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Understanding the relationship between stress state, strain state and fracture initiation and propagation is critical to the improvement of fracture simulation capability if it is to be used as a tool for guiding hydraulic fracturing operations. The development of fracture predict...
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulat...
This is a presentation on Real-Time Robust Adaptive Traffic Light System and Reservoir Engineering with Machine-Learning-Based Seismicity Forecasting and Data-Driven Ground Motion Prediction (RT Forecast) by Lawrence Berkeley National Laboratory, presented by Nori Nakata. This vid...
These two reports from the University of Pittsburgh document related efforts under Utah FORGE Project 2-2439v2 to estimate in-situ stresses in well 16B(78)-32 using laboratory data, machine learning models, and physics-based simulations. One report focuses on developing and valida...
This submission contains datasets and a final manuscript associated with a project simulating carbon dioxide push-pull into a conjugate fault system modeled after Dixie Valley-
sensitivity analysis of significant parameters and uncertainty prediction by data-worth analysis.
Datas...
This report presents the far-field stress predictions at two locations along the vertical section of Utah FORGE Well 16A (78)-32 using a physics-based thermo-poro-mechanical model. Three principal stresses in far-field were obtained by solving an inverse problem based on the near-...
This report reviews the training of machine learning algorithms to laboratory triaxial ultrasonic velocity data for Utah FORGE Well 16A(78)-32. Three machine learning (ML) predictive models were developed for the prediction of vertical and two orthogonally oriented horizontal str...
This task completion report documents the development and implementation of machine learning (ML) models for the prediction of in-situ vertical (Sv), minimum horizontal (SHmin) and maximum horizontal (SHmax) stresses in well 16A(78)-32. The detailed description of the experimental...
A review of brine chemistry data for the Mt. Simon Sandstone in the Illinois Basin is provided for calculations to predict the potential for mineral scaling and precipitation. The assessment includes expected changes in temperature, pressure, and/or exposure to air or other materi...
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 is a presentation on the Probabilistic Estimation of Seismic Response Using Physics-Informed Recurrent Neural Networks by GTC Analytics, presented by Dr. Jesse Williams. This video slide presentation discusses the development of machine learning-based predictive tools to esti...
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 ...
The Utah FORGE 2025 v1 DFN (fracture model) includes 131 discrete planar fractures which were identified using combined site data sets to capture flow pathways between wells 16A(78)-32 and 16B(78)-32 following stimulation activities in 2022 and 2024. It also includes stochastic fr...
This submission includes a methods report and an accompanying Excel dataset documenting temperature-dependent Mode-I fracture toughness (KIC) measurements for Utah FORGE granite obtained using semi-circular bending (SCB) tests in accordance with the ISRM Suggested Method. Testing ...
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...
This paper describes the applications of the fractured continuum model to the different enhanced geothermal systems reservoir conditions. The capability of the fractured continuum model to generate fracture characteristics expected in enhanced geothermal systems reservoir environm...
This report provides insights into Utah FORGE well 58-32's hydraulic fractures. It utilizes both electrical borehole scans from Schlumberger's Formation Micro-scanner Image tool (FMI) and Stoneley waves from a borehole sonic tool. These methods are combined in a comprehensive work...
This dataset contains the final technical report for the project Joint Electromagnetic/Seismic/InSAR Imaging of Spatial-Temporal Fracture Growth and Estimation of Physical Fracture Properties During EGS Resource Development, carried out from 2021 to 2025 by Lawrence Berkeley Natio...
This package includes data and models that support hydraulic fracture stimulation and fluid circulation experiments in the Sanford Underground Research Facility (SURF). A paper by Schwering et al. (2020) describes the deterministic basis for developing a "common" discrete fracture...
Data from high temperature dynamic sealing tests for various fracture widths, at various temperatures (degrees F), with 5 wt.% bentonite-based mud containing various material fiber contents, at 100 to 400 psi differential pressure.
Data from pressure test and evaluation of the dy...
This is a report that describes the modelling of fracture nucleation and propagation in the near-wellbore region to understand the relationship between in situ stress and fracture patterns. A novel phase field formulation is described here, which represents fractures as a diffuse ...
This a report for the project "Mapping Fracture Network Creation with Microseismicity During EGS Demonstrations". Effective enhanced geothermal systems (EGS) require optimal fracture networks for efficient heat transfer between hot rock and fluid. Microseismic mapping is a key too...
A Schlumberger Fullbore Formation Micro-Imager (FMI) log was run from 7390 feet to 7527 feet depth in well 58-32, originally known as well MU-ESW1. Well 58-32 was completed in 2017 as part of Utah FORGE Phase 2. It reached a depth of 7536 feet and recorded a bottom hole temperatur...
Provided here is a set of presentation slides detailing stress-dependent permeability in FORGE granitoid fractures and how fracture slip affects permeability. It outlines empirical correlations between permeability, stress, and fracture aperture, emphasizing that mechanically clos...
The evolution of flow pattern along a single fracture and its effects on heat production is a fundamental problem in the assessments of engineered geothermal systems (EGS). The channelized flow pattern associated with ubiquitous heterogeneity in fracture aperture distribution caus...
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