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Gravity Survey on the Glass Buttes Geothermal Exploration Project Lake County, Oregon

This report covers data acquisition, instrumentation and processing of a gravity survey performed on the Glass Buttes Geothermal Exploration Project, located in Lake County, Oregon for ORMAT Technologies Inc. The survey was conducted during 21 June 2010 to 26 June 2010. The surve...
Akerley, J. Ormat Nevada Inc
Oct 12, 2011
2 Resources
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Acquisition and Processing of a Detailed Aeromagnetic Survey Glass Buttes, Oregon

Using an ultra-light aircraft, a high-resolution aeromagnetic survey was carried out over Ormat Nevada's Glass Buttes project area in Oregon. Survey operations were completed on May 25, 2010. Average terrain clearance was 223 meters from the sensor. A total of 1,352 line-miles o...
Akerley, J. Ormat Nevada Inc
May 27, 2010
6 Resources
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Glass Buttes Exploration and Drilling: 2010 Geothermal Technologies Program Peer Review Presentation

Glass Buttes Exploration and Drilling: 2010 Geothermal Technologies Program Peer Review Presentation, Walsh, et al, Ormat
Walsh, P. Ormat Nevada Inc
Jan 01, 2010
1 Resources
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2011 Glass Buttes Exploration and Drilling

2011 Geothermal Technologies Program Peer Review Presentation summarizing relevance, proposed approach, and logistics of the Glass Buttes Exploration and Drilling.
Walsh, P. Ormat Nevada Inc
Jan 01, 2011
1 Resources
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MT Survey on the Glass Buttes Geothermal Exploration Project in Lake County, Oregon

Zonge Geosciences, Inc. performed a magnetotelluric (MT) survey for the Glass Buttes Project at the request of Ormat Technologies Inc. during the period of 7 October 2010 to 8 November 2010. This report provides the deep electromagnetic data and methods that were used to assist O...
Akerley, J. Ormat Nevada Inc
Nov 08, 2010
1 Resources
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The Use of 3D Geologic Modeling to Improve Well Targeting in Glass Buttes, Oregon

The Glass Buttes Project includes combining a suite of high-resolution geophysical and geochemical techniques to reduce exploration risk by characterizing hydrothermal alteration, fault geometries and relationships. This is aided through geologic observation, modern remote sensing...
Walsh, P. Ormat Nevada Inc
Oct 09, 2011
1 Resources
0 Stars
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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
3 Resources
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