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TOC | Abstract | Introduction | Database | Applications | Acknowledgements | References | Appendices

Locations and Samples
Chemical Analyses
Petrographic Analyses
Detailed Optical Mineralogy
Microprobe Analyses
XRD
Geologic Intervals from Drillholes
Physical Properties and Geophysical Logs


II. THE GEOLOGICAL DATA

The geological data are organized within a set of related database tables. These tables are described in this section; beginning with tables defining attributes for the measurement location, followed by those containing the geological measurements. Database table names are identified by italics within the text. For example, table_desc is a table that contains descriptions of individual tables and their data fields. The relational structure and organization of these tables are described in the next section.

Tables within each of the following subsections identify the database tables that support the identified data items. These tables describe the contents and associated tables (foreign keys) for each of the named database tables. The term "foreign key" has its origin in relational database literature and is a table that provides a list of acceptable values for a given data field within a database table.

Locations and Samples

Geologic measurements and supporting information are provided for depth (elevation) intervals of more than 750 drill holes, and for points at approximately 4,300 surface and subsurface locations within the database tables listed in Table 1. Geological interval measurements are descriptive (text data), whereas geophysical interval measurements are quantitative (numeric data). Separate tables for the different data types identify the type of laboratory measurement as well as its value. More than 8,600 samples (point data) were collected at the 4,300 locations, and multiple splits (e.g. X-ray diffraction, polished thin section, wet chemistry) often provide a diversity of measurements for individual samples. Most of the "point" measurement data are reported at the split level, with the associated table structures reflecting the generic class of laboratory data (e.g. chemical, petrologic, mineralogic). The quantitative measurements are provided with the appropriate units of measure and individual uncertainty values, if available. Most samples used for these splits have been curated and are available for additional work. The different types of laboratory measurements are described in the following sections.

Primary laboratory measurements reported at the split level are contained in database tables with names that begin with a code reflecting the generic class of data, and end in _measure, e.g., ca_measure, which contains data for chemical analyses and pa_measure, which contains data for petrographic analyses. Multivalued descriptive information that constitutes primary measurements is most efficiently stored in separate tables, such as sample_alt (Table 1). Multivalued, descriptive information for each measurement is stored within separate database tables whose names begin with the same generic class code, e.g., sample_worker. Such supporting information is often termed "metadata". These different types of tables are described in the geological database section.

Table name

Description

Foreign key tables

     

location

Describes sample locations

loc_qa_ list, quad_ list

location_ref

Sources of information for location

topic_list, ref_list

     

sample

Sample characteristics

strat_list, sam_type_list, lit_list

sample_desc

Sample descriptions

worker_list, sam_desc_type_list

sample_ref

Citations for sample characteristics

topic_list, ref_list

sample_worker

Sample workers

topic_list, worker_list

sample_avail

Sample availability

avail_list

sample_color

Sample colors

comp_list, hue_list

sample_alt

Alteration of sample

alt_list

sample_malt

Minor alteration of sample

alt_list

 

 

 

 

 

 

 

 

 

 

 

 

 


Table 1. Database tables for locations and samples. More detailed descriptions of each table are provided in database table table_desc.

 

Age Dates and Stratigraphic Units

Age measurements, determined primarily by the Ar/Ar and K/Ar dating methods, are available for 386 samples within database tables listed in Table 2. These measurements provide model ages for Tertiary units of the SWNVF, which constitute the vast majority of the 365 stratigraphic units or subunits defined within the SWNVF. Figure 3 shows a portion of the stratigraphic column that is based on these age assignments. The assigned stratigraphic codes define groups of petrographically, chemically, and temporally related units (Warren et al., 1989a). These groups are termed "volcanic assemblages".

Table name

Description

Foreign key tables

     

age_measure

Age date

split_type_list, comp_list

     

Strat

Stratigraphic units

strat_list

prev_strat_code_ref

References for previously used stratigraphic symbols

strat_list, ref_list

prev_strat_name_ref

Reference codes for previously used stratigraphic names

strat_list, ref_list


Table 2. Database tables for age dates and stratigraphic units.

