Edward C. Reboulet and Warren Barrash...Edward C. Reboulet and Warren Barrash Center for Geophysical...
Transcript of Edward C. Reboulet and Warren Barrash...Edward C. Reboulet and Warren Barrash Center for Geophysical...
Core, Grain-Size, and Porosity Data from the Boise Hydrogeophysical Research Site
Boise, Idaho
Edward C. Reboulet and Warren Barrash
Center for Geophysical Investigation of the Shallow Subsurface Boise State University
Boise, Idaho 83725
Technical Report BSU CGISS 03-02 February 2003
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Table of Contents
Table of Contents.............................................................................................................. i List of Figures ................................................................................................................... iii List of Tables ................................................................................................................... vi List of Symbols ................................................................................................................ vii 1. INTRODUCTION ...................................................................................................... 1 2. DRILLING METHODS AND CORE RECOVERY ................................................. 3 3. CORE ANALYSIS AND SPLITS ............................................................................. 8 4. GRAIN-SIZE ANALYSIS .........................................................................................11
4.1. Cobble Analysis.................................................................................................14 4.2. Matrix Analysis .................................................................................................16
4.3. Data Calculations...............................................................................................20
4.4. Data Corrections ................................................................................................23
4.5. Grain-Size Distribution Types or Lithotypes ....................................................27
4.6. Slough ................................................................................................................33
4.7. Matrix Uniformity Coefficient or Sorting .........................................................34
4.8. Average Grain-Size Distributions......................................................................36
4.9. Average Continuous Length ..............................................................................37
5. POROSITY.................................................................................................................39
5.1. Assigning Porosity Values.................................................................................42
5.2. Porosity Units ....................................................................................................43 6. REFERENCES CITED...............................................................................................50
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7. APPENDICES ............................................................................................................53
7.1. Drilling Logs .....................................................................................................54 7.2. Core Photographs ..............................................................................................55 7.3. Core and Cobble Analysis Sheets .....................................................................56 7.4. Grain-Size Analysis Data Sheets.......................................................................57
7.5. Modified CX361 Engineering Properties of Soils Lab .....................................58
7.6. Grain-Size Analysis Data Sheets From Outcrops and Quarries........................66
7.7. Well Master Data Sheets ...................................................................................67
7.8. GSD Type Logs and Porosity Logs...................................................................68
7.9. Gamma-Spectrometry Analysis Worksheets.....................................................83
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List of Figures
Figure 1. Air photo of the Boise Hydrogeophysical Research Site, Boise, Idaho. Location and position of wells given on photo and inset of the central wellfield. Flow of the Boise River here is to the north-northwest……………………………..……………………..………2
Figure 2. The drilling process at the BHRS was a repeated sequence of
core, core, drill, drive, and drill…………………………………………...3 Figure 3. A. Split spoon from coring procedure at the BHRS.
B. Photograph of the same completed core box ready for analysis………4 Figure 4. Example of field notes taken during the drilling of the wells at
the BHRS…………………………………………………………..……...5 Figure 5. Schematic diagram of well construction, and generalized
stratigraphy at the BHRS………………………………………………….7 Figure 6. Core analysis sheet for a 2-ft sample of core from the BHRS…………….9 Figure 7. Core box from the BHRS showing the cobble survey transects
and the locations between sample splits…………………………………10 Figure 8. Grain-size scale for sediments, showing Wentworth size classes,
equivalent phi (Φ) units, and sieve numbers of U.S. Standard Sieves corresponding to various millimeter and Φ sizes. The highlighted sieve sizes were used on the BHRS core samples. (Modified from Boggs, 1996)……………………………………………12
Figure 9. Example of bag labels for the sample splits of the BHRS core………….13 Figure 10. Cobble analysis sheet for the core at the BHRS…………………………15 Figure 11. Grain-size analysis data sheet for the core from the BHRS. The
highlighted fields are filled by the person doing the GSA……………….17 Figure 12. A. Uncorrected histogram of grain-size distribution with
anomalous classes highlighted. B. Corrected histogram of the same grain-size distribution…………….24
Figure 13. Average Sand lithotype grain-size distribution based on 29 core
samples from 12 of 18 wells at the BHRS…...…………………………..28
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Figure 14. Average Floating Cobble lithotype grain-size distribution based on 70 core samples from 12 of 18 wells at the BHRS ...…………..…….28
Figure 15. Average Bimodal lithotype grain-size distribution based on 61
core samples from 12 of 18 wells at the BHRS….………………………29 Figure 16. Average Mixed Cobble lithotype grain-size distribution based
on 311 core samples from 12 of 18 wells at the BHRS...……………..…29 Figure 17. Average Large Cobble lithotype grain-size distribution based on
482 core samples from 12 of 18 wells at the BHRS………………....…..30 Figure 18. A line graph of the histogram values for the five lithotypes found
at the BHRS (see Figures 13-17)..…………………………………….…30 Figure 19. Ternary plots.
A. Shows the regions and transition zones for each lithotype. B. Shows each of the BHRS samples plotted of the graph………...……32
Figure 20. Examples of normalized matrix fractions showing D10 (short
dashes) and D60 (long dashes) for calculation of matrix uniformity coefficients, Um ………………………………………………….………35
Figure 21 Example logs for well C5 at the BHRS.
A) A quick reference lithotype log where, in general, the lighter the color the more matrix material present in the interval. The dark and medium blues represent Large and Mixed Cobble lithotypes. The purple intervals represent the Bimodal lithotype. And the green and yellow intervals represent Floating Cobble and Sand lithotypes. Blank intervals are zones of no recovery or slough. B) A second type of GSD lithotype log: this is a bar graph log where intervals showing greater cobble dominance lithotypes extend further to the right in the log. C) Porosity values derived from neutron logs recorded at the BHRS with identification of the different porosity units (see Section 5.2) found in the subsurface at the BHRS. D) Four component log which shows representative sample volume of intervals by integrating porosity (void volume) with the solid volume fraction (cobbles and matrix). E) Three component log showing the relative composition of the solid volume fraction of each sample interval…………………………...41
Figure 22. Matlab® script to assign average geophysical log values to sample
intervals…………………………………………………………………..42
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Figure 23. Porosity log cross-sections, A) A-A’ and B) B-B’, showing the porosity units in the central portion of the wellfield (From Barrash and Clemo, 2002)……………………………………………….44
Figure 24. Normalized histograms of the neutron derived porosity values
within each Porosity Unit. The solid line superimposed over each histogram is a normal distribution using the same statistics. A) Unit 1. B) Unit 2…………………………………………………….45 C) Unit 3. D) Unit 4…………………………………………………….46 E) Unit 5. F) A comparison of units with the statistics shown in Table 9……………………………………………………….…………..47
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List of Tables
Table 1. Table of identifiers used to code sample interval bags from the BHRS…………………………………………………………………….13
Table 2. Sieve stacks used in the grain-size analysis at the BHRS………………..18 Table 3. Hydrometer reading schedule used in the grain-size analysis for
BHRS core samples……………………………………………………...19 Table 4. Table of parameters used in the GSD lithotype coding process…………31 Table 5. Average matrix uniformity coefficients (Um) for each lithotype by
porosity unit (see Section 5.2)………………………………………..….35 Table 6. Average weight percent values, porosity and matrix sorting values
for lithotypes (from Appendix 7.7)………………………………………36 Table 7. Average continuous thickness intervals for each lithotype by porosity
unit (see Section 5.2)……………………………………………………..38 Table 8 Depth of investigation of the neutron tool as a function of porosity
(from Rider, 1996)……………………………………………………….39 Table 9. Porosity statistics for the porosity units………………………………….43 Table 10. Elevations used for the basal contact picks for each porosity unit.
Note absence of Unit 5 in four wells on the eastern side of the BHRS….48 Table 11. Average porosity values for each lithotype by porosity unit..…………...49
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List of Symbols
MFINES ........................Mass of entire matrix fraction. MOGR......................................Mass of sample split for analysis. MTR18 .........................Total mass retained on no.18 and larger sieves after sieving. MR## ..........................Mass retained on sieve no. ##. FR ..............................Fragments of cobbles in no.5 sieve. HMCF .......................Hygroscopic moisture correction factor. MOD............................Mass oven dried sample. MAD ............................Mass air dried sample. MHSOD ........................Mass hydrometer sample, oven-dried. MR##mm......................Mass retained for calculations of cobble size class ##mm. M##mm.........................Mass of cobble size fraction for entire sample interval. MHSAD ........................Mass hydrometer sample air dried. W................................Represented mass of hydrometer sample. %P## ..........................Percent of the sample passing a given sieve size (##). %P .............................The represented percent of soil in suspension. D.................................The calculated diameter of the largest soil particle in suspension. GS ...............................The specific gravity for the grains (2.65-g/cm3). GMIX ...........................The corrected hydrometer readings for each batch of standard. ? .................................Dynamic viscosity of water. L .................................The depth of hydrometer (cm) t ..................................Sample reading time (min). WP## ..........................Weight percent of ## size class. MRFINES .....................Mass retained of the matrix fraction after analysis. PR##............................Percent retained on ## size class. Um ..............................Matrix Uniformity Coefficient.
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1 INTRODUCTION
Data sets examined within this Technical Report are taken from the Boise
Hydrogeophysical Research Site (BHRS). The BHRS is a research wellfield located on a
cobble bar adjacent to the Boise River 15 km from downtown Boise, Idaho (Figure 1).
Deposits at this site are the youngest in a series of Quaternary to Recent coarse braided-
stream deposits of the Boise River.
Data from the subsurface at the BHRS which support the interpretation of coarse
braided-stream deposits include core from 18 wells and GPR reflection surveys at the
site, both of which identify 18 to 21 meters of unconsolidated cobbles and sands
underlain by a tight red clay (Barrash and Knoll, 1998; Peretti, Knoll, Clement, and
Barrash, 1999). At the BHRS, core analysis was supplemented with borehole, crosshole,
and surface geophysical data.
This report will cover the details of the core and grain-size analysis and will correlate
neutron-derived borehole porosity measurements with recovered intervals of the core.
The report will cover the field methods and procedures used in the core drilling and
recovery process. Then the report will detail the laboratory procedures used in the
analysis of core from the BHRS. Finally this report will detail the computations and
analysis of the corrected data sets completed to date for: grain-size analysis, lithotype
assignments, and neutron-derived porosity-based hydrostratigraphic units (Reboulet,
2003).
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Figure 1. Air photo of the Boise Hydrogeophysical Research Site, Boise, Idaho. Location and position of wells given on photo and inset of the central wellfield. Flow of the Boise river here is to the north-northwest.
