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Utah FORGE 2-2404: Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE Workshop Presentation

This is a presentation on the Application of Advanced Techniques for Determination of Reservoir-Scale Stress State at Utah FORGE project by the University of Oklahoma, presented by Dr. Ahmad Ghassemi, McCasland Chair Professor. The project's objective was to develop a methodology ...

Ghassemi, A. University of Oklahoma

Sep 08, 2023
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Utah FORGE 2-2404: Determination of Reservoir-Scale Stress State Presentation Slides

This PowerPoint summarizes the integration of multiple approaches and data to constrain wellbore stress models at Utah FORGE. This stress determination used faulting theory, breakouts, and drilling-induced cracks detected in image logs. Wellbore stress profiles were established f...

Ghassemi, A. et al The University of Oklahoma

Jul 31, 2022
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Penn State Lab Testing Fluid-Rock Interaction in Geothermal Reservoirs

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 ...

Madara, B. et al Pennsylvania State University

Jan 01, 2018
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Utah FORGE 5-2428: Fracture Permeability Impact on Reservoir Stress and Seismic Slip Behavior Workshop Presentation

This is a presentation on the Fracture Permeability Impact on Seismic Slip Behavior project by Lawrence Livermore National Laboratory, presented by Dr. Kayla A. Kroll. The project's objective is to develop, apply and validate a holistic thermal, hydrologic, mechanical, and chemic...

Kroll, K. et al Lawrence Livermore National Laboratory

Sep 08, 2023
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Active Source Seismic (Ultrasonic) Data from Double-Direct Shear Lab Experiments

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...

Marone, C. Pennsylvania State University

May 05, 2021
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STRESSINVERSE Software for Stress Inversion

The STRESSINVERSE code uses an iterative method to find the nodal planes most consistent with the stress field given fault frictional properties. STRESINVERSE inverts the strike, rake and dip from moment tensor solutions for the in-situ state of stress. The code iteratively solves...

Gritto, R. Array Information Technology

Oct 31, 2018
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Data Arrays for Microearthquake (MEQ) Monitoring using Deep Learning for the Newberry EGS Sites

The 'Machine Learning Approaches to Predicting Induced Seismicity and Imaging Geothermal Reservoir Properties' project looks to apply machine learning (ML) methods to Microearthquake (MEQ) data for imaging geothermal reservoir properties and forecasting seismic events, in order to...

Zhu, T. Pennsylvania State University

May 05, 2021
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Utah FORGE: Fault Shear Reactivation Experimental Data for Fluid Injection-Rate Controls on Seismic Moment

Included are experimental data recorded from shear experiments that specifically explore the link between fluid-injection rate and seismic moment resulting from shear reactivation of laboratory faults. Raw mechanical data from three experiments are included alongside corresponding...

Roseboom, M. et al Pennsylvania State University

Nov 07, 2023
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Utah FORGE: Fault Reactivation Through Fluid Injection Induced Seismicity Laboratory Experiments

Included are results from shear reactivation experiments on laboratory faults pre-loaded close to failure and reactivated by the injection of fluid into the fault. The sample comprises a single-inclined-fracture (SIF) transecting a cylindrical sample of Westerly granite. All expe...

Yu, J. et al Pennsylvania State University

Jul 01, 2023
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Fault Information and Seismicity for the Portland Basin Deep Direct-Use Feasibility Study

Included in this dataset is a spreadsheet with the primary fault information used in the basin model, a spreadsheet with earthquake magnitude estimates, and a figure showing location of faults and microseismicity in the Portland Basin

Streig, A. and Wells, R. Portland State University

Dec 04, 2018
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Processed Lab Data for Neural Network-Based Shear Stress Level Prediction

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...

Marone, C. et al Pennsylvania State University

May 14, 2021
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Hybrid machine learning model to predict 3D in-situ permeability evolution

Enhanced geothermal systems (EGS) can provide a sustainable and renewable solution to the new energy transition. Its potential relies on the ability to create a reservoir and to accurately evaluate its evolving hydraulic properties to predict fluid flow and estimate ultimate therm...

Elsworth, D. and Marone, C. Pennsylvania State University

Nov 22, 2022
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Final Report: Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin

This is a final report summarizing a two-year (2014-16) DOE funded Geothermal Play Fairway Analysis of the Low-Temperature resources of the Appalachian Basin of New York, Pennsylvania and West Virginia. Collaborators included Cornell University, Southern Methodist University, and ...

E. Jordan, T. Cornell University

Nov 18, 2015
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Newberry EGS Demonstration: Well 55-29 Stimulation Data

The Newberry Volcano EGS Demonstration in central Oregon, a 3 year project started in 2010, tests recent technological advances designed to reduce the cost of power generated by EGS in a hot, dry well (NWG 55-29) drilled in 2008. First, the stimulation pumps used were designed to ...

T., T. AltaRock Energy Inc

Dec 08, 2012
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