 

Figure 3. Stratigraphic column for assemblages of the SWNVF emplaced between 10 to 15 Ma. Voluminous caldera-related silicic volcanism occurred between 16.3 to 11.4 Ma from the centers shown in Figure 1 and from additional centers of unknown location buried by younger volcanism. Stratigraphic codes used in the column (e.g. QT,Tf) identify stratigraphic units as defined in database table strat. Individual units are shown for the Wahmonie Formation (Tw), using the expanded scale of model ages shown to the right.

 

Chemical Analyses

Chemical analyses are provided for nearly 3,000 samples within the database tables listed in Table 3. More than 80,000 chemical concentrations, representing 70 of the 85 natural occurring elements, have been obtained by a variety of analytical methods such as X-ray fluorescence (XRF), neutron activation analysis (NAA), and a variety of wet chemical methods such as atomic absorption, flame emission spectroscopy, and inductively-coupled plasma emission spectroscopy. Each sample split normally reflects a general analytical type, although sample preparation, computational method, and analytical "subtype" can vary for individual analytes. For example, a wet chemical split could include analyses by the subtypes atomic absorption, flame or inductively-coupled plasma emission spectroscopy, or gravimetric analysis. Multiple splits from a sample can provide multiple measurements for a single analyte. Database tables described in Table 3 provide supplemental information so that users can make informed decisions regarding which data are most appropriate for their use. For all elements, concentrations are reported as the oxide that generally predominates in the natural environment, for example, MgO and BaO. Note that a trace element such as Ba is typically reported as the element rather than the oxide within the geochemical literature. Concentrations can be converted to elemental form through use of a foreign key table of gravimetric factors. Many chemical data represent the average of repeat analyses (replicates) of a split by the same technique, occasionally performed on a different day and/or by another analyst. Because of this, sample preparation and analyst data are stored in separate replicate tables to allow the many-to-one relationship between such replicate data and the reported chemical measurements to be preserved.

Table name

Description

Foreign key tables

     

ca_split

Chemical analysis type

split_type_list, meas_type_list

ca_spl_rep

Replicate ID

 

ca_measure

Chemical data

oxide_list, error_meth_list, units_list, ca_subtype_list, ref_list

ca_compute_method

Computational method

ca_comp_meth_code

ca_rep_oxide

Replicate analyte

oxide_list

ca_rep_prep

Sample preparation

ca_prep_list

ca_rep_worker

Chemical analyst

worker_list


Table 3. Database tables for chemical analyses (ca).

 

Many of the previously unpublished chemical analyses in the database were generated within the Earth and Environmental Sciences (EES) XRF laboratory at LANL (Figure 4). All splits are prepared as fused disks by fusing the sample with a low-Z (lithium borate) flux, which dilutes the sample, minimizing matrix affects. The model used to calculate concentrations from measured X-ray intensities is non-linear, utilizes loss on ignition (LOI), and is based on more than 40 standards, with reference analytical values mostly from Govindaraju (1994). Use of LOI in computations is important because loss of volatiles during fusion changes the initially measured flux-to-sample ratio. This computational model provides realistic estimates of uncertainty in the accuracy of these XRF analyses.

 

Figure 4. The XRF instrument at LANL.   A) Panel for display of elements currently being analyzed and their count rates, B) Operation control panel, C) Control panel for sample changer, D) Automatic sample changer, E) Chart recorder for wavelength scans of X-ray intensities.

 

Petrographic Analyses

Nearly 90,000 quantitative mineral abundances have been obtained by optical petrography for nearly 4700 samples. These analyses are compiled within database tables listed in Table 4. Supplemental descriptive information provided for each analysis includes mineral alteration. Analyses of individual minerals, described in the next section, supplement and support many petrographic analyses. Measurements are available from four general types of petrographic methods, several representing new petrographic methods. The methods, described below, include grain mount analyses, "quick look" estimates, "standard" analyses by point count, and "detailed" analyses. Some samples have been analyzed by more than one method.

