new wells at appropriate locations. Th...
This document describes the design requirements for the geothermal heat pump (GHP) module being added to the existing REopt Lite web tool. This document describes the purpose, users, and functional requirements to which the modified web tool shall conform. This document will be re...
Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information...
This dataset covers work that investigated the apparent toughness anisotropy at Utah FORGE by comparing microseismic data with stress profiles from field measurements. The study analyzes the hydraulic fracture growth of Stage 3 at Well 16A(78)-32 using MEQ data, calibrating a nume...
Probabilistic Multi-Horizon Spatiotemporal Forecasting of Injection-Induced Seismicity in Geothermal Systems
Companion code for the manuscript by Zhengfa Bi (Lawrence Berkeley National Laboratory) and Nori Nakata (Lawrence Berkeley National Laboratory; MIT).
Fluid injection and ...
This dataset contains distributed acoustic sensing (DAS) data collected during the April 2024 mini-circulation test at the Utah FORGE site. Data were acquired from wells 16B(78)-32 and 58-32 during the mini-circulation period from April 23-28, 2024, following stimulation of the in...
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