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Title: Tularosa Basin Play Fairway Analysis: Partial Basin and Range Heat and Zones of Critical Stress Maps

Interpolated maps of heat flow, temperature gradient, and quartz geothermometers are included as TIF files. Zones of critical stress map is also included as a TIF file. The zones are given a 5km diameter buffer. The study area is only a part of the Basin and Range, but it does includes the Tularosa Basin.
Authors:
Publication Date:
Report Number(s):
634
DOE Contract Number:
EE0006730
Product Type:
Dataset
Research Org(s):
DOE Geothermal Data Repository; University of Utah
Collaborations:
University of Utah
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
Subject:
15 Geothermal Energy; geothermal; fort bliss; tularosa basin; tularosa; new mexico; critical stress; quartz geothermometer; heat flow; heatflow; temperature gradient; maps; map; Basin and Range; Great Basin; Utah; Nevada; interpolation; extrapolation; basin and range; Quartz; geothermometer; temperature; gradient; zones; fault; permeability
OSTI Identifier:
1261945
  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. The Engineered Geothermal System (EGS) Exploration Methodology Project is developing an exploration approach for EGS through the integration of geoscientific data. The Project chose the Dixie Valley Geothermal System in Nevada as a field laboratory site for methodology calibration purposes because, in the public domain,more » it is a highly characterized geothermal system in the Basin and Range with a considerable amount of geoscience and most importantly, well data. The overall project area is 2500km2 with the Calibration Area (Dixie Valley Geothermal Wellfield) being about 170km2. The project was subdivided into five tasks (1) collect and assess the existing public domain geoscience data; (2) design and populate a GIS database; (3) develop a baseline (existing data) geothermal conceptual model, evaluate geostatistical relationships, and generate baseline, coupled EGS favorability/trust maps from +1km above sea level (asl) to -4km asl for the Calibration Area at 0.5km intervals to identify EGS drilling targets at a scale of 5km x 5km; (4) collect new geophysical and geochemical data, and (5) repeat Task 3 for the enhanced (baseline + new ) data. Favorability maps were based on the integrated assessment of the three critical EGS exploration parameters of interest: rock type, temperature and stress. A complimentary trust map was generated to compliment the favorability maps to graphically illustrate the cumulative confidence in the data used in the favorability mapping. The Final Scientific Report (FSR) is submitted in two parts with Part I describing the results of project Tasks 1 through 3 and Part II covering the results of project Tasks 4 through 5 plus answering nine questions posed in the proposal for the overall project. FSR Part I presents (1) an assessment of the readily available public domain data and some proprietary data provided by Terra-Gen Power, LLC, (2) a re-interpretation of these data as required, (3) an exploratory geostatistical data analysis, (4) the baseline geothermal conceptual model, and (5) the EGS favorability/trust mapping. The conceptual model presented applies to both the hydrothermal system and EGS in the Dixie Valley region. FSR Part II presents (1) 278 new gravity stations; (2) enhanced gravity-magnetic modeling; (3) 42 new ambient seismic noise survey stations; (4) an integration of the new seismic noise data with a regional seismic network; (5) a new methodology and approach to interpret this data; (5) a novel method to predict rock type and temperature based on the newly interpreted data; (6) 70 new magnetotelluric (MT) stations; (7) an integrated interpretation of the enhanced MT data set; (8) the results of a 308 station soil CO2 gas survey; (9) new conductive thermal modeling in the project area; (10) new convective modeling in the Calibration Area; (11) pseudo-convective modeling in the Calibration Area; (12) enhanced data implications and qualitative geoscience correlations at three scales (a) Regional, (b) Project, and (c) Calibration Area; (13) quantitative geostatistical exploratory data analysis; and (14) responses to nine questions posed in the proposal for this investigation. Enhanced favorability/trust maps were not generated because there was not a sufficient amount of new, fully-vetted (see below) rock type, temperature, and stress data. The enhanced seismic data did generate a new method to infer rock type and temperature. However, in the opinion of the Principal Investigator for this project, this new methodology needs to be tested and evaluated at other sites in the Basin and Range before it is used to generate the referenced maps. As in the baseline conceptual model, the enhanced findings can be applied to both the hydrothermal system and EGS in the Dixie Valley region. « less