Table name

Description

Foreign key tables

     

pa_split

General petrographic information

split_type_list, pa_meth_list, light_type_list, comp_list, sep_meth_list, qa_list

pa_misc

Miscellaneous petrographic information

pa_meas_type_list, qa_list

pa_count

Points counted for petrographic analysis

pa_meth_list, qa_list

pa_measure

Petrographic analyses

comp_list, units_list, comp_alt_list, pa_meth_list, ref_list, qa_list

pa_worker

Petrographic analyst

comp_list, worker_list, qa_list

     

xx_pa_split

Superceded or erroneous general petrographic information

split_type_list, pa_meth_list, light_type_list, comp_list, sep_meth_list, qa_list

xx_pa_misc

Superceded or erroneous miscellaneous petrographic information

pa_meas_type_list, qa_list

xx_pa_count

Superceded or erroneous points counted for petrographic analysis

pa_meth_list, qa_list

xx_pa_measure

Superceded or erroneous petrographic analyses

comp_list, units_list, comp_alt_list, pa_meth_list, ref_list, qa_list

xx_pa_worker

petrographic analyst for superceded or erroneous analysis

comp_list, worker_list, qa_list


Table 4. Database tables for petrographic analyses (pa). Tables with names that begin xx_ should not be employed for usual applications of petrographic data.

Our technique for grain mount analysis provides an accurate measure for the relative proportions of felsic phenocrysts (quartz and feldspars), crude measures for abundances of other constituents, and a microscopic view of sample alteration. The method provides inexpensive, quantitative petrographic information and avoids delays associated with thin section preparation. With a petrographic microscope stationed at a drill rig, petrographic data can be immediately available for critical drilling decisions. The method generates quantitative data comparable in accuracy to analysis of a thin section (Table 5). Our technique provides quantitative analysis only for felsic minerals and does not provide a permanent sample, as does standard thin section analysis. The grain mount analysis proceeds by crushing a few grams of sample in a mortar to silt size, pinching a few milligrams of this powder between the thumb and forefinger, and sprinkling the powder on a standard thin section slide. After adding a drop or two of immersion oil and covering the oil with a cover slip, the sample is ready for grain mount analysis.

"Quick look" estimates provide crude but useful petrographic data when time or expense is a primary consideration. The accuracy of individual quick look estimates reflect the effort for each such analysis, which varies widely. Each quick look analysis ranges from a five minute inspection of the thin section to estimation of abundances from detailed photodocumentation of the largest mineral grains, as described below. Comparing superceded quick look analyses with detailed analyses of the same thin section demonstrates that the quick look estimates are generally only slightly less accurate for the relative proportion of felsic phenocrysts. Quick look estimates are generally accurate within a factor of two for the total abundance of felsic phenocrysts, and within a factor of three for abundances of mafic phenocrysts (biotite, hornblende, pyroxene, olivine). Although these uncertainties are indeed large, the differences in mineral abundances among stratigraphic units are often several times larger. These data can therefore be very useful for certain applications.

Most of the "standard" petrographic analyses of this database are based on very accurate and precise identification (counts) of minerals using a very large number of grid points for each thin section, and so may be standard in their methodology but with much higher accuracy and precision than normally reported for this type of analysis. Points were generally counted at 0.1 mm intervals within traverse lines separated by 0.5 or 1.0 mm, covering as much of the thin section as a standard point counting stage would allow, generally 90-100% of the slide. With this approach, precision is adequate for minor constituents, including mafic minerals and Fe-Ti oxide minerals (magnetite and ilmenite).

Felsic phenocryst

Petrographic method

Mafic-poor Calico Hills Formation (Thp)

 

Rhyolite of Echo Peak (Tpe)

   

value

2SEM

n

 

value

2SEM

n

Total felsic phenocrysts (volume %)

Point count

2.3

0.2

176

 

8.9

1.1

27

Grain mount

2.4

0.4

71

 

6.5

1.3

4

Quick look

3.4

0.4

71

 

12.6

1.1

30

                 

Quartz

(percent of felsic phenocrysts)

Point count

41

2

148

 

0.4

0.4

27

Grain mount

42

4

54

 

2.7

1.6

19

Quick look

40

2

67

 

0.9

0.5

30

                 

K-spar

(percent of felsic phenocrysts)

Point count

35

2

148

 

65

4

27

Grain mount

41

3

54

 

64

4

19

Quick look

41

3

67

 

58

3

30

                 

Plagioclase

(percent of felsic phenocrysts)

Point count

25

2

148

 

35

4

27

Grain mount

17

2

54

 

33

4

19

Quick look

20

3

67

 