The methods and calculations contained within this report were applied to the core
from all 18 of the wells at the BHRS. The results and statistics presented within this
report and associated appendices are for 15 of the 18 wells.
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2 DRILLING METHODS AND CORE RECOVERY
The BHRS consists of 18 wells emplaced in 1997 and 1998 using a split-spoon
coring and tricone rock-bit drilling method. The well drilling process followed a repeated
sequence of coring, drilling, and driving temporary casing (Figure 2). A high percentage
of core recovery (84%) was accomplished by driving a 2.5 inch (6.3 cm) ID by 1.5 or 2 ft
(0.46 or 0.61 m) long split spoon with 140 pound hydraulic and 300 pound slide
hammers. This method truncates cobbles that are larger than the diameter of the spoon
mouth or that straddle the spoon mouth. Whole cobbles, cobble fragments, and matrix
sands were captured mostly in place using this method (Figure 3).
Figure 2. The drilling process at the BHRS was a repeated sequence of core, core, drill, drive, and drill.
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Figure 3. A. Split spoon from coring procedure at the BHRS. B. Photograph of the same completed core box ready for analysis.
A
B
5 Any sections of unrecovered core were assigned to the top of the core barrel for a
given core section. Field notes of the well drilling process (Figure 4 and Appendix 7.1)
include blow counts for coring and casing, drilling notes, and recovery diagrams for each
spoon. Two spoons were driven in succession followed by drilling to the cored depth
with a rock bit. Then 5 inch (12.7 cm) ID, 5.25 inch (13.3 cm) OD steel casing with a
welded-on 6 inch (15.2 cm) drive shoe was driven to the cored depth followed by a
second drilling cycle to clean out the hole (Barrash and Knoll, 1998). This core-core-
drill-drive-drill sequence (Figure 2) was used through the entire thickness of the
unconsolidated cobble-and-sand units. In some of the wells at the BHRS, a thin (<1 m),
Figure 4. Example of field notes taken during the drilling of the wells at the BHRS.
6 basalt layer below the cobbles and sand, and above the clay layer (Figure 5) was
encountered. This basalt was not cored, but drilled through with the rock bit, and the
cuttings were examined.
During the drilling with the rock bit, a synthetic drilling “mud” was used to help lift
the drill cuttings without adding mineral solids (e.g., bentonite) to the formation. The
synthetic “mud” was removed from the completed well with the addition of 5.25%
sodium hypochlorite solution (common bleach). The wells were completed through the
unconsolidated cobble-and-sand deposits, and 5 or 10 ft (1.5 or 3 m) into red clay that
underlies the entire site. Once the hole had been drilled into the clay, the 4 inch (10 cm),
schedule 40, PVC well casing and screen (Figure 5) was assembled and installed inside
the temporary drive casing. After the PVC well casing and screen were installed, the
well was flushed with clean water and then the temporary drive casing was pulled out of
the hole allowing the formation to collapse against the well casing and screen.
7
WL @ 7000 cfs
WL @ 1000 cfs
Clay
Cobbles andSand
60
50
40
30
20
10
5 ft
65 ft
4-inchPVC
Basalt
∆
∆
Figure 5. Schematic diagram of well construction, and generalized stratigraphy at the BHRS.
0.020 inch Slotted Screen
Blank Casing
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3 CORE ANALYSIS AND SPLITS
The core recovered from the BHRS was analyzed in the Soils Properties Laboratory
at Boise State University during the period of 1998 to 2003. Each core box was
photographed with depth labels, well identification tags, and a scale bar in order to
preserve a historical record of the recovered core (Figure 3B and Appendix 7.2). Within
the core box, the core was examined in 2 ft (0.61 m) intervals regardless of the length of
the split spoon used for recovery.
Each 2 ft section of core was first examined for gross lithologic changes, and
locations of no recovery were checked against the drilling notes taken in the field. These
features were noted on the core analysis pages for each section (Figure 6 and Appendix
7.3). Then a transect of each section of core was laid out above the core using a folding
engineering scale marked in feet. This transect was used to make a first-order estimate of
cobble volume percentage (Underwood, 1970; Clarke, 1979; Medley, 1994). The
position of all cobbles and cobble fragments which were intercepted by the transect
(Figure 7) with a length greater than 0.03 ft (~10 mm) were recorded on the core analysis
sheet.
The detailed characteristics of each 0.6 m section of core were examined and the
section was broken into sample intervals based upon changes in lithology, size, shape or
relative volume of cobbles, and/or composition and average size of the matrix material.
The largest allowable length of sample was 1 ft (0.3 m). After the interval splits were
made, relative volumes of cobbles to matrix were calculated for each interval.
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Figure 6. Core analysis sheet for a 2-ft sample of core from the BHRS.
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Figure 7. Core box from the BHRS showing the cobble survey transects and the locations between sample splits.
From the transect measurements, the lengths of all of the cobble and cobble-fragment
intercepts within a sample interval were summed. The sum of these intercepts was
divided by the overall length of the sample to produce a first-order estimate of cobble
volume percent in each recovered interval.
100×= ∑LengthInterval
InterceptstsecTranCobblePercentVolumeCobble (1)
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4 GRAIN-SIZE ANALYSIS
Each sample interval of core underwent a complete grain-size analysis (GSA) using
American Society for Testing and Materials (ASTM) standard analysis test methods as a
guide (ASTM, 1996). The sieve sizes recommended by ASTM D-422-63 were modified
so that the results of this grain-size analysis would have size classes more similar to those
reported in the geologic literature (Figure 8).
Prior to splitting out each sample interval for grain-size analysis, a system of labeling
was established in order to keep the samples organized and available for future analysis.
Each sample interval identified in the core analysis was removed from the core storage
box and placed into a series of labeled zip-lock bags. The labeling of the bags (Figure 9)
consists of the BHRS well ID, the box number containing that particular depth interval of
core sample, the depth interval of the sample (in feet from land surface), and an identifier
as to what fraction of the depth interval was contained within each bag. Currently there
are six identifiers used in sample labeling for the core samples from the BHRS (Table 1).
12 Figure 8. Grain-size scale for sediments showing Wentworth size classes, equivalent phi (Φ) units, and sieve numbers of U.S. Standard Sieves corresponding to various millimeter and Φ sizes. The highlighted sieve sizes were used on the BHRS core samples. (Modified from Boggs, 1996).
U.S. Standard Sieve Mesh
Phi (Φ) Units Wentworth Size Class
4096 -12.01024 -10.0 Boulder
256 256 -8.064 64 -6.0
16 -4.05 4 4 -2.06 3.36 -1.757 2.83 -1.508 2.38 -1.25
10 2.00 2 -1.0012 1.68 -0.7514 1.41 -0.5016 1.19 -0.2518 1.00 1 0.0020 0.84 0.2525 0.71 0.5030 0.59 0.7535 0.50 1/2 1.0040 0.42 1.2545 0.35 1.5050 0.30 1.7560 0.25 1/4 2.0070 0.21 2.2580 0.177 2.50
100 0.149 2.75120 0.125 1/8 3.00140 0.105 3.25170 0.088 3.50200 0.074 3.75230 0.0625 1/16 4.00270 0.053 4.25325 0.044 4.50
0.037 4.750.031 1/32 5.0
0.0156 1/64 6.0 Medium Silt0.0078 1/128 7.0 Fine Silt0.0039 1/256 8.0 Very Fine Silt
0.002 9.00.00098 10.00.00049 11.00.00024 12.00.00012 13.00.00006 14.0
Coarse Sand
Medium Sand
Fine Sand
Millimeters
Cobble
Pebble
Granule
GR
AV
ELSA
ND
MU
D
SILT
CLA
Y
Very Fine Sand
Coarse Silt
Clay
Very Coarse Sand
13
X1 , 1 : 2.00-2.32 c
Figure 9. Example of bag labels for the sample splits of the BHRS core.
Identifier Explanation Example
C
Used for the portion of the sample larger than 3/8" or 9.525 mm.
X1,1;2.00-2.32 c
S
Used for the archive portion of the sample smaller than 3/8" or 9.525 mm.
X1,1;2.00-2.32 s
SF (note)
Used for the sand fraction between 0.25 and 1.0 mm removed from the ‘S’ fraction bag. The note will include the weight and location of any of the sample that is not present in the ‘SF’ bag.
X1,1;2.00-2.32 sf (80g in GS)
S (-SF)
Used for the archive portion of the sample smaller than 3/8" or 9.525 mm that has had the sand fraction between 0.25 and 1.00 mm removed.
X1,1;2.00-2.32 s (-sf)
S (-SF)
Completely reconstituted archive portion of the sample smaller than 3/8" or 9.525 mm. (All parts of the ‘SF’ fraction have been re-mixed back into bag)
X1,1;2.00-2.32 s (-sf)
A
Used for the portion of the ‘S’ fraction that has been used in the ASTM grain-size analysis.
X1,1;2.00-2.32 a
Table 1. Table of identifiers used to code sample interval bags from the BHRS.
Well ID
Box Number Depth Interval
Identifier (See Table 1)
144.1 Cobble Analysis
After identification of all the sample intervals within each core box, the individual
sample intervals were separated from the core and removed from the box for analysis.
Each sample interval was separated into two components: a cobble fraction and a matrix
fraction. This first split of the core was accomplished using two sieves (3/4 in [19.0 mm]
and 3/8 in [9.5 mm]) and a pan. This sieve stack was put into a roto-tap for five to ten
minutes in order to separate all the fines from the cobble material.
The fraction retained in the 19 mm sieve was then hand sorted into two size classes:
19 to ~40 mm and greater than 40 mm. The fraction retained on the 9.5 mm sieve was
then hand sorted into three size classes: the two classes mentioned above and a class from
9.5 to 19 mm. For reference, the portion of the sample interval larger than 9.5 mm is
called the cobble fraction in this report. Fragmented cobble pieces from both sieves were
placed into their appropriate size classes by first examining the unbroken, naturally
weathered portion of the fragments and then estimating how much of the original cobble
had been broken off in the coring process. Smaller fragments were also placed into larger
size classes based upon matching the fragments with their larger source cobbles.
Each of the three size classes that comprise the cobble fraction of the sample interval
(9.5 – 19 mm, 19 – 40 mm, > 40 mm) were recorded on the cobble analysis sheets
(Figure 10 and Appendix 7.3). The textural elements, shape, and roundness of whole
cobbles in each size class were also recorded on these cobble analysis sheets. All whole
cobbles and fragments of each size class were weighed and their collective weight was
recorded on the cobble analysis sheets and on the core analysis sheets for later data entry.
