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Title: SW New Mexico BHT geothermal gradient calculations

This file contains a compilation of BHT data from oil wells in southwestern New Mexico. Surface temperature is calculated using the collar elevation. An estimate of geothermal gradient is calculated using the estimated surface temperature and the uncorrected BHT data.
Authors:
Publication Date:
Report Number(s):
554
DOE Contract Number:
GO00841
Product Type:
Dataset
Research Org(s):
DOE Geothermal Data Repository; New Mexico Bureau of Geology and Mineral Resources
Collaborations:
New Mexico Bureau of Geology and Mineral Resources
Sponsoring Org:
USDOE Office of Energy Efficiency and Renewable Energy (EERE), Geothermal Technologies Program (EE-2C)
Subject:
15 Geothermal Energy; geothermal; geothermal gradient; southwestern New Mexico; BHT; SW New Mexico
OSTI Identifier:
1261932
  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. x,y,z data of the 3D temperature model for the West Flank Coso FORGE site. Model grid spacing is 250m. The temperature model for the Coso geothermal field used over 100 geothermal production sized wells and intermediate-depth temperature holes. At the near surface of this model,more » two boundary temperatures were assumed: (1) areas with surface manifestations, including fumaroles along the northeast striking normal faults and northwest striking dextral faults with the hydrothermal field, a temperature of ~104ËšC was applied to datum at +1066 meters above sea level elevation, and (2) a near-surface temperature at about 10 meters depth, of 20ËšC was applied below the diurnal and annual conductive temperature perturbations. These assumptions were based on heat flow studies conducted at the CVF and for the Mojave Desert. On the edges of the hydrothermal system, a 73ËšC/km (4ËšF/100’) temperature gradient contour was established using conductive gradient data from shallow and intermediate-depth temperature holes. This contour was continued to all elevation datums between the 20ËšC surface and -1520 meters below mean sea level. Because the West Flank is outside of the geothermal field footprint, during Phase 1, the three wells inside the FORGE site were incorporated into the preexisting temperature model. To ensure a complete model was built based on all the available data sets, measured bottom-hole temperature gradients in certain wells were downward extrapolated to the next deepest elevation datum (or a maximum of about 25% of the well depth where conductive gradients are evident in the lower portions of the wells). After assuring that the margins of the geothermal field were going to be adequately modelled, the data was contoured using the Kriging method algorithm. Although the extrapolated temperatures and boundary conditions are not rigorous, the calculated temperatures are anticipated to be within ~6ËšC (20ËšF), or one contour interval, of the observed data within the Coso geothermal field. Based on a lack of temperature data west of 74-2TCH, the edges of this model still seem to have an effect on West Flank modeled temperatures. « less
  2. This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (project DE-EE0006726). The submission includes data pertinent to themore » methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau ‘Places’ within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped ‘risk’ of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. « less
  3. This submission of Utilization Analysis data to the Geothermal Data Repository (GDR) node of the National Geothermal Data System (NGDS) is in support of Phase 1 Low Temperature Geothermal Play Fairway Analysis for the Appalachian Basin (project DE-EE0006726). The submission includes data pertinent to themore » methods and results of an analysis of the Surface Levelized Cost of Heat (SLCOH) for US Census Bureau Places within the study area. This was calculated using a modification of a program called GEOPHIRES, available at http://koenraadbeckers.net/geophires/index.php. The MATLAB modules used in conjunction with GEOPHIRES, the MATLAB data input file, the GEOPHIRES output data file, and an explanation of the software components have been provided. Results of the SLCOH analysis appear on 4 .png image files as mapped risk of heat utilization. For each of the 4 image (.png) files, there is an accompanying georeferenced TIF (.tif) file by the same name. In addition to calculating SLCOH, this Task 4 also identified many sites that may be prospects for use of a geothermal district heating system, based on their size and industry, rather than on the SLCOH. An industry sorted listing of the sites (.xlsx) and a map of these sites plotted as a layer onto different iterations of maps combining the three geological risk factors (Thermal Quality, Natural Reservoir Quality, and Risk of Seismicity) has been provided. In addition to the 6 image (.png) files of the maps in this series, a shape (.shp) file and 7 associated files are included as well. Finally, supporting files (.pdf) describing the utilization analysis methodology and summarizing the anticipated permitting for a deep district heating system are supplied. UPDATE: Newer version of the Utilization Analysis has been added here: https://gdr.openei.org/submissions/878 « less