41

3

30


Table 5. Comparison of mean values obtained by different petrographic methods. Statistical parameters are twice the standard error of the mean (2SEM) and number of analyses (n). Includes only analyses entered into database by 23 October 1998. Values from point count are the most accurate. Values from grain mount provide analyses that compare well with those from point count. A typically slightly higher content of quartz from grain mount analysis is attributed to a contribution of quartz from phenocrysts and coarse granophyric groundmass within lithics. Values for total felsic phenocrysts from quick look are typically erroneously high compared to those from point count. Stratigraphic units compared are mafic-poor Calico Hills Formation (Thp) and rhyolite of Echo Peak (Tpe), which occur in succession within certain areas of Pahute Mesa subsurface. Some non-representative samples from these units are not included in the comparison.

All "detailed" petrographic analyses in this database were performed by Rick Warren, using methods he developed to provide thoroughly documented petrographic analyses for minor and accessory minerals. These methods require that individual components be located on a "photomap" of a polished thin section, and their mineral identities, textures, and other features noted on standardized worksheets (Figure 5). Application of this technique requires combined use of reflected and transmitted light, with grain margins determined in reflected light to assure point counting on a truly planar surface without depth of field.

Figure 5. Photomaps and petrographic worksheets used for detailed petrographic analysis.

All detailed analyses require systematic scans of the entire polished thin section at 100X, first in reflected light, and then in transmitted light. Each scan consists of successive traverses across the entire length of the thin section, spaced 1.5 to 2.0 mm apart, with the field of view for each traverse, 1.7 to 2.2 mm, slightly overlapping that of the previous traverse. Traverses in transmitted light are offset from those in reflected light by 0.5 mm. Minerals intersected by the point count, those located during scans for the determination of their abundances, and components included to represent features of interest are marked with pins as shown in Figure 5. A point count usually precedes the systematic scans, but is not required for detailed analysis and is often omitted for crystal-poor samples. The pins are systematically removed from the photomap as the worksheet is completed. The worksheet is reduced into electronic form, and mineral abundances, based on the analytical method and mineralogic data from the worksheet, are determined through computer processing.

Except for sphene and allanite, which typically occur in larger grains, accessory grains either have a smaller thickness than the polished thin section or are wholly or partly included within opaque phases, making them virtually invisible in transmitted light (Figure 6). Consequently, abundances of most accessory minerals are highly underestimated without use of reflected light. All accessory and minor minerals have distinctive reflectivities, assuring that all individual grains in a polished section can be recognized, as required by Method A (described below).

Figure 6. Reflected light (left) and transmitted light (right) views of ilmenite grain O4 in split RW19AK2(B. Field of view is approximately 0.5 mm by 0.7 mm. Most inclusions, with examples identified as zircon (ZR), apatite (AP), and monazite (MN), are invisible in transmitted light.

The methods of detailed petrographic analysis are described in detail within database table pa_meth_list. Methods A, C, and E are those most frequently employed for detailed petrographic analysis. Method A is the most commonly used to determine abundances of primary minerals that occur at <100 parts per million by volume (ppmV). Method C, a variation of Method A, is more practical to apply at higher abundances of apatite, zircon, or perrierite/chevkinite, and utilizes the observed linear relationship between the areal density of these three accessory minerals and their abundances, as illustrated in Figure 7. Method E is the most commonly applied detailed petrographic method to determine abundances of mafic minerals, particularly when their abundances are between 1000 to 10,000 ppmV (0.1 to 1%).

Figure 7. Apatite abundances determined by method A plotted versus the areal density of apatite grains with areas >0.00045 mm2 observed in thin section. A least-square linear fit of these data yields the constant used to determine apatite abundances by method C.

The database also includes analyses of questionable or poor quality within separate database tables. These tables, which have names beginning in "xx_" (e.g., Table 4), provide such data for three reasons.

1. Retention of all superceded data, some erroneous, allows uncertainties in petrographic analyses to be quantified.

2. Values that statistically are highly imprecise and unusable for individual samples, such as those for accessory minerals from point count, can be combined from several samples to provide averages with acceptable precision.

3. We reject some entire published datasets based on comparisons to a subset of higher accuracy. A more complete comparison might result in the acceptance of these data.

