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Numerical modeling on fused silica cylindrical materials for predicting overpressures required to fracture an homogeneous pure (surrogate) material with known mechanical properties similar to igneous rock materials and later compare these values to experimental overpressures obtai...
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...
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...
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...
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 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 ...
This dataset includes reports and a slide presentation on discrete fracture network (DFN) generation and hydraulic fracture modeling at the Utah FORGE site. It details the characterization of natural fractures using well log and core data, as well as stochastic modeling techniques...
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...
This submission contains 167 deviatoric moment tensor (MT) solutions for the seismicity observed two years prior and three years post start of injection activities at The Geysers Prati 32 EGS Demonstration. Also included is a statistical representation of the properties of 751 fra...
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...
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...
This project focused on assessment and discovery of fluid-rock interaction in geothermal reservoirs. We accomplished work in four main areas: 1) fracture formation and the relationship between fluid flow and shear failure, 2) assessment of fracture geometry and fluid permeability ...
This dataset contains the final technical report and closeout presentation for Utah FORGE Project 4-2492, which investigated advanced stimulation design and diagnostic approaches to improve fracture uniformity, inter-well connectivity, and energy recovery efficiency in enhanced ge...
This is the final technical report documenting laboratory experiments and modeling conducted to characterize the thermo-poromechanical behavior of fractured crystalline rocks for application to Utah FORGE. The report includes measurements of poroelastic and thermo-poroelastic prop...
This report discusses the results of research on the ability to create and/or reactivate and subsequently sustain fracture systems which are strongly influenced by complexly coupled mechanical (M) and chemical (C) processes in reservoirs forced from equilibrium by hydraulic stimul...
The Utah FORGE 2024 Discrete Fracture Network (DFN) Model dataset provides a set of files representing discrete fracture network modeling for the FORGE site near Milford, Utah. The dataset includes four distinct DFN model file sets, each corresponding to different time frames and ...
This dataset contains drilling core data from well 16B(78)-32, including PDF documents with flattened core images annotated by feature type and core interval, as well as spreadsheets detailing feature morphologies by depth, planar feature measurements, and planar feature orientati...
Hydraulic shearing is an appealing reservoir stimulation strategy for Enhanced Geothermal Systems. It is believed that hydro-shearing is likely to simulate a fracture network that covers a relatively large volume of the reservoir whereas hydro-fracturing tends to create a small nu...
The FORGE team is making these fracture models available to researchers wanting a set of natural fractures in the FORGE reservoir for use in their own modeling work. They have been used to predict stimulation distances during hydraulic stimulation at the open toe section of well 1...
This report presents geodetic observations from the April 2024 stimulations at the Utah FORGE site, as part of LBNL FORGE Project 3-2535. It focuses on Distributed Strain Sensing (DSS) data from an optical fiber in well 16B, capturing localized strain linked to fracture propagatio...
Visualize the Utah FORGE DFN model in three-dimensional space using the Seequent Central public viewer. 131 discrete planar fractures have been interpreted by Aleta Finnila (https://gdr.openei.org/submissions/1750) from various data sets obtained during the 2022 and 2024 stimulati...
This is a presentation on the Design and Implementation of Innovative Stimulation Treatments to Maximize Energy Recovery Efficiency at the Utah FORGE Site project by The University of Texas at Austin, presented by Professor Mukul M. Sharma. The project's objectives were to place f...
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