For the first few wells examined, the volume and density of the cobbles were also
15determined by immersion in graduated cylinders and recording the amount of water
displaced. This process showed that the average density of cobbles at the BHRS was in
the range of 2.6 to 2.7 g/cm3.
Figure 10. Cobble analysis sheet for the core at the BHRS.
164.2 Matrix Analysis
Before a matrix sample is analyzed, the entire matrix sample is weighed and then
divided into a split for analysis with the remaining fraction reserved as an archived
sample. This sample splitting is accomplished using a soil splitter that randomizes the
splits of the two samples. The analyzed sample is repeatedly put through the soil splitter
to reduce the analysis sample to less than half the total matrix fraction weight, or 150 to
175 g of sample, whichever weight is less. The archived portion of the sample is returned
to the core box and the weights of the entire matrix fraction (MFINES) and the sample split
(MORG) are recorded on the GSA Data Sheet (Figure 11 and Appendix 7.4).
The grain-size analysis is based on ASTM standards and a procedure established by
Dr. Paul Michaels (Michaels, 1997, Appendix 7.5). The split for analysis is first sieved
through a no. 18 (1 mm) sieve with the material retained on the sieve being transferred to
a mortar to break any fines free of the larger particles. This material is then sieved a
second time in the no. 18 sieve and the retained material is washed and oven dried until a
stable weight is obtained. The weight of this cleaned and dried sample is recorded as
MTR18 on the data sheet. This MTR18 sample is then sieved in the coarse matrix sieve
stack (Table 2) that consists of no. 5 (4 mm), no. 10 (2 mm), and no. 18 (1 mm) sieves.
The mass retained on each sieve (MR##) is recorded on the data sheet. The MR5 sample
is examined by hand for fragments of larger cobbles. The weight of any fragmented
pieces of cobbles that appear to have come from cobbles larger than 9.5 mm are recorded
as FR on the data sheets. This FR subset is explained in greater detail in Section 4.4
Data Corrections.
17 Figure 11. Grain-size analysis data sheet for the core from the BHRS. The highlighted fields are filled in by the person conducting the GSA.
Sample Interval _______________ Date _________________ Name ____________
Entire Sand Fraction Weight g mass of sand fraction + container- g mass of container
g mass of sample (MFINES)+ g mass of cobbles (MCOB)
g mass of Division
Split sample for analysis g mass of container + sample- g mass of container
g mass of sample (MORG)
Coarse Fraction g mass of container + sample- g mass of container
g mass of sample (MTR18)
Coarse Sieve Stack
Sieve SizeMass of
container + sample
Mass of Container
Mass Retained Symbol
3/8" MR3/8
no.5 MR5
no.10 MR10
no.18 MR18
pan panMTR18AS
Hygroscopic MoistureAir Dried Sample g mass of container + sample (AD)
- g mass of containerg mass of sample (MAD)
Oved Dried Sample g mass of container + sample (OD)- g mass of container
g mass of sample (MOD)
HMCF = MOD / MAD =
Hydrometer Testing & Fine Sieve StackSample g mass of container + sample
- g mass of containerg mass of sample (MHSAD)
Time (minutes)
Time & Date (mm/dd/time) Reading Temperature Sieve
Size
Mass of container +
sample
Mass of Container
Mass Retained Symbol
0 no.35 MR35
2 no.60 MR60
5 no.120 MR120
15 no.230 MR230
30 pan pan60 MTR18AS
2501440
Grain Size Analysis
Sum the Mass Retained
Sum the Mass Retained
18
Sieve Stack U.S. Standard
Sieve Mesh Millimeters Phi Units
Cobble
3/4 inch 3/8 inch Pan
19.05 mm 9.525 mm
-4.25 -3.25
Coarse Matrix
No. 5 No.10 No.18 Pan
4 mm 2 mm 1 mm
-2.00 -1.00 0
Fine Matrix
No. 35 No. 60 No. 120 No. 230 Pan
0.5 mm 0.25 mm 0.125 mm 0.0625 mm
1.00 2.00 3.00 4.00
Table 2. Sieve stacks used in the grain-size analysis at the BHRS.
Approximately 10 g of the sample split that passed the no. 18 sieve earlier is used to
calculate the moisture content in the matrix material of the sample interval. The air-dried
(MAD) weight is recorded and the sample is dried in the oven until a stable weight is
obtained (MOD). The hygroscopic moisture correction factor (HMCF) is the ratio of the
oven-dried to air-dried sample weight:
AD
OD
MM
HMCF = (2)
The weight of the remaining sample is recorded on the data sheets as MHSAD.
The next step in the grain-size analysis is to determine the distribution of the silt- and
clay-size particles using hydrometers and settling cylinders. The MHSAD sample is
soaked in 125 ml of 40 g/L hexametaphosphate dispersing solution for at least 16 hours.
This soaking separates and surrounds the clay-size particles in the sample. After the
soaking period the sample solution is transferred to a malt mixer cup using DI water. The
solution is stirred in the mixer for about 1 minute and then is transferred to a 1000 ml
19settling cylinder and the volume is brought up to 1000 ml with DI water. The cylinder
is sealed and agitated for another minute by hand, after which hydrometer readings are
immediately started as prescribed in the measurement schedule (Table 3). This step has
been skipped for the final four wells from the BHRS undergoing analysis (X5, X3, B2,
and C4) after it was determined that silt-size and finer grains were almost entirely
artifacts due to the drilling processes (see Section 4.4).
Time (minutes)
Reading RT
Temperature (oC)
0 2 5
15 30 60 250 1440
Table 3. Hydrometer reading schedule used in the grain-size analysis for BHRS core samples.
After completion of the hydrometer readings, the sample is removed from the settling
cylinder and washed through a no. 270 (0.053 mm) sieve. The sample is then oven-dried
until a stable weight is obtained. The oven-dried sample is then sieved in the fine-matrix
sieve stack (Table 2) that consists of no. 35 (0.5 mm), no. 60 (0.25 mm), no. 120 (0.125
mm), and no. 230 (0.0625 mm) sieves. The weight retained (MR##) on each sieve is
recorded on the data sheets.
204.3 Data Calculations
The complete grain-size analysis produces four data sets: cobble weight; coarse sieve
stack; fine sieve stack; and hydrometer readings. The weights and other measurements
recorded on the GSA data sheets are entered on a duplicate data sheet in a custom-
designed Excel® worksheet (Appendix 7.4). This worksheet is used to run all of the
calculations to convert the four data sets into a smooth single curve that is representative
of the grain-size distribution for each recovered sample interval.
The data from the cobble analysis are representative of the entire sample interval,
and the weights for each cobble size class must be made proportional to the analyzed
portion of the matrix sample. The proportional mass of cobbles for each cobble size class
is calculated using equation (3), showing the calculations for the >40 mm size class as an
example.
FINES
ORGmmmm M
MMMR *4040 >> = (3)
Each cobble weight fraction (>40 mm, 20 mm, and 9.5 mm) is multiplied by the ratio of
the analyzed sample split to the entire matrix fraction.
The weights recorded for the contents found within each sieve in both the coarse and
fine sieve stacks give the proportional mass retained (MR##) for each size class directly.
The hydrometer sample mass must first be corrected to an oven-dried equivalent mass,
MHSOD, by multiplying the air-dried mass by the hygroscopic moisture correction factor.
HMCFMM HSADHSOD *= (4)
21This mass must then be scaled to the equivalent mass of the original sample split
analysis so that the hydrometer curves blend together with the other grain-size curves at a
common scale. This representative mass, W, is calculated by:
%100*% 18
=
PM
W HSOD (5)
using the oven-dried equivalent mass (MHSOD) and the percent passing the No. 18 sieve
(%P18)
The hydrometer and temperature readings recorded during the hydrometer testing
stage must then be converted into the represented percent of soil in suspension (P), and
the calculated diameter of the largest soil particle still in suspension (D) at each
scheduled reading interval.
% ( ) ( )0.1*0.1
*000,100
−
−
= MIXS
S GG
GW
P (6)
( ) tL
GD
S
*0.1
30−
=η
(7)
Where:
100,000 is the product of the cylinder volume (1000 ml), the unit mass of water
(1 g/cm3), and 100%
GS is the specific gravity for the grains (2.65 g/cm3)
GMIX is the corrected hydrometer readings for each batch of standard
1.0 is the specific gravity of water
? is dynamic viscosity of water (g/cm sec)
L is depth of hydrometer (cm)
t is sample reading time (min)
22All of the hydrometer-derived size classes (D) and percent soil still in suspension (%P)
at each of the hydrometer reading intervals were combined into a single size class for
data sets at the BHRS. This size class was recorded as <0.0625mm.
23
4.4 Data Corrections
During the initial analysis of the first wells tested, anomalous values in two weight
classes were recognized in the data graphs (Figure 12A). These two anomalous classes
are the 4 to 9.5 mm class and the <0.0625 mm class. The 4 to 9.5 mm size class was the
largest grain-size class that was not sorted by hand; its bin size was wider than the
standard one phi size class used in this analysis. A one phi size bin would have been 4 to
8 mm; however the 9.5 mm (3/8 inch) sieve is a more standard size sieve, and grain sizes
up to 9.5 mm are considered matrix material. We included grains up to 9.525 mm in the
matrix category because grains up to pebble size commonly fill interstitial space between
cobble framework grains (see also Smith, 1986; Todd, 1989; Shih and Komar, 1990a).
The additional 1.5-mm bin width alone was not enough to account for the unusual weight
percent spikes seen in this class.
Upon closer examination of the material retained on the 4 mm sieve, it became
apparent that the material was comprised of a significant percentage of fragments broken
from larger cobbles. It would have been a very time consuming and difficult process to
try to reconstitute these fragments (FR) into their proper size classes. Therefore the
following correction process was used to correct the anomaly of this weight class and to
redistribute the excess weight proportionately to the larger size classes.
The representative weight percents of the cobble classes are summed to obtain the
weight percent of cobbles in the sample interval.
mmmmmmCOB WPWPWPWP 5.92040 ++= > (8)
24
Grain Size
0
10
20
30
40
50
Wei
ght
Per
cent
Grain Size
0
10
20
30
40
50
Wei
ght
Per
cent
B
A
Figure 12. A. Uncorrected histogram of grain-size distribution with anomalous classeshighlighted. B. Corrected histogram of the same grain-size distribution.