Accurate petrographic data can be used to resolve many geologic problems. For example, petrologic measurements can allow correct correlation and assignment of stratigraphic units within the stratigraphic column. Table 6 provides very simple statistics for abundances of selected minerals in units of the Wahmonie Formation that are shown in Figure 3, illustrating that the units are genetically related and are a part of a single unique formation. Units of the Wahmonie Formation contain high plagioclase and biotite and low quartz and K-spar contents; such primary mineralogy readily distinguishes these units from nearly all others of the SWNVF. Units within the Wahmonie Formation are distinguished from each other by their abundances of individual mafic minerals.

Strat

n

 

Felsic phenocrysts

 

Mafic phenocrysts

 

Total

unit

   

QZ

KF

PL

 

Biotite

Hbld

Opx

Cpx

Olivine

 

%

                           

Twu

5

 

0.02

0

23.68

 

8800

10900

41200

34400

0

 

33.23

Twm

7

 

0.04

0

21.34

 

14400

2210

38400

41500

10800

 

32.1

Twl

14

 

0.3

0

18.04

 

21000

19400

8720

0

0

 

23.25

Twlb

22

 

0

0

17.94

 

20300

14900

0

0

0

 

21.46

Tww

9

 

0.76

0.18

13.97

 

21700

572

466

23

0

 

17.18


Table 6. Simple statistical summary of abundances for selected primary minerals in units of the Wahmonie Formation. Abbreviations are QZ for quartz, KF for alkali feldspar, PL for plagioclase, Hbld for hornblende, Opx for orthopyroxene, and Cpx for clinopyroxene. Values are medians from n samples. Symbols for stratigraphic units are defined in database table strat_list. Felsic abundances are in volume percent, and mafic abundances are in parts per million by volume (ppmV). Includes only analyses entered into database by 23 October 1998.

 

Detailed Optical Mineralogy

Detailed information from optical mineralogy is provided for more than 1,000 petrographic thin section splits within database tables listed in Table 7. Both standard and detailed petrographic analyses provide abundances and a qualitative definition of alteration for each mineral, but only detailed petrographic analyses, described in the previous section, represent summaries derived from optical mineralogy of individual mineral grains. These optical mineralogic analyses provide supplemental quantitative or qualitative data for specific mineral grains including size, texture, alteration, and chemical compositions. During the process of detailed petrographic analysis, specific grains that require optical mineralogic analysis are identified on a photomap of a thin section (Figure 5). The identified grains, assigned unique grain IDs, may be a single crystal or consists of an assemblage of grain components (minerals), each identified by a unique grain component ID. Probe analysis (described in the next section) provides quantitative chemical analyses for grain component minerals. Complete mineralogic analyses provide data for a full or representative set of grains for each mineral, according to the method used for petrographic analysis. For example, the distribution of sizes (as the area in thin section) can be determined for each mineral determined by point count or method A. Appendix B provides examples of rules followed and uses for complete mineralogic analyses and Appendix C provides blank and completed forms for such analyses. Complete mineralogic analyses are available within the database for roughly 200 polished thin sections. Hardcopy information is available for approximately 600 additional sections from the senior author.

Table name

Description

Foreign key tables

     

ma_gr_measure

Grain component petrographic analyses

comp_list, pa_meth_list, ans_list, worker_list, qa_list

ma_gr_comp_texture

Grain component textures

texture_list

     

ma_clast_measure

Individual clast analyses

comp_list, pa_meth_list, strat_list, lith_list, worker_list, qa_list

ma_clast_alt

Clast alteration

alt_list

ma_clast_malt

Clast minor alteration

alt_list

     

xx_ma_gr_measure

Superceded or erroneous grain component petrographic analyses

comp_list, pa_meth_list, ans_list, worker_list, qa_list

xx_ma_clast_measure

Superceded or erroneous individual clast analyses

comp_list, pa_meth_list, strat_list, lith_list, worker_list, qa_list


Table 7. Database tables for detailed optical mineralogic analyses. Tables with names that begin xx_ should not be employed for usual applications of mineralogic data.

