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Modeling Responses of Naturally Fractured Geothermal Reservoir to Low-Pressure Stimulation

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...

Fu, P. and Carrigan, C. Lawrence Livermore National Laboratory

Jan 01, 2012
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Using Fully Coupled Hydro-Geomechanical Numerical Test Bed to Study Reservoir Stimulation with Low Hydraulic Pressure

This paper documents our effort to use a fully coupled hydro-geomechanical numerical test bed to study using low hydraulic pressure to stimulate geothermal reservoirs with existing fracture network. In this low pressure stimulation strategy, fluid pressure is lower than the minimu...

Fu, P. et al Lawrence Livermore National Laboratory

Jan 31, 2012
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Geothermal Electricity Technology Evaluation Model (GETEM) Individual Case Files and Summary Spreadsheet (GETEM version Spring 2013)

This group of files includes 10 GETEM individual scenario files and 1 summary spreadsheet. Each spreadsheet contains final data (following the revisions made between summer of 2011 and spring of 2013).

Entingh, D. et al Idaho National Laboratory

Mar 07, 2013
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An HPC-Based Hydrothermal Finite Element Simulator for Modeling Underground Geothermal Behavior with Example Simulations on The Treasure Island and UC Berkeley Campus

This submission contains the source code of the Hydrothermal Finite Element Simulator used for the Treasure Island and UC Berkeley campus geothermal simulation. It contains a report that summarizes the development and validation of this Hydrothermal Finite Element Simulator, with ...

Chen, K. et al Lawrence Berkeley National Laboratory

Aug 01, 2021
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EGS Collab Experiment 2: Laser Scanned 4100 L Drift Map

The EGS Collab project is evaluating a site for Experiment 2 (hydraulic fracturing/shearing) at a depth of 1.25 km in the Sanford Underground Research Facility (SURF) on the 4100 Level. Two early test holes were drilled in an alcove (formerly known as Battery Charging Station) nea...

Neupane, G. et al Idaho National Laboratory

Dec 19, 2019
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GeoThermalCloud: Cloud Fusion of Big Data and Multi-Physics Models using Machine Learning for Discovery, Exploration and Development of Hidden Geothermal Resources

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...

Ahmmed, B. Stanford University

Apr 04, 2022
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