-5.2538.10
-4.2519.05
-12.00
-24.00
-3.259.525
4.0625
3.125
2.250
1.500
01.00
phimm
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
25The method utilized to remove the anomalous peak in the 4 mm size class was to
calculate a new weight percent for the class by assigning it the average of its two adjacent
weight classes (see also Folk, 1966):
( )
225.9
4
WPWPWP NEW
+= (9)
The weight percent removed by this averaging was then redistributed proportionally to
each of the cobble size classes as shown by the redistribution of the >40 mm weight
class:
( )
−+= >
>>COB
ORIGNEWORIGORIGNEW WP
WPWPWPWPWP 40
444040 * (10)
This equation was then applied to the other two cobble size classes thereby correcting the
anomaly in the 4 mm size class and redistributing the weight removed back to the larger
cobble size classes.
The second anomaly was a minor peak in the <0.0625 mm size class (Figure 12A).
This class was comprised of all sediments measured in the hydrometer analysis (i.e., silts
and clays). While this size class showed an increase in weight percent for core samples
from the BHRS, other samples tested from outcrops and quarries in the Boise area
(Appendix 7.6) showed a lack of sediments in this size class. Of the outcrop and other
samples tested, normally there was less than 2% percent in this size class. The only
samples that showed elevated weight percents in this size class were samples taken of
rock flour (i.e., including artificially ground-up sizes) taken from the road surface at the
Prime Earth quarry. Therefore, this size class was eliminated from the analysis as being
an artifact of the drilling process and not naturally occurring. It should be noted that
26published GSD analyses for similar deposits commonly are deficient in grains <0.0625
mm (see also Carling and Reader, 1982; Church, McLean, and Wolcott, 1987, Figures
3.2 and 3.8; Lord and Kehew, 1987; Paola and Seal, 1995; Barrash, Morin, Gallegos,
1997; Heinz, 2001)
After both of the size class anomalies were corrected, the weight percents for the
recalculated size classes and all the matrix size classes were renormalized to represent
100% of the solid volume fraction of the sample (Figure 12B).
274.5 Grain-Size Distribution Types or Lithotypes
After the GSDs were corrected, a GSD Type or Lithotype was assigned to each
sample interval. These lithotypes are based solely on the grain-size distribution of each
sample. All of the corrected GSDs of sample intervals from the BHRS have been
classified into one of five lithotypes. The first is a Sand lithotype (Figure 13) and is
comprised entirely of material smaller than 9.525 mm (i.e., the size of matrix material).
The second lithotype is dominated by matrix-size material but also contains small
quantities of material larger than 9.525 mm. These matrix-supported intervals are type
coded as Floating Cobbles (Figure 14). The third lithotype has a bimodal distribution of
cobbles and matrix-size material, and is coded as Bimodal (Figure 15).
The final two lithotypes are dominated by cobbles and have cobble-size clast-
supported framework with interstitial matrix. The intervals that are coded as Mixed
(Figure 16) are comprised of very poorly sorted sands and gravels. These intervals are
easily recognized on histogram plots by their almost linear decrease of weight percent
with decreasing grain size. The last lithotype, Large Cobble (Figure 17), is dominated by
the >40 mm size class. For the Large Cobble lithotype, the weight percentage of the >40
mm class starts at 30%, with some intervals having >60% of the entire sample interval
comprised of this size class alone. Figure 18 shows the average weight distributions for
all the samples at the BHRS in each lithotype.
28
Grain Size
0
10
20
30
40
50
Wei
ght
Per
cent
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
Grain Size
0
10
20
30
40
50
Wei
ght
Per
cent
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
Figure 14. Average Floating Cobble lithotype grain-size distribution based on 98 coresamples from 15 of 18 wells at the BHRS.
Figure 13. Average Sand lithotype grain-size distribution based on 40 core samplesfrom 15 of 18 wells at the BHRS.
29
Grain Size
0
10
20
30
40
50
Wei
ght
Per
cent
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
Grain Size
0
10
20
30
40
50
Wei
ght
Per
cent
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
Figure 16. Average Mixed Cobble lithotype grain-size distribution based on 391 coresamples from 15 of 18 wells at the BHRS.
Figure 15. Average Bimodal lithotype grain-size distribution based on 85 core samplesfrom 15 of 18 wells at the BHRS.
30
Grain-Size
0
10
20
30
40
50
Wei
ght
Per
cent
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
Grain-Size
0
10
20
30
40
50
Wei
ght
Per
cent
phimm
4.0625
3.125
2.250
1.500
01.00
-12.00
-24.00
-3.259.525
-4.2519.05
-5.2538.10
Figure 18. A line graph of the histogram values for the five lithotypes found at theBHRS (see Figures 13-17).
Figure 17. Average Large Cobble lithotype grain-size distribution based on 611 coresamples from 15 of 18 wells at the BHRS.
Sand
Floating Cobbles
Bimodal
Mixed
Large Cobble
31One of the five lithotypes was assigned to each sample interval based on the
distribution of the corrected weight percentages using a three-component system of
weight distributions (Table 4). The first of the three components used was the large
cobbles. This was the weight percent of the sample that was larger than 40 mm. The
next component was mixed cobbles and was comprised of the weight percent of the
sample that was larger than 9.525 mm and smaller than 40 mm. The third component
used in the evaluation process is the matrix-sized material that was comprised of the
remaining weight percent from 0.0625 to 9.525 mm.
Lithotype Large Cobbles >40mm
Mixed Cobbles 9.525-40mm
Matrix 0.0625-9.525mm
Sand 0 0 100% Floating Cobbles >0 >0 >70 and <100%
Bimodal >0 >0 >55 and <70% Mixed <30% >0 <55%
Large Cobbles >30% >0 <55% Table 4. Table of parameters used in the GSD lithotype coding process.
Once the lithotype had been assigned, each sample was examined by hand to ensure
the GSD graph has the appearance appropriate for each lithotype assigned to it. In fewer
than 5% of the intervals, it was observed that the strict analytical method used to assign
the lithotype code left some apparent borderline cases with questionable GSD lithotype
assignments. These samples were reassigned lithotypes based on observation of the GSD
histograms and by the understanding that there may be transitional samples between
lithotypes. A ternary plot (Figure 19) of the three components and the questionable
samples showed that if a five percent transition region was added to the quantities in
32Table 4, the questionable samples then fall within the lithotype that they more closely
resemble with few exceptions.
0.00 0.20 0.40 0.60 0.80 1.00
Large Cobbles% > 40 mm
1.00
0.80
0.60
0.40
0.20
0.00
Mixed C
obbles
% Betw
een
9.525 - 40 mm
1.00
0.80
0.60
0.40
0.20
0.00
Mat
rix
% B
etw
een
0.06
25 -
9.52
5 m
m
0.00 0.20 0.40 0.60 0.80 1.00
Large Cobbles> 40 mm
1.00
0.80
0.60
0.40
0.20
0.00
Mixed C
obbles
9.525 - 40 mm
1.00
0.80
0.60
0.40
0.20
0.00
Mat
rix
0.06
25 -
9.52
5 m
m
Figure 19. Ternary plots. A. Shows the regions and transition zones for each lithotype. B. Shows each of the BHRS samples plotted on the graph.
Mixed Large Cobbles
Bimodal
Floating Cobbles
Sand
Sand
Floating Cobbles
Bimodal
Mixed
Large Cobbles
334.6 Slough
Once all the coding was assigned and checked, the next step was to check the
samples for intervals that may be artifacts of the drilling process, or slough. This
identification process involved looking through the original site drilling logs and the core
description sheets to locate and record intervals that were originally thought to be slough
or of a questionable nature. Slough is comprised of matrix-sized particles (i.e., Sand
lithotype), which are really numerous broken fragments that often appeared as mixed
dark- and light-colored grains. Slough usually occurs at the top of a recovery interval
(i.e., captured grains in the fluid column) or where the core barrel was bouncing and not
driving. For the latter type of slough occurrence, field notes for sample intervals coded
as sand or floating cobbles indicated hammer blow counts during coring that were too
high to justify going through this type of material.
344.7 Matrix Uniformity Coefficient or Sorting
Matrix of each sample interval was assigned a uniformity coefficient (Fetter, 1994)
or sorting value based on the sorting characteristics of the matrix-sized material (i.e.,
grains <9.525 mm). The first step in this process was to normalize the matrix size
fractions by the total weight percentage of the matrix fraction. Then these normalized
weight percentages were plotted on a semi-log graph (Figure 20). From the graphs the
grain diameter associated with D10 (10% of the fraction being finer) and D60 (60% of the
fraction being finer) were recorded. The uniformity coefficient associated with the
matrix of each sample interval was then obtained by calculating the ratio of these two
grain diameters:
10
60
DD
Um = (11)
The higher the matrix uniformity coefficient (Um), the more poorly sorted the matrix of
the sample is. Values of Um ranged from 2.0 to more than 10 for matrix of samples
analyzed from the BHRS for this study. Table 5 is a summary of average matrix
uniformity coefficient (i.e., sorting) for each lithotype by porosity unit (see Section 5.2).
35
10 1 0.1 0.01Grain Size (mm)
0
10
20
30
40
50
60
70
80
90
100
Wei
ght
Per
cent
Fin
er Um=2.8Um=8.2
Um=13.9
Figure 20. Examples of normalized matrix fractions showing D10 (short dashes) and D60 (long dashes) for calculation of matrix uniformity coefficients, Um.
P-unit 5 P-unit 4 P-unit 3 P-unit 2 P-unit 1 Unit 2&4 Unit 1&3Count 17 7 4 11Average 2.763 2.879 2.926 2.896Variance 0.489 0.500 0.361 0.409
Count 20 23 19 42Average 3.105 3.394 5.449 4.323Variance 0.492 1.691 2.603 3.122
Count 7 24 35 59Average 3.148 4.634 4.896 4.789Variance 0.178 2.203 2.021 2.075
Count 2 56 87 157 64 213 151Average 4.957 7.399 10.189 8.605 7.711 8.288 9.139Variance 0.126 6.579 5.910 4.824 4.712 5.540 6.876
Count 4 119 153 216 100 335 253Average 4.693 7.790 9.412 8.114 7.544 7.999 8.674Variance 1.806 6.342 4.989 3.489 2.979 4.511 5.018
Average Matrix Uniformity Coefficients (Um)
Lar
ge
San
dF
loat
ing
Bim
od
alM
ixed
Table 5. Average matrix uniformity coefficients (Um) for each lithotype by porosity unit (see Section 5.2).