 

Abundances of groundmass minerals cannot generally be determined within volcanic rocks of silicic affinity by optical methods. However, groundmass minerals of basic rocks are generally sufficiently coarse to quantify their abundances and 2-dimensional size ranges from point counts using reflected light. Basic volcanic rocks include basalt through andesite and their alkali-rich equivalents (Le Bas et al., 1986). Such rocks are also generally much simpler mineralogically than silicic volcanic rocks, and so fewer minerals are present, with abundances that usually provide satisfactory precision from point count. For basic rocks, complete mineralogic analysis usually provides 2-dimensional size ranges for all minerals except feldspar, which is generally so abundant that individual grains are bounded by other feldspar grains, rendering grain boundaries unrecognizable. Minerals that usually provide 2-D size distributions are olivine, clinopyroxene, and magnetite. Size distributions for each of these minerals, as well as for the largest feldspar grains, offer a more precise definition of basalt mineralogy than determination of separate abundances for "phenocryst", "microphenocryst", and "groundmass".

Minerals frequently occur within clasts in volcanic rocks. Clasts include:

Pyroclasts, such as pumices, shards, and lapilli of basalt or other cogenetic mafic components, representing original magma in most cases, and

lithics, which are foreign fragments of older rock.

Large clasts, clasts that contain more than a single component of interest, and clasts counted by point count are usually assigned a clast ID, and are described in the database (Table 7). Clasts generally become progressively less recognizable as alteration intensity increases. Mineral abundances from petrographic analyses include their occurrences within pyroclasts, but not within lithics. Aggregates of phenocryst-sized minerals, classified as lithics by some petrographers, are assigned glomerophyric textures and not considered lithics.

 

Microprobe Analyses

Quantitative mineral grain chemistry was obtained through more than 36,000 microprobe analyses which provide more than 370,000 analyte concentrations for common minerals within database tables described in Table 8. This quantitative mineral chemistry can be related to quantitative and qualitative mineralogic determinations of the grain component, such as area in thin section or alteration. Multiple probe analyses may be available for any grain component. Typically, these replicate analyses represent different analytical locations, such as core or rim, within a single mineral grain component.

Table name

Description

Foreign key tables

     

probe_rep

Microprobe analysis description

probe_loc_list, qa_list, ref_list, topic_list, worker_list

probe_measure

Microprobe analyses

probe_standard_set_list, oxide_list

probe_end_members

Mineral end members

end_member_list

     

xx_probe_rep

Description for unacceptable microprobe analyses

probe_loc_list, qa_list, ref_list, topic_list, worker_list

xx_probe_measure

Unacceptable microprobe analyses

probe_standard_set_list, oxide_list

xx_probe_end_members

Mineral end members for unacceptable microprobe analyses

end_member_list


Table 8. Database tables for microprobe analyses. Tables with names that begin xx_ should not be employed for usual applications of microprobe data.

 

The database also provides information from non-quantitative microprobe analyses. Most such analyses simply represent the recognition of a highly distinctive pattern of counts from energy dispersive spectroscopy (EDS) as shown in Figure 8. EDS analysis provides very accurate verifications of mineral identities that improve and validate the accuracy of petrographic analyses. Quantitative microprobe analysis is preferentially applied to a mineral with an uncertain identity, size large enough to allow significant zonation, unusual texture, or one intergrown with one or more other phase. EDS is generally used for grain components that are either unsuitable for quantitative analysis, or for minerals generally not analyzed. Detailed petrographic analyses incorporate either quantitative microprobe or EDS analyses for all grain components with identities that are even slightly uncertain.

Figure 8. Energy dispersive spectra (EDS) for common minerals within volcanic rocks of the SWNVF.

The database also includes more than 3,000 unacceptable quantitative microprobe analyses within separate database tables that have names beginning in "xx_" (Table 8). Most of the unacceptable microprobe analyses do not meet acceptance criteria described in Table 9. Some published analyses meet the criteria, but the entire sets are considered unacceptable because a very large fraction of companion analyses, usually >30%, fail to meet the criteria of Table 9. The acceptance criteria have not yet been rigorously applied to all analyses, but only a few unacceptable analyses likely remain in the database. Database tables provide unacceptable analyses for the following reasons:

1. These analyses always provide valuable verification of optical mineralogy.

2. Universal standards of analytical quality are not presently applied for quantitative microprobe analyses, so many analyses deemed unacceptable might be acceptable to certain users of this database.