  4. Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) providesmore » an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = τ / σn (Morris et al., 1996). Dilation tendency is defined by the stress acting normal to a given surface: Td = (σ1-σn) / (σ1-σ3) (Ferrill et al., 1999). Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. 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 focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. 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 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) as well as local stress information if applicable. For faults within these focus systems we applied either 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) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. 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, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012). Slip and dilation tendency for the San Emidio geothermal field was calculated based on the faults mapped Tuscarora area (Rhodes, 2011). The San Emidio area lies in the Basin and Range Province, as such we applied a normal faulting stress regime to the San Emidio area faults, with a minimum horizontal stress direction oriented 115, based on inspection of local and regional stress determinations, as explained above. This is consistent with the shmin determined through inversion of fault data by Rhodes (2011). Under these stress conditions north-northeast striking, steeply dipping fault segments have the highest dilation tendency, while north-northeast striking 60° dipping fault segments have the highest tendency to slip. Interesting, the San Emidio geothermal field lies in an area of primarily north striking faults, which... « less
  5. Critically stressed fault segments have a relatively high likelihood of acting as fluid flow conduits (Sibson, 1994). As such, the tendency of a fault segment to slip (slip tendency; Ts; Morris et al., 1996) or to dilate (dilation tendency; Td; Ferrill et al., 1999) providesmore » an indication of which faults or fault segments within a geothermal system are critically stressed and therefore likely to transmit geothermal fluids. The slip tendency of a surface is defined by the ratio of shear stress to normal stress on that surface: Ts = τ / σn (Morris et al., 1996). Dilation tendency is defined by the stress acting normal to a given surface: Td = (σ1-σn) / (σ1-σ3) (Ferrill et al., 1999). Slip and dilation were calculated using 3DStress (Southwest Research Institute). Slip and dilation tendency are both unitless ratios of the resolved stresses applied to the fault plane by ambient stress conditions. 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 focus study areas at, McGinness Hills, Neal Hot Springs, Patua, Salt Wells, San Emidio, and Tuscarora on fault traces. As dip is not well constrained or unknown for many faults mapped in within these we made these calculations using the dip for each fault that would yield the maximum slip tendency or dilation tendency. As such, these results should be viewed as maximum tendency of each fault to slip or dilate. 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 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) as well as local stress information if applicable. For faults within these focus systems we applied either 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) or strike-slip faulting stress regime where the maximum horizontal stress (shmax) is larger than the vertical stress (sv) which is larger than the minimum horizontal stress (shmax >sv>shmin) depending on the general tectonic province of the system. 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, which are consistent with complete and partial stress field determinations from Desert Peak, Coso, the Fallon area and Dixie valley (Hickman et al., 2000; Hickman et al., 1998 Robertson-Tait et al., 2004; Hickman and Davatzes, 2011; Davatzes and Hickman, 2006; Blake and Davatzes 2011; Blake and Davatzes, 2012). Slip and dilation tendency for the Salt Wells geothermal field was calculated based on the faults mapped in the Bunejug Mountains quadrangle (Hinz et al., 2011). The Salt Wells area lies in the Basin and Range Province (N. Hinz personal comm.) As such we applied a normal faulting stress regime to the Salt Wells area faults, with a minimum horizontal stress direction oriented 105, based on inspection of local and regional stress determinations. Under these stress conditions north-northeast striking, steeply dipping fault segments have the highest dilation tendency, while north-northeast striking 60° dipping fault segments have the highest tendency to slip. Several such faults intersect in high density in the core of the accommodation zone in the Bunejug Mountains and local to the Salt Wells geothermal . « less