36
>40 20 9.525 4 2 1 0.5 0.25 0.125 0.0625 Porosity SortingAverage 0 0 0 1.45814 4.3506 17.1888 38.8042 29.7029 6.59344 1.90196 0.354 2.690
StDev 0 0 0 2.14377 5.08971 9.22816 9.63026 14.1653 3.924 1.3874Variance 0.011 0.424
Average 3.51138 5.88044 6.59854 6.36683 8.83515 15.3826 25.2582 19.9689 5.96123 2.23675 0.308 4.025StDev 6.25878 5.76952 6.57444 4.74168 5.85425 6.70876 11.1781 12.1302 4.51208 2.44586
Variance 0.008 2.587
Average 12.9054 15.8587 9.35426 7.56886 7.67353 11.0022 16.3919 12.5253 4.69522 2.02455 0.263 4.624StDev 10.2043 8.64611 5.11344 3.39146 3.66627 4.43304 5.67801 5.35311 2.3196 0.82468
Variance 0.003 1.889
Average 19.029 21.2237 13.5308 9.72564 7.9674 7.15183 8.26144 7.46768 3.739 1.9035 0.212 8.485StDev 8.09019 8.02143 4.87852 2.36258 2.13787 2.68758 2.527 2.38761 1.17916 0.64537
Variance 0.002 6.256
Average 46.1909 9.86153 6.49309 6.26494 6.61012 5.95104 6.76639 6.4459 3.52719 1.88892 0.211 8.200StDev 11.1438 6.48361 3.47566 1.86784 1.92915 2.14389 2.38856 2.28065 1.12975 0.61302
Variance 0.002 4.832Lar
ge
(482
)Sa
nd
(29)
Flo
atin
g (7
0)B
imod
al
(61)
Mix
ture
(3
11)
4.8 Average Grain-Size Distributions
After all the sample intervals (i.e., 1013 samples from 12 of 18 wells at the BHRS)
were assigned a code and checked as to their lithotype, they were separated by lithotype
in the Master_data.xls workbook (Table 6 and Appendix 7.7). An average graph for each
lithotype (Figures 13–17) has been generated along with the average porosity and matrix
sorting for each lithotype. The average GSD lithotypes have been generated along with
one (1) standard deviation error values using the following relationships:
n
WPx
n
∑ >
> = 140
40 (12)
( )∑ >> −=n
xxn 1
24040
1σ (13)
Note: These equations and others within this report that apply to individual grain-size classes are shown being applied to the >40 mm size class as an example, but in the actual calculations these equations are used for each size class.
The average porosity and sorting values for each lithotype are reported along with
their variances in Table 6.
Table 6. Average weight percent, porosity and matrix sorting values for each lithotype (from Appendix 7.7).
374.9 Average Continuous Length
The longest analyzed sample length was 1 ft (0.3 m) but some contiguous sample
intervals contained the same lithotypes. The thicknesses of these contiguous intervals
were added together for calculation of average thickness by lithotype. Intervals of no
recovery or slough were examined to see if these intervals “artificially” interrupted a
contiguous interval of the same lithotype on both sides. Intervals of no recovery or
slough greater than 10 cm in thickness were all considered zones of no recovery.
Intervals of no recovery and slough that are less than or equal to 10 cm are examined
more closely. The intervals directly above and below the interval as well as the unit in
question were examined as a set. If the sample intervals above and below the <10 cm-
thick no recovery / slough intervals have been assigned different lithotype codes, the no
recovery / slough intervals were assigned as intervals of no recovery. However, if the
sample intervals above and below the no recovery / slough interval have been assigned
the same lithotype code, then for the purposes of continuous length measurements and
counting transitions (see Section 7), the no recovery / slough interval is re-coded as the
same lithotype thus creating a continuous recovered series of sample intervals for
continuous length measurements. Table 7 is a summary of average continuous thickness
intervals for each lithotype by porosity unit (see Section 5.2).
38
P-unit 5 P-unit 4 P-unit 3 P-unit 2 P-unit 1 Unit 2&4 Unit 1&3Count 11 7 4 11Average 0.251 0.149 0.105 0.133Variance 0.015 0.003 0.001 0.003
Count 14 19 17 36Average 0.229 0.172 0.176 0.174Variance 0.011 0.008 0.011 0.009
Count 6 20 28 48Average 0.165 0.208 0.177 0.190Variance 0.006 0.022 0.012 0.016
Count 2 46 64 109 45 155 109Average 0.137 0.212 0.246 0.262 0.253 0.248 0.249Variance 0.000 0.006 0.016 0.028 0.030 0.022 0.022
Count 4 75 77 132 58 207 135Average 0.150 0.273 0.390 0.300 0.312 0.291 0.357Variance 0.002 0.040 0.161 0.039 0.035 0.039 0.107
Continuous Thickness (m)
Lar
ge
San
dF
loat
ing
Bim
od
alM
ixed
Table 7. Average continuous thickness intervals for each lithotype by porosity unit (see Section 5.2).
39
5 POROSITY
Porosity values for each well were derived from neutron logs that were run in each
well at the BHRS by Century Geophysical Corporation in 1998. The neutron log
recorded readings every 0.1-foot from the bottom of the well to the water table. Porosity
logs were generated from neutron log readings at 0.2-ft intervals using a petrophysical
transform (Hearst and Nelson, 1985; Barrash, Clemo, and Knoll, 1999; Barrash and
Clemo, 2000; 2002). The logs were smoothed using a 5-point moving average. Neutron
tools have a generally shallow depth of influence (Table 8) on the order of 15-25cm (6”-
10”) (Rider, 1996).
Porosity % 90% of signal 0 60 cm 10 34 cm 20 23 cm 30 16.5 cm
Table 8. Depth of investigation of the neutron tools as a function of porosity (from Rider, 1996).
Figure 21 (and Appendix 7.8) show the porosity logs for well C5 at the BHRS. The
porosity log, third log from the left, illustrates the variability of porosity measurements
with depth for this example well. In the fourth log, “4 Component,” the porosity values
or void volume fraction for each interval (see Section 5.1) are integrated with the solid
volume fraction (i.e., cobbles and matrix) to show a representation of the entire interval
as it would have been found undisturbed in nature.
40
Figure 21. Example logs for well C5 at the BHRS. A) A quick reference lithotype log where, in general, the lighter the color the
more matrix material present in the interval. The dark and medium blues represent Large and Mixed Cobble lithotypes. The purple intervals represent the Bimodal lithotype. And the green and yellow intervals represent Floating Cobble and Sand lithotypes. Blank intervals are zones of no recovery or slough.
B) A second type of GSD lithotype log: this is a bar graph log where intervals showing greater cobble dominance lithotypes extend further to the right in the log.
C) Porosity values derived from neutron logs recorded at the BHRS with identification of the different porosity units (see Section 5.2) found in the subsurface at the BHRS.
D) Four component log which shows representative sample volume of intervals by integrating porosity (void volume) with the solid volume fraction (cobbles and matrix).
E) Three component log showing the relative composition of the solid volume fraction of each sample interval.
41
A B C D E
Unit 5
Unit 4
Unit 3
Unit 2
Unit 1
425.1 Assigning Porosity Values
Each sample interval below the water table was assigned a porosity value by taking
the average of all the neutron-derived porosity values that fell within each sample interval
and +0.08 feet of the sample interval’s bounding surfaces. The following Matlab® script
(Figure 22) was used to automate this selection and the averaging process (well A1 at the
BHRS is shown as an example):
load a1_int.txt load a1_pdg.txt a1_pdg(find(a1_pdg==0))=NaN
for i=1:100 por(i)=mean(a1_pdg(find(a1_pdg(:,1)>=a1_int(i)-0.08 & a1_pdg(:,1)<=a1_int(i+1)+0.08),2)) %den(i)=mean(a1_pdg(find(a1_pdg(:,1)>=a1_int(i)-0.08 & a1_pdg(:,1)<=a1_int(i+1)+0.08),3)) %gam(i)=mean(a1_pdg(find(a1_pdg(:,1)>=a1_int(i)-0.08 & a1_pdg(:,1)<=a1_int(i+1)+0.08),4))
end Figure 22. Matlab® script to assign average geophysical log values to sample intervals.
The first line of the program loads a file with a single column, listing the upper
elevation of each sample interval within the well. The second line loads the geophysical
logs (porosity, density and / or gamma) to be averaged over the sample intervals. The
third line finds values of zero in the geophysical log files and assigns them Not-A-
Number (NaN) values for the output file. The fourth line was changed for each well; it is
set to repeat the loop for the number of sample intervals within a well.
The three lines of the script within the loop average the geophysical values over each
sample interval thickness +0.08 feet for each of the three geophysical logs: porosity,
density, and natural gamma. The last line of the script ends the loop and the script. The
calculated average porosity (or other geophysical log) value for each sample interval is
then recorded in the master data sheet for each well.
435.2 Porosity Units
The neutron-derived porosity logs at the BHRS show five hydrostratigraphic units
between the water table and the basal clay that can be traced across the central well area
(inset in Figure 1) and some of the X-wells (Barrash and Clemo, 2000; 2002 and Figure
23). These subsurface units are also consistent with GPR reflection profiles (Peretti et
al., 1999) and GPR and seismic crosshole tomography (Peterson, Majer, and Knoll, 1999;
Liberty, Clement, and Knoll, 2000; Clement and Knoll, 2000). Four of these units are
cobble-dominated deposits and can be traced across the central portion of the site. The
fifth unit is a channel sand that is continuous in the western part of the site and that
pinches out from the river to the central portion of the wellfield. The channel sand and
cross-beds within the sand deposits can be distinguished in the GPR reflection profiles.
Also it should be noted that coarse fluvial sediments occur between Unit 1 and the basal
clay in at least two of the X wells.
Unit Average Variance Data Points Unit 5 0.408 0.0045 132 Unit 4 0.226 0.0023 747 Unit 3 0.180 0.0010 708 Unit 2 0.246 0.0013 1059 Unit 1 0.177 0.0005 536
Table 9. Porosity statistics for the porosity units. Using the porosity values for 12 of the wells at the BHRS provides a data set of 3182
measurements at 6-cm intervals. Table 9 provides the porosity statistics, and the
similarities and differences between the porosity units become apparent (Figure 24A-F).
Porosity Units 1 and 3 have similar means, variances, and vertical geostatistics (Barrash
and Clemo, 2002) and are considered to be similar, if not the same type of,
hydrostratigraphic units based on the trends and statistics seen within porosity logs.
45
0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50Porosity
0
2
4
6
8
10
12
14
Nor
mal
ized
Fre
quen
cy
0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50Porosity
0
2
4
6
8
10
12
14
Nor
mal
ized
Fre
quen
cy
Unit 1
Unit 2
Figure 24. Normalized histograms of the neutron derived porosity values within each PorosityUnit. The solid line superimposed over each histogram is a normal distribution using the samestatistics. A) Unit 1. B) Unit 2. C) Unit 3. D) Unit 4 E) Unit 5 F) A comparison of units withthe statistics is shown in Table 9.
