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High-Temperature Inorganic Self-Healing Inorganic Cement Composites

The data files below summarize the results from various experiments testing properties of high-temperature self-healing inorganic cement composites. These properties include cement-carbon steel bond strength, Young's modulus recovery, matrix recovery strength, and compressive stre...

Pyatina, T. and Sugama, T. Brookhaven National Laboratory

Sep 13, 2017
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Chemical, Calcium Phosphate Cements for Geothermal Wells Corrosion Protection, Bond Strength and Matrix Self-Healing

The data set shows performance of economical calcium phosphate cement (Fondu) blended with fly ash, class F (FAF) in carbon steel corrosion protection tests (corrosion rate, corrosion current and potential), bond and matrix strength, as well as matrix strength recovery after impos...

Sugama, T. Brookhaven National Laboratory

Sep 26, 2017
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Chlorite Dissolution Kinetics at Variable pH and Temperatures up to 275C

FY13 annual report describing the calculations and results associated with the data and dissolution rate contained in "Chlorite Kinetic Dissolution Data and Rate" (linked below).

Carroll, S. and Smith, M. Lawrence Livermore National Laboratory

Oct 01, 2013
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Resource Analysis for Deep Direct-Use Feasibility Study in East Texas

The National Renewable Energy Laboratory, Southern Methodist University Geothermal Laboratory, Eastman Chemical, Turbine Air Systems, and the Electric Power Research Institute are evaluating the feasibility of using geothermal heat to improve the efficiency of natural gas power pl...

Richards, M. et al Southern Methodist University

Jun 28, 2018
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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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Newberry EGS Demonstration: Well 55-29 Stimulation Data 2014

The Newberry Volcano EGS Demonstration in central Oregon, a 5 year project begun 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 ru...

Cladhouhos, T. et al AltaRock Energy Inc

Sep 03, 2015
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Subsurface Characterization and Machine Learning Predictions at Brady Hot Springs Results

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...

Beckers, K. et al National Renewable Energy Laboratory

Oct 20, 2021
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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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