  2. Over the course of the entire project, field visits were made to 117 geothermal systems in the Great Basin region. Major field excursions, incorporating visits to large groups of systems, were conducted in western Nevada, central Nevada, northwestern Nevada, northeastern Nevada, east‐central Nevada, eastern California,more » southern Oregon, and western Utah. For example, field excursions to the following areas included visits of multiple geothermal systems: - Northwestern Nevada: Baltazor Hot Spring, Blue Mountain, Bog Hot Spring, Dyke Hot Springs, Howard Hot Spring, MacFarlane Hot Spring, McGee Mountain, and Pinto Hot Springs in northwest Nevada. - North‐central to northeastern Nevada: Beowawe, Crescent Valley (Hot Springs Point), Dann Ranch (Hand‐me‐Down Hot Springs), Golconda, and Pumpernickel Valley (Tipton Hot Springs) in north‐central to northeast Nevada. - Eastern Nevada: Ash Springs, Chimney Hot Spring, Duckwater, Hiko Hot Spring, Hot Creek Butte, Iverson Spring, Moon River Hot Spring, Moorman Spring, Railroad Valley, and Williams Hot Spring in eastern Nevada. - Southwestern Nevada‐eastern California: Walley’s Hot Spring, Antelope Valley, Fales Hot Springs, Buckeye Hot Springs, Travertine Hot Springs, Teels Marsh, Rhodes Marsh, Columbus Marsh, Alum‐Silver Peak, Fish Lake Valley, Gabbs Valley, Wild Rose, Rawhide‐ Wedell Hot Springs, Alkali Hot Springs, and Baileys/Hicks/Burrell Hot Springs. - Southern Oregon: Alvord Hot Spring, Antelope Hot Spring‐Hart Mountain, Borax Lake, Crump Geyser, and Mickey Hot Spring in southern Oregon. - Western Utah: Newcastle, Veyo Hot Spring, Dixie Hot Spring, Thermo, Roosevelt, Cove Fort, Red Hill Hot Spring, Joseph Hot Spring, Hatton Hot Spring, and Abraham‐Baker Hot Springs. Structural controls of 426 geothermal systems were analyzed with literature research, air photos, google‐Earth imagery, and/or field reviews (Figures 1 and 2). Of the systems analyzed, we were able to determine the structural settings of more than 240 sites. However, we found that many “systems” consisted of little more than a warm or hot well in the central part of a basin. Such “systems” were difficult to evaluate in terms of structural setting in areas lacking in geophysical data. Developed database for structural catalogue in a master spreadsheet. Data components include structural setting, primary fault orientation, presence or absence of Quaternary faulting, reservoir lithology, geothermometry, presence or absence of recent magmatism, and distinguishing blind systems from those that have surface expressions. Reviewed site locations for all 426 geothermal systems– Confirmed and/or relocated spring and geothermal sites based on imagery, maps, and other information for master database. Many systems were mislocated in the original database. In addition, some systems that included several separate springs spread over large areas were divided into two or more distinct systems. Further, all hot wells were assigned names based on their location to facilitate subsequent analyses. We catalogued systems into the following eight major groups, based on the dominant pattern of faulting (Figure 1): - Major normal fault segments (i.e., near displacement maxima). - Fault bends. - Fault terminations or tips. - Step‐overs or relay ramps in normal faults. - Fault intersections. - Accommodation zones (i.e., belts of intermeshing oppositely dipping normal faults), - Displacement transfer zones whereby strike‐slip faults terminate in arrays of normal faults. - Transtensional pull‐aparts. These settings form a hierarchal pattern with respect to fault complexity. - Major normal faults and fault bends are the simplest. - Fault terminations are typically more complex than mid‐segments, as faults commonly break up into multiple strands or horsetail near their ends. - A fault intersection is generally more complex, as it generally contains both multiple fault strands and can include discrete di... « less
  3. A DEM of the Tularosa Basin was divided into twelve zones, each of which a ZR ratio was calculated for. This submission has a TIFF image of the zoning designations, along with a table with respective ZR ratio calculations in the metadata.