A
B
46
0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50Porosity
0
2
4
6
8
10
12
14
Nor
mal
ized
Fre
quen
cy
0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50Porosity
0
2
4
6
8
10
12
14
Nor
mal
ized
Fre
quen
cy
Unit 3
Unit 4
Figure 24. Normalized histograms of the neutron derived porosity values within each PorosityUnit. The solid line superimposed over each histogram is a normal distribution using the samestatistics. A) Unit 1. B) Unit 2. C) Unit 3. D) Unit 4. E) Unit 5. F) A comparison of units with the statistics is shown in Table 9.
C
D
47
0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50Porosity
0
2
4
6
8
10
12
14
Nor
mal
ized
Fre
quen
cy
0.10 0.15 0.20 0.25 0.30 0.35 0.40 0.45 0.50Porosity
0
2
4
6
8
10
12
14
Nor
mal
ized
Fre
quen
cy
Unit 5
Figure 24. Normalized histograms of the neutron derived porosity values within each PorosityUnit. The solid line superimposed over each histogram is a normal distribution using the samestatistics. A) Unit 1. B) Unit 2. C) Unit 3. D) Unit 4. E) Unit 5. F) A comparison of units with the statistics is shown in Table 9.
UNIT 1Avg.=0.177Var.=0.0005
UNIT 3Avg.=0.180Var.=0.0010
UNIT 2Avg.=0.246Var.=0.0013
UNIT 4Avg.=0.226Var.=0.0023
UNIT 5Avg.=0.408Var.=0.0045
E
F
48 Units 2 and 4, also have similar porosity statistics and may be similar hydrostratigraphic
units although they have dissimilar vertical geostatistics (Barrash and Clemo, 2002).
Unit 5 is known from the core to be sand and also has statistical characteristics,
based on the porosity logs, that are unique among the five units. Table 10 gives the
elevations used as the basal contacts for each of the porosity units at the BHRS. Table 11
is a summary of average porosity values for each lithotype by porosity unit.
Elevation in meters of basal contacts of Porosity Units Well Water Table Unit 5 Unit 4 Unit 3 Unit 2 Unit 1
A1 847.691 847.082 842.937 840.071 833.975 831.079 B1 847.487 N/A 843.799 841.178 834.533 831.148 B2 847.710 N/A 843.605 840.861 833.790 831.960 B3 847.701 N/A 841.635 838.709 834.625 831.119 B4 847.438 846.555 841.983 838.325 834.972 831.466 B5 847.487 846.238 843.738 838.679 834.167 831.151 B6 847.528 846.765 842.070 840.120 834.024 831.373 C1 847.393 N/A 843.827 838.035 833.829 831.696 C2 847.507 N/A 842.539 838.393 834.126 831.464 C3 847.356 847.082 843.973 840.315 834.280 831.628 C4 847.705 845.846 843.956 841.213 834.324 831.855 C5 847.328 845.591 843.702 840.532 832.729 831.112 C6 847.417 846.472 842.083 839.462 834.646 831.019 X4 846.829 845.518 843.507 838.752 832.168 830.278 X5 847.658 844.870 843.590 840.420 832.800 830.484 Table 10. Elevations used for the basal contact picks for each porosity unit. Note
absence of Unit 5 in four wells on the eastern side of the BHRS.
49
P-unit 5 P-unit 4 P-unit 3 P-unit 2 P-unit 1 Unit 2&4 Unit 1&3Count 17 7 4 11Average 0.435492 0.2679323 0.2659583 0.2672145Variance 0.0035673 0.0037318 0.0016883 0.0027465
Count 19 21 19 40Average 0.4224767 0.268222 0.2507909 0.2599422Variance 0.0018416 0.0024978 0.0015737 0.002085
Count 5 25 35 60Average 0.3936878 0.2444655 0.2588147 0.2528358Variance 0.0060734 0.0008916 0.0010821 0.0010372
Count 2 56 91 160 66 216 157Average 0.3421667 0.2179958 0.175052 0.2391932 0.1851724 0.2336976 0.1793065Variance 0.0008134 0.0015391 0.0004687 0.0011921 0.0002588 0.001362 0.0004034
Count 3 124 164 227 100 351 264Average 0.3283056 0.2217828 0.1759123 0.2380256 0.181943 0.2322874 0.1781967Variance 0.0106586 0.0023655 0.0004534 0.0014365 0.0004218 0.0018193 0.0004484
Average Porosity
Lar
ge
San
dF
loat
ing
Bim
od
alM
ixed
Table 11. Average porosity values for each lithotype by porosity unit.
50
6 REFERENCES CITED
American Society for Testing and Materials (ASTM), 1996, Annual Book of ASTM Standards: Conshohocken, PA, ASTM, Section 4, v. 4.08 Soil and Rock (I): D420-D4914.
Barrash, W. and Clemo, T., 2000, Hierarchical geostatistics of porosity derived from
neutron logs at the Boise Hydrogeophysical Research Site, Boise Idaho: Proceedings of TraM’2000, Liege, Belgium, IAHS Publication No. 262, p. 333-338.
Barrash, W. and Clemo, T., 2002, Hierarchical geostatistics and multifacies systems:
Boise Hydrogeophysical Research Site, Boise, Idaho, Water Resources Research, v. 38, no. 10, 1196, doi:10.1029/2001WR001259, 2002.
Barrash, W. and Knoll, M. D., 1998, Design of research wellfield for calibrating
geophysical methods against hydrologic parameters: Proceedings of the 1998 Conference on Hazardous Waste Research, May 18-21, 1998, Snowbird, UT, Great Plains/Rocky Mountains Hazardous Substance Research Center, Kansas State University, p. 296-318.
Barrash, W., Clemo, T., and Knoll, M. D., 1999, Boise Hydrogeophysical Research Site
(BHRS): Objectives, design, initial geostatistical results: Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, March 14-18, 1999, Oakland, CA, p.389-398.
Barrash, W., Morin, R., and Gallegos, D. M., 1997, Lithologic, hydrologic and
petrophysical characterization of a coarse-grained, unconsolidated aquifer, Capital Station site, Boise, Idaho: 32nd Symposium on Engineering Geology and Geotechnical Engineering, March 26-28, 1997, Boise, ID, p. 307-323.
Boggs, S., 1995, Principles of sedimentology and stratigraphy, 2nd ed., New Jersey,
Prentice-Hall, 774p. Carling, P. A. and Reader, N. A., 1982, Structure, composition and bulk properties of
upland stream gravels: Earth Surface Processes and Landforms, v. 7, p. 349-365. Church, M. A., McLean, D. G., and Wolcott, J. F., 1987, River bed gravels: Sampling
and analysis, Chapter 3 in Thorne, C. R., Bathurst, J. C., and Hey, R. D., eds., Sediment transport in gravel-bed rivers: John Wiley & Sons, p. 43-88.
51 Clarke, R. H., 1979, Reservior properties of conglomerates and conglomeratic
sandstones: The American Association of Petroleum Geologists Bulletin, v. 63, no. 5, p. 799-809.
Clement, W. P., and Knoll, M. D., 2000, Tomographic inversion of crosshole radar data:
Confidence in results: Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, February 20-24, 2000, Arlington, VA, p. 553-562.
Fetter, C. W., 1994, Applied Hydrogeology, 3rd ed.: New York, McMillan College
Publishing, 691 p. Hearst, J. R. and Nelson, P. H., 1985, Well logging for physical properties: New York,
McGraw-Hill, 571 p. Heinz, J., 2001, Sedimentary geology of glacial and periglacial gravel bodies (SW-
Germany): Dynamic stratigraphy and aquifer-sedimentology: PhD Dissertation, Tübingen, Germany, Universität Tübingen.
Liberty, L. M., Clement, W. P., and Knoll, M. D., 2000, Crosswell seismic reflection
imaging of a shallow cobble-and-sand aquifer: An example from the Boise Hydrogeophysical Research Site: Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, February 20-24, 2000, Arlington, VA, p. 545-552.
Lord, M. L. and Kehew, A. E., 1987, Sedimentology and paleohydrology of glacial-lake
outburst deposits in southeastern Saskatchewan and northwestern North Dakota: Geological Society of America Bulletin, v. 99, p. 663-673.
Medley, E. M., 1994, The engineering characterization of mélanges and similar block-in-
matrix rocks: PhD Dissertation, Berkeley, CA, University of California at Berkeley.
Michaels, P., 1997, Standard Test Methods for Particle-Size Analysis of Soils: CX361
Engineering Properties of Soils Lab, Boise State University. Paola, C. and Seal, R., 1995, Grain size patchiness as a cause of selective deposition and
downstream fining: Water Resources Research, v. 31, no. 5, p. 1395-1407. Peretti, W. R., Knoll, M. D., Clement, W. P., and Barrash, W., 1999, 3-D GPR imaging
of complex fluvial stratigraphy at the Boise Hydrogeophysical Research Site: Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, March 14-18, 1999, Oakland, CA, p. 555-564.
52 Peterson, J. E., Jr., Majer, E. L., and Knoll, M. D., 1999, Hydrogeological property
estimation using tomographic data at the Boise Hydrogeophysical Research Site: Proceedings of the Symposium on the Application of Geophysics to Engineering and Environmental Problems, March 14-18, 1999, Oakland, CA, p. 629-638.
Reboulet, E. C., 2003, Quantitative analysis of unconsolidated coarse fluvial sediments
from the Boise Hydrogeophysical Research Site: Statistical analysis of core and porosity data (M.S. Thesis): Boise, ID, Boise State University, 150 p.
Rider, M., 1996, The geological interpretation of well logs, 2nd ed.: Caithness, Whittles
Publishing, 280 p. Shih, S. M. and Komar, P. D., 1990a, Hydraulic controls of grain-size distributions of
bedload gravels in Oak Creek, Oregon, USA: Sedimentology, v. 37, p. 367-376. Smith, G. A., 1986, Coarse-grained nonmarine volcaniclastic sediment: Terminology and
depositional process: Geological Society of America Bulletin, v. 97, p. 1-10. Todd, S. P., 1989, Steam-driven, high-density gravelly traction carpets: Possible deposits
in the Trabeg Conglomerate Formation, SW Ireland and some theoretical considerations of their origin: Sedimentology, v. 36, p. 513-530.
