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Title: Silica Precipitation and Lithium Sorption

This file contains silica precipitation and lithium sorption data from the project. The silica removal data is corrected from the previous submission. The previous submission did not take into account the limit of detection of the ICP-MS procedure.
Authors:
Publication Date:
Report Number(s):
531
DOE Contract Number:
EE0006746
Product Type:
Dataset
Research Org(s):
DOE Geothermal Data Repository; Southern Research
Collaborations:
Southern Research
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
Subject:
15 Geothermal Energy; geothermal; lithium; silica; precipitation
OSTI Identifier:
1234402
  1. The Geothermal Data Repository (GDR) is the submission point for all data collected from researchers funded by the U.S. Department of Energy's Geothermal Technologies Office (DOE GTO). The DOE GTO is providing access to its geothermal project information through the GDR. The GDR is powered by OpenEI, an energy information portal sponsored by the U.S. Department of Energy and developed by the National Renewable Energy Laboratory (NREL).
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  1. This is a continuation of the REE sorption study for shaker bath tests on 2g media #1 in 150mL brine #1 with different starting pH's at 70C. In a previous submission we reported data for shaker bath tests for brine #1 with starting pH's ofmore » 3.5, 4.5 and 5.5. In this submission we these pH's compared to starting brine #1 pH's of 6, and 7. « less
  2. Lithium sorption information from experiments. Data includes the effects of pH, temperature and brine chemistry on the sorption of Lithium from a simulated geothermal brine. The sorbent used in the experiments is "hydrothermally produced, Spinel-LiMn2O4". The sorbent was produced by Carus Corporation.
  3. *This submission provides corrections to GDR Submissions 844 and 845* Poroelastic Tomography (PoroTomo) by Adjoint Inverse Modeling of Data from Hydrology. The 3 *csv files containing pressure data are the corrected versions of the pressure dataset found in Submission 844. The dataset has been correctedmore » in the sense that the atmospheric pressure has been subtracted from the total pressure measured in the well. Also, the transducers used at wells 56A-1 and SP-2 are sensitive to surface temperature fluctuations. These temperature effects have been removed from the corrected datasets. The 4th *csv file contains corrected version of the pumping data found in Submission 845. The data has been corrected in the sense that the data from several wells that were used during the PoroTomo deployment pumping tests that were not included in the original dataset has been added. In addition, several other minor changes have been made to the pumping records due to flow rate instrument calibration issues that were discovered. « less
  4. These brine samples are collected from the Soda Geyser (a thermal feature, temperature ~30 C) in Soda Springs, Idaho. These samples also represent the overthrust brines typical of oil and gas plays in western Wyoming. Samples were collected from the source and along the flowmore » channel at different distances from the source. By collecting and analyzing these samples we are able to increase the density and quality of data from the western Wyoming oil and gas plays. Furthermore, the sampling approach also helped determine the systematic variation in REE concentration with the sampling distance from the source. Several geochemical processes are at work along the flow channels, such as degassing, precipitation, sorption, etc. « less
  5. In September 2013, an experiment using Distributed Acoustic Sensing (DAS) was conducted at Garner Valley, a test site of the University of California Santa Barbara (Lancelle et al., 2014). This submission includes all DAS data recorded during the experiment. The sampling rate for all filesmore » is 1000 samples per second. Any files with the same filename but ending in _01, _02, etc. represent sequential files from the same test. Locations of the sources are plotted on the basemap in GDR submission 481, titled: "PoroTomo Subtask 3.2 Sample data from a Distributed Acoustic Sensing experiment at Garner Valley, California (PoroTomo Subtask 3.2)." Lancelle, C., N. Lord, H. Wang, D. Fratta, R. Nigbor, A. Chalari, R. Karaulanov, J. Baldwin, and E. Castongia (2014), Directivity and Sensitivity of Fiber-Optic Cable Measuring Ground Motion using a Distributed Acoustic Sensing Array (abstract # NS31C-3935), AGU Fall Meeting. 
https://agu.confex.com/agu/fm1/meetingapp.cgi#Paper/19828 The e-poster is available at: https://agu.confex.com/data/handout/agu/fm14/Paper_19828_handout_696_0.pdf « less