  4. Slip and dilation tendency on the Great Basin fault surfaces (from the USGS Quaternary Fault Database) were calculated using 3DStress (software produced by Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by themore » measured ambient stress field. - Values range from a maximum of 1 (a fault plane ideally oriented to slip or dilate under ambient stress conditions) to zero (a fault plane with no potential to slip or dilate). - Slip and dilation tendency values were calculated for each fault in the Great Basin. As dip is unknown for many faults in the USGS Quaternary Fault Database, we made these calculations using the dip for each fault that would yield the maximum slip or dilation tendency. As such, these results should be viewed as maximum slip and dilation tendency. - The resulting along‐fault and fault‐to‐fault variation in slip or dilation potential is a proxy for along fault and fault‐to‐fault variation in fluid flow conduit potential. Stress Magnitudes and directions were calculated across the entire Great Basin. Stress field variation within each focus area was approximated based on regional published data and the world stress database (Hickman et al., 2000; Hickman et al., 1998 Robertson‐Tait et al., 2004; Hickman and Davatzes, 2010; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012; Moeck et al., 2010; Moos and Ronne, 2010 and Reinecker et al., 2005). The minimum horizontal stress direction (Shmin) was contoured, and spatial bins with common Shmin directions were calculated. Based on this technique, we subdivided the Great Basin into nine regions (Shmin <070, 070140). Slip and dilation tendency were calculated using 3DStress for the faults within each region using the mean Shmin for the region. Shmin variation throughout Great Basin are shown on Figure 3. For faults within the Great Basin proper, we applied a normal faulting stress regime, where the vertical stress (sv) is larger than the maximum horizontal stress (shmax), which is larger than the minimum horizontal stress (sv>shmax>shmin). Based on visual inspection of the limited stress magnitude data in the Great Basin, we used magnitudes such that shmin/shmax = .527 and shmin/sv= .46. These values are consistent with stress magnitude data at both Dixie Valley (Hickman et al., 2000) and Yucca Mountain (Stock et al., 1985). For faults within the Walker Lane/Eastern California Shear Zone, we applied a strike‐slip faulting stress, where shmax > sv > shmin. Upon visual inspection of limited stress magnitude data from the Walker Lane and Eastern California Shear zone, we chose values such that SHmin/SHmax = .46 and Shmin/Sv= .527 representative of the region. Results: The results of our slip and dilation tendency analysis are shown in Figures 4 (dilation tendency), 5 (slip tendency) and 6 (slip tendency + dilation tendency). Shmin varies from northwest to east‐west trending throughout much of the Great Basin. As such, north‐ to northeast‐striking faults have the highest tendency to slip and to dilate, depending on the local trend of shmin. These results provide a first order filter on faults and fault systems in the Great Basin, affording focusing of local‐scale exploration efforts for blind or hidden geothermal resources. « less
  5. This dataset contains a variety of data about the Fort Bliss geothermal area, part of the southern portion of the Tularosa Basin, New Mexico. The dataset contains schematic models for the McGregor Geothermal System, a shallow temperature survey of the Fort Bliss geothermal area. Themore » dataset also contains Century OH logs, a full temperature profile, and complete logs from well RMI 56-5, including resistivity and porosity data, drill logs with drill rate, depth, lithology, mineralogy, fractures, temperature, pit total, gases, and descriptions among other measurements as well as CDL, CNL, DIL, GR Caliper and Temperature files. A shallow (2 meter depth) temperature survey of the Fort Bliss geothermal area with 63 data points is also included. Two cross sections through the Fort Bliss area, also included, show well position and depth. The surface map included shows faults and well spatial distribution. Inferred and observed fault distributions from gravity surveys around the Fort Bliss geothermal area. « less