Underwood, E. E., 1970, Quantitative Stereology: Reading, MA, Addison-Wesley
Publishing Company, 255 p. Weissmann, G. S., Carle, S. F., and Fogg, G. E., 1999, Three-dimensional hydrofacies
modeling based on soil surveys and transition probability geostatistics: Water Resources Research, v. 35, no. 6, p. 1761-1770.
Weissmann, G. S., and Fogg, G. E., 1999, Multi-scale alluvial fan heterogeneity modeled
with transition probability geostatistics in a sequence stratigraphic framework: Journal of Hydrology, 226, no. 1-2 (1999): p. 48-65.
53
7 APPENDICES - **FOR INTERNAL COPIES ONLY**
54
Appendix 7.1** Drilling Logs
BSU_CGISS_03-02_Disk-1 A7.1-Drilling_Logs
A1_DL.pdf B1_DL.pdf B2_DL.pdf B3_DL.pdf B4_DL.pdf B5_DL.pdf B6_DL.pdf C1_DL.pdf C2_DL.pdf C3_DL.pdf C4_DL.pdf C5_DL.pdf C6_DL.pdf X1_DL.pdf X2_DL.pdf X3_DL.pdf X4_DL.pdf X5_DL.pdf
55
Appendix 7.2 **Core Photographs
BSU_CGISS_03-02_Disk-1 A7.2-Core_Photos
A1_Photos A1_00-08.tif A1_08-16.tif A1_16-24.tif A1_24-32.tif A1_32-40.tif A1_40-48.tif A1_48-56.tif A1_56-64.tif
B1_Photos B2_Photos B3_Photos B4_Photos B5_Photos B6_Photos C1_Photos C2_Photos C3_Photos C4_Photos C5_Photos C6_Photos X1_Photos X2_Photos X3_Photos X4_Photos X5_Photos
Example of Files Included
56
Appendix 7.3 **Core and Cobble Analysis Sheets
BSU_CGISS_03-02_Disk-1 A7.3-Core-Cobble_Analysis
A1_CCA.pdf B1_CCA.pdf B2_CCA.pdf B3_CCA.pdf B4_CCA.pdf B5_CCA.pdf B6_CCA.pdf C1_CCA.pdf C2_CCA.pdf C3_CCA.pdf C4_CCA.pdf C5_CCA.pdf C6_CCA.pdf X1_CCA.pdf X2_CCA.pdf X3_CCA.pdf X4_CCA.pdf X5_CCA.pdf
57
Appendix 7.4 **Grain-Size Analysis Data Sheets
BSU_CGISS_03-02_Disk-1 A7.4-G-S_Analysis
A1_GSA A1_Box1&2.pdf A1_Box3&4.pdf A1_Box5&6.pdf A1_Box7&8.pdf
B1_GSA B2_GSA B3_GSA B4_GSA B5_GSA B6_GSA C1_GSA C2_GSA C3_GSA C4_GSA C5_GSA C6_GSA X1_GSA X2_GSA X4_GSA X5_GSA
Example of Files Included
58
Appendix 7.5 Modified CX361 Engineering Properties of Soils Lab
This is the procedure used to sample and test the matrix material of each sample. The details of the cobble and matrix analyses and how they are fitted together in the sample analysis can be found in Sections 4 to 4.4.
Copyright © 1997 P. Michaels
Re-printed with permission Title: Standard Test Methods for Particle-Size Analysis of Soils Reference: ASTM D-422-63 and ASTM D-421-85 (Dry Preparation for Particle-Size
Analysis) in American Society for Testing and Materials, 1996, “Annual Book of ASTM Standards”, Section 4, Construction, Vol. 4.08 Soil and Rock (I): D420-D4914. Published by: ASTM, 100 Barr Harbor Drive, West Conshohocken, PA 19428, (610) 832-9500.
Requirements:
1. Prepare sample of matrix material for particle-size analysis (ASTM D-421).
2. Conduct Sieve and Hydrometer Analysis on prepared sample (ASTM D-422).
Introduction: The number 18 sieve was used to partition the matrix sample into two portions:
1. Retained no. 18 è Coarse grains, sieve analysis. 2. Passed no. 18 è Finer grains, hydrometer + additional sieve analysis.
This was a rather complicated lab, and will require corrections which include: 1. Composite hydrometer corrections. 2. Hygroscopic moisture corrections. 3. Temperature / Viscosity variation corrections.
Soil Sample Size: The portion of the sample interval used in the analysis process was approximately 150g of matrix material. Materials Needed:
1. Complete set of sieves. 2. Thermometer. 3. Balance. 4. Hydrometer. 5. Oven for drying. 6. Sample splitter, mortar, pestle, paper cups, malt mixer, dispersing agent,
deionized water.
59Protocol:
Sample Preparation (ASTM D421) 1. Measure and record the mass of the matrix fraction, MFINES, of the sample interval.
Total mass of matrix fraction of the sample interval, MFINES=MC+SS-MC
MC+SS=mass container + sample split, MC=mass container _________g mass of matrix fraction + container _________g mass of container
2. Use the sample splitter to extract a sample for this grain size testing. The portion of the matrix sample was to be approximately 150 grams or half of the matrix sample interval, whichever was less.
3. Measure and record the mass of the air dried sample from the splitter. Original sample split mass, uncorrected for hygroscopic moisture, MORG=MC+SS-MC
_________g mass sample split + container _________g mass of container
4. First air dry sieving: Stack a no. 18 sieve (1.0 mm) and a pan. Place the sample in the no. 18 sieve and shake for 1 minute in the roto-tap. Set the pan and its contents aside for a moment.
5. Mechanical grinding: Take the material in the no. 18 sieve and place it in a clean mortar. Using a pestle, grind the sample to break any fines free from the larger grains.
6. Second air dry sieving: Re-assemble the no. 18 sieve and the pan with the original fines from step (4) above. Place the ground sample from the mortar into the no. 18 sieve and shake for 1 minute. Save the pan contents in a container for later use in the hydrometer test.
7. Wet wash sieving: Take the no. 18 sieve and its contents to the sink. Wash the sample in the sieve until clean.
8. Dry coarse material: Take the washed sample and dry it in the oven. Spread it out on a paper plate and use the microwave on half power. Heat the material, let cool and then measure the mass. Each time a sample is weighed a plate that hasn’t been in the microwave or a paper cup should be used. Repeat this process until the mass of the cooled sample was stable on successive dryings.
9. Measure mass of oven dried coarse material: Place the dried sample on the balance. Total retained on the number 18 sieve (coarse grained, wash and dried), MTR18
_________g mass sample + container _________g mass of container
Coarse Sieving Step (ASTM D422) 10. Coarse Sieving Stack: Stack the following sieves together (large on top, pan on
bottom). Place the material from the balance, from step 9, on the top sieve and shake for 3 minutes.
Sieve Size Mass Retained Symbol No. 5 MR5
No. 10 MR10 No. 18 MR18
Pan Pan
6011. Measure masses in each sieve: Take the contents in each sieve and record the mass
in the chart above, step (10). 12. Quality Check 1: Sum the masses in the chart. The total should equal MTR18. Record
your total below. Total mass retained on no. 18 or larger after sieving; MTR18AS. _________g MTR18AS
Hydrometer (Sedimentation) Test
(ASTM D422) 13. Prepare dispersing solution: Prepare a solution of sodium hexametaphosphate; this
was a soap solution designed to keep the soil particles from clumping together. Each batch was made by dissolving 40 g of crystals per liter of deionized water.
14. Prepare calibration chart, Composite Hydrometer Corrections: A chart must be prepared to correct for the following three effects:
a. Density of dispersion solution greater than pure water. b. Hydrometers are calibrated for 68OF (20OC) only. c. Meniscus was not visible in the samples due to cloudy water. The
hydrometers are designed to be read at the bottom of the meniscus, but this will not be visible. All of readings including the correction readings will have to be taken at the top of the meniscus.
15. Prepare a calibration standard: A two-point calibration curve must be produced for each batch of standard dispersing solution made.
a. Warm about 900 ml of water in the microwave oven. Heat the water to about 30OC.
b. In a sedimentation cylinder, combine 125 ml of the dispersing solution (as per step 13 above) with enough warmed deionized water to bring the total mixture to 1000 ml.
c. Place the hydrometer in the cylinder and wait about 30 seconds for the temperature to stabilize. Then read the hydrometer at the top of the meniscus formed on the stem. Measure the temperature of the solution. Calculate the composite correction and record both the correction and the temperature in the table below. (Note: Correction will be subtracted from the readings.)
151H Hydrometer: Correction = (Reading – 1.00) Repeat step c) above once the calibration standard solution mixture reaches room temperature.
Temperature Correction
Linear interpolation can then be used to make a correction chart for different temperatures between the warm and cold values above.
16. Determine Hygroscopic Moisture: Take about 10 g or 10% , whichever is less, of the material form the sample saved in step (6) above (passing no. 18) and place it on a small plate. This was the air dry soil.
a. Record the mass of the air dry sample. Mass of air dried sample, MAD, MC+S=mass container + sample MC=__________g MC+S=__________g MAD=_______________g
61b. Place this sample in the oven and dry it using the same process described in
step (8) above. c. Record the mass of the oven dried sample below. Mass of oven dried sample, MOD MC=__________g MC+S=__________g MOD=_______________g d. Compute the hygroscopic moisture correction factor. The hygroscopic
moisture correction factor: HMCF = MOD / MAD HMCF=______________unitless
17. Prepare sedimentation sample: Take about 100 g (usually the entire remaining sample) from the soil sample saved in step (6) above (passing no. 18). Record the mass below. Mass of hydrometer sample, air dried, MHSAD
MC=__________g MC+S=__________g MHSAD=_______________g a. Place the sample in a 250 ml beaker. b. Add 125 ml of dispersing solution, step (13), to the beaker and mix with the
soil. c. Let soak for 16 hours. d. Transfer the mixture to a malt mixer cup. e. Rinse out the beaker with deionized water, pouring the rinse into the malt
mixer cup. f. Add deionized water to bring the malt mixer cup to half full. g. Stir in the malt mixer for 1 minute.
18. Sedimentation cylinder shake: a. Transfer the solution from the malt mixer cup immediately to a 1000 ml
sedimentation cylinder. b. Rinse out the mixer cup with a spray bottle, transferring all of the sediment to
the sedimentation cylinder. c. Add deionized water to bring the level to 1000 ml. d. Place plastic wrap over the cylinder, and then your hand over the top to seal
the cylinder. e. Agitate by turning the cylinder upside down and the upside right. Take about
two seconds per inversion and upright cycle. Do this for a minute. If material was stuck on the bottom of the cylinder, shake it in the inverted position to free up the mixture and continue mixing.