3. Most analyses are rejected owing to analytical problems with a small number of elements, usually a single element within a suite of about 10 analyzed; the remaining elements may offer very useful information.

Table 9. Acceptance criteria for microprobe analyses within this database (at end of document).

 

XRD Analyses

The database includes quantitative and semiquantitative analyses of mineral components by X-ray diffraction (XRD) for nearly 1100 samples within the database tables described in Table 10. These analyses provide the "whole-rock" mineralogy of each sample, although in some cases the sample may represent a separated mineral or component such as pumice. Mineralogic analyses by petrographic methods provide a complementary data set that represents only phenocryst minerals, which are large enough to be recognized by optical techniques. Phenocrysts form within the magma prior to each volcanic eruption, and comprise a small fraction of the sample, typically between 0 to 30% of the rock. This assemblage of phenocrysts and their chemistry are almost always distinctive for each volcanic unit. Thus, petrographic analyses define mineralogy applicable to stratigraphy. Glass or tiny secondary minerals, which define mineralogy applicable to alteration, and which comprise the remaining 70 to 100% of most volcanic rocks, are difficult or impossible to quantify by petrographic methods. The large fraction of secondary minerals dominates the results of whole-rock sample analyses. Thus XRD analyses are most suitable for defining mineralogy applicable to alteration. Knowledge of the XRD method used, and of the nature of the sample are key considerations in the successful evaluation of these data.

XRD measurements are reported in the database as units of weight, whereas petrographic measurements are in units of volume. To exactly relate the two measurements requires knowledge of the bulk density of the sample, as well as the density of each constituent mineral. Non-numerical abundance measurements originally reported, e.g. "not detected", "trace", have been converted to numerical values recommended or implied by the analysts. Reports of "not detected" are represented in the database as zero. "Trace" abundances are typically assigned a value of 0.5% or 0.25%, which is assumed to represent the two sigma uncertainty.

Table name

Description

Foreign key tables

     

xrd_split

Method for XRD analysis

xrd_meth_list

xrd_measure

XRD analyses

comp_list


Table 10. Database tables for X-ray diffraction (XRD) mineralogic analyses.

This first revision of the database excludes the large set of XRD analyses within the GEODES database (Winterkamp et al., 1985). However, we anticipate adding these and many additional XRD analyses within the next version.

 

Geologic Intervals from drillholes

Database tables described in Table 11 define stratigraphic units, lithologies, major and minor alterations, and fracture and lithophysal zone intensities within elevation (depth) intervals for more than 750 drill holes of the SWNVF. These characteristics of the rock column, defined independently within successive intervals of elevation, are together termed "geologic intervals". The geologic intervals very strongly relate to the chemical, mineralogic, petrographic, and physical characteristics of the rock column provided by sample splits at points within geologic intervals, and to geophysical logs. Geologic intervals can be combined with these data to develop three-dimensional representations of the chemical, mineralogic, and petrographic characteristics of the subsurface, as well its physical properties.

Table name

Description

Foreign key tables

     

strat_int

Stratigraphic intervals

strat_list

lith_int Lithologic intervals lith_list
alt_int Alteration and minor alteration intervals alt_list, topic_list
frac_physae_int Fracture and lithophysal intervals frac_physae_list, topic_list

geol_int_ref

Citations for geologic interval characteristics

topic_list, ref_list


Table 11. Database tables for geologic intervals from drillholes.

 

Physical Properties and Geophysical Logs

This first revision of the database has added more than 21 million records that represent all geophysical logs originally within the GEODES database (Winterkamp et al., 1985). A large variety of geophysical logs added include density, porosity, water content, spectral gamma (K, U, Th), caliper, gravity, and many others listed within foreign key table log_type_list. Nearly all of these logs represent drill holes within Los Alamos use areas of the NTS, which occupy the southern half of Yucca Flat and the eastern part of Pahute Mesa. We have removed nearly 80,000 records transformed from GEODES that represent inferior or erroneous portions of geophysical logs, or entire logs. Most of these records reside within the database table geophys_int; the records removed reside within database table xx_geophys_int, both described in Table 12. The process to remove inferior or erroneous portions of geophysical logs is presently incomplete but should be complete with the next revision of the database.



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