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Appalachian Basin Play Fairway Analysis Gravity, Magnetics, and Earthquake Data

This archived dataset contains magnetic and gravity imaging data for the Appalachian Basin, compiled using Poisson Wavelet Multiscale Edge Detection, referred to as 'worm' for brevity, and stored in a PostGIS database, along with shapefiles and CSVs of relevant data. The archive ...

Horowitz, F. Cornell University

Jul 20, 2016
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Utah FORGE: 2023 Induced Seismicity Mitigation Plan

This is the updated Utah FORGE Phase 3B induced seismicity mitigation plan (ISMP) covering the general Utah FORGE area. This new version incorporates newly collected seismic data, including data collected during the 2022 stimulation and a probabilistic seismic hazard assessment (...

Pankow, K. et al University of Utah Seismograph Stations

Aug 09, 2023
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Utah FORGE: Induced Seismicity Mitigation Plan

This is the current induced seismicity mitigation plan (ISMP) for the Utah FORGE project. Information that was collected during Phases 1 and 2 of the Utah FORGE project has been incorporated, as have literature searches and risk assessments. The purpose of this report is to identi...

Utah, U. et al Energy and Geoscience Institute at the University of Utah

Dec 30, 2020
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Curated

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
12 Resources
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Utah FORGE: Well 58-32 Stimulation Conference Paper and Data

The U.S. Department of Energy's (U.S. DOE) Frontier Observatory for Research in Geothermal Energy (FORGE) is a field laboratory that provides a unique opportunity to develop and test new technologies for characterizing, creating and sustaining Enhanced Geothermal Systems (EGS) in ...

Best, S. Energy and Geoscience Institute at the University of Utah

Apr 24, 2019
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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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