19. Take hydrometer readings: Note: insert the hydrometer about 25 seconds before each scheduled reading time to let it stabilize. Take a reading, record it, and then remove the hydrometer from the cylinder. Be sure to take readings at the top of the meniscus and record the temperature of the sample after each reading.
62READING SCHEDULE
Time (minutes)
Reading RT
Temperature (oC)
Composite Correction
Corrected Reading,
Gmix 0 2 5
15 30 60 250 1440
20. Wash after last reading: After the last hydrometer reading, pour the cylinder contents through a no. 270 sieve (0.053 mm). Rinse the sample with tap water through the sieve.
21. Dry the no. 270 sieve contents: Place the washed contents of the no. 270 sieve on a paper plate and dry using the same procedure as in steps (8) and (16b).
22. Fine Sieving Stack: Stack the following sieves together (large on top, pan on bottom). Place the washed and dried hydrometer material in the top sieve and shake for three minutes.
Sieve Size Mass Retained Symbol No. 35 MR35 No. 60 MR60
No. 120 MR120 No. 230 MR230
Pan Pan 23. Measure mass in each sieve: Take the contents in each sieve and record the mass in
the chart above, step (22). Calculations
24. Compute Mass Passing no. 18 Sieve: From step (3) obtain the recorded value for the Original Sample Split Mass, MORG. From step (9), obtain the recorded value for Total Retained on no. 18 Sieve, MTR18. This was not the value retained in the coarse sieve stack, but the value for the total, full range of matrix sizes greater than no. 18. Mass Passing no. 18, MP18:
MP18 = (MORG – MTR18) = _______________g 25. Compute Representative Mass Retained in Each Cobble Class: The mass recorded on
the cobble analysis sheets for cobble size class must be converted to a representative mass by multiplying each class’s weight by the ratio of the mass of the sample split, step (2) MORG, to the mass of the entire matrix fraction, step (1) MFINES. For example,
MR>40 = M>40*[MORG/MFINES]
6326. Compute Mass Retained in Each Coarse Sieve: Obtain each sieve mass for steps
(10) and (11). Enter the value for MP18, step (24) above, in the table below step (27) for the mass passing no. 18. Then, to get all the other mass-passing values, accumulate a sum from MP18. For example, for MP5 (mass passing no. 5 sieve),
MP5 = MP18 + MR18 + MR10 where MP18 was from step (24) above, and MR18 and MR10 are from the table under step (10).
27. Compute Percent Finer for Each Sieve and Cobble Diameter: Once step (26) was done, the percent finer was computed by dividing each mass-passing-finer value by MORG and multiplying by 100%. For example, for Percent Passing no.4, %P4:
%100*% 44
=
ORGMMP
P
Sieve
Number Diameter
(mm) Mass Retained
[from steps (10) & (25)] Mass Passing
[from step (26)] % Finer
[from step (27)] >2*3/4” >38.100
¾” 19.050 3/8” 9.525
No.5 4.000 No.10 2.000 No.18 1.000 MP18= %P18=
28. Calculate the oven dried mass of the hydrometer sample: Since the hydrometer
sample mass, step (17), was determined for an air dried sample, you must multiply by the step (16d) factor to obtain the equivalent oven dried mass. Oven dried equivalent mass, MHSOD
MHSOD=MHSAD*HMCF=_______________g 29. Calculate the mass of the total sample represented by the mass of sample actually
used in the hydrometer analysis. If the sieve and hydrometer curves are to blend together, the actual mass computed in step (28) must be scaled to the equivalent mass of the original sieve analysis. This represented mass was W in the standard.
%100*% 18
=
PM
W HSOD
where MHSOD was from step (28) and %P18 was from step (27) calculation, last row and column of table under step (27). Represented mass, W; W=_____________g
6430. Calculate the represented percent of sample in suspension: This was the percent
passing value, %P, needed which corresponds to a hydrometer reading of the soil mixture specific gravity, GMIX. For the hydrometer used, 151H, the formula is
( ) ( )0.1*0.1
*000,100
% −
−
= MIXS
S GG
GW
P
where the 100,000 was the product of the cylinder mixture volume (1000 ml), the unit mass of water (1g/cm3), and 100%. GS was the specific gravity assumed for the sample grains (2.65g/cm3), GMIX was the hydrometer reading taken from the last column in the table under step (19). It takes into account dispersing agent, meniscus, and temperature effects. Compute %P, percent finer, for each reading taken and record the value on the table below step (31).
31. Calculate the diameter of the soil particle for each reading: This involves using Table A and Effective Depth Equation. The effective depth equation gives the depth, L, that the hydrometer reading was referenced to. Table A gives the constant, K, for the diameter equation. That is,
tL
KD *=
where D was the particle diameter (mm), t was the sample reading time (minutes), L was the depth (cm) from the effective depth equation, and K was the constant from Table A.
Temperature OC
K for 2.65g/cm3 grains
16 0.01435 17 0.01417 18 0.01399 19 0.01382 20 0.01365 21 0.01348 22 0.01332 23 0.01317 24 0.01301 25 0.01286 26 0.01272 27 0.01258 28 0.01244 29 0.01230 30 0.01217
Table A. Effective Depth Equation:
85.28055.264 +∗−= TRL
65
(31 cont.) Hydrometer Portion of the Grain Size Distribution Time (min)
Corrected GMIX [table step (19)]
Temperature [table step (19)]
%P (%finer) step (30)
D (mm) step (31)
0 2 5 15 30 60
250 1440
32. Compute %Passing for finer than no. 18 sieving: This was the sieve analysis for the
granular material recovered from the sedimentation tube in steps (20, 21, and 22). a. Compute mass fraction that would have been retained on the no. 18 sieve, had
it not been removed, MXR18. [ ]
%100*)(%%100 18
18
WPM XR
−= MXR18=__________g
where %P18 was from the table under step (27) and W was the mass computed in step (29).
b. Compute total mass passing the no. 230 sieve, MP230. Add all the mass fractions retained on each sieve of the table of step (22). Add to that sum MXR10 above. Finally, subtract this total sum from W of step (29). This was the mass passing no. 230, MP230.
c. Compute the other mass passing for the larger sieve sizes above the no. 230 using the same method as in step (26).
d. Compute the percent finer passing values by dividing the mass passing values of step (32c) above by the value W computed in step (29) and then multiplying by 100%.
Sieve Size D (mm) Mass Passing
[from step (32b,c)] % finer
[from (32d)] No. 35 0.5000 No. 60 0.2500 No. 120 0.1250 No. 230 0.0625 MP200= %P200=
33. Graph the Grain-Size Distributions: Combine results from the tables in steps (27),
(31), and (32) in a single plot. a. The first plot was a graph of grain size (mm) vs. percent finer on semi-log
paper. b. The second plot was a histogram of the weight percent retained on each sieve
size. c. The third plot was a graph of grain size (phi) vs. cumulative weight percent.
66
Appendix 7.6 ** Grain-Size Analysis Data Sheets From Outcrops and Quarries
BSU_CGISS_03-02_Disk-1 A7.6-G-S_Analysis_Outcrop-Quarry
Quarry_Outcrop.pdf
67
Appendix 7.7 **Well Master Data Sheets
BSU_CGISS_03-02_Disk-1 A7.7-Master_Data_Sheets
A1_master_data.xls B1_master_data.xls B2_master_data.xls B3_master_data.xls B4_master_data.xls B5_master_data.xls B6_master_data.xls C1_master_data.xls C2_master_data.xls C3_master_data.xls C4_master_data.xls C5_master_data.xls C6_master_data.xls X1_master_data.xls X2_master_data.xls X4_master_data.xls X5_master_data.xls Master_data.xls
68
Appendix 7.8 **GSD Type Logs and Porosity Logs
69
Unit 5
Unit 4
Unit 3
Unit 2
Unit 1
70
Unit 1
Unit 4
Unit 2
Unit 3
71
Unit 4
Unit 3
Unit 2
Unit 1
72
Unit 4
Unit 2
Unit 3
Unit 1
73
Unit 5
Unit 4
Unit 3
Unit 2
Unit 1
74
Unit 5
Unit 4
Unit 3
Unit 1
Unit 2
75
Unit 5
Unit 3
Unit 4
Unit 2
Unit 1
76
Unit 4
Unit 3
Unit 2
Unit 1
77
Unit 4
Unit 2
Unit 3
Unit 1
78
Unit 4
Unit 5
Unit 3
Unit 2
Unit 1
79
Unit 5
Unit 4
Unit 3
Unit 2
Unit 1
80
Unit 3
Unit 4
Unit 5
Unit 2
Unit 1
81
Unit 3
Unit 5
Unit 4
Unit 1
Unit 2
82
83
84
Unit 2
Unit 5
Unit 4
Unit 3
Unit 1
Unit 0
85
Unit 0
Unit 1
Unit 2
Unit 3
Unit 4
Unit 5
86Appendix 7.9 Gamma-Spectrometry Analysis Worksheets
Further analysis on the matrix portion of the sample intervals within porosity Units 2
and 3 have been conducted. This analysis requires an 80 g sample material in the 0.25
mm and 1.0 mm size range. All of the recovered intervals of the wells used in this
analysis had to be checked as to the quantity of the sample that could be found between
0.25 and 1.0 mm. All of the information used to prepare the listing for this analysis was
taken from individual core data sheets for each individual well.
In order to produce the Gamma-Spec analysis worksheet (attachment) for a particular
well, the sample interval data sheets must be examined one-by-one. From each sample
interval worksheet the sample interval location data were copied onto a new worksheet.
The original mass of the matrix fraction, MFINES, and the sample mass used in the grain-
size analysis, MORG, are copied to the Gamma-Spec worksheet. The calculated values
for the masses retained on the #35 sieve (MR35), 0.50 to 1.00 mm, and the #60 sieve
(MR60), 0.25 to 0.50 mm, are copied from the final table on the GSA worksheet.
The mass of the matrix fraction remaining, MRFINES, for the sample interval after the
grain-size analysis was completed was calculated.
ORGFINESFINES MMMR −=
The mass retained on the #35 and #60 sieves was recalculated as a percentage of the
sample mass used in the analysis.
%1003535 ×=
ORGMMR
PR
The mass of the archived sample between 0.25 and 1.0 mm was calculated by
applying the sum of the calculated percent retained on the two sieves to the matrix
87fraction remaining. The calculated amount remaining was compared to the volume
needed for sample preparation for gamma-spectrometry analysis. The sample intervals
which have sufficient material remaining for gamma-spectrometry analysis are
highlighted on the worksheet for further consideration.