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Qualifying Frac Sand
Resources Using Cutting
Edge Technology
Sample prep & handling
Data correlation
PSD as decision tool
PSD for “fingerprinting”
Conclusions
 Camsizer
 Quick
 Reliable
 21st Century upgrade for PSD and more
 Sample Handling Key to Reproducible Results
 Natural variability on material is different that
manufactured product
 Use statistics & trend charts for big data sets vs.
time
Prospecting
ISO 13503-2/API 19/56
*Gert Beckmann
Retsch Technology
{
“representative sample….”
• Analyzing Representative Samples
• Standardizing Testing …..
Methods
Techniques
Equipment
• Quality Assurance/Quality Control -
QA/QC
 NEVER scoop always use sample splitter
 No mechanical agitation like RoTap
 Clusters and “coating” source for
discrepancy
 Smaller sample size – unforgiving!!
Camsizer vs. Rotap
learnings
Sample prep
Air dry
Split & weigh
Wash, wet sieve – P200
Dry and calculate %loss
Micro photograph
Archive sample
{
Gradation Analysis
Proving the “method…”
• Creating a “standard” sample
• Splitting “standard” sample – maintain
representative
• Confirm to “ISO equivalence”
• Establish statistically significant like
vs. different
Split sample into 5 parts. 4 splits used for ro-tap. 1 split used exclusively for
CAMSIZER
Run 3 of 4 samples in the ro-tap individually - once (saved 2, 3 and 4 to run through the
CAMSIZER)
Run 4th sample three times through ro-tap
Split the one sample used for the CAMSIZER into 4 smaller
parts
Run 3 of 4 samples through the CAMSIZER
once
Run the 4th sample through the CAMSIZER three
times
Run sample 2, 3, and 4 from the ro-tap through the
CAMSIZER
Same split sample using sieves
Same sample 3x Rotap
Same sample 3x Camsizer
All sets of Rotap data
All Sets of Camsizer data
Average of all
Camsizer - Blue
Rotap - Red
Round/Sphericity….Proving
the “method…”
Roundness/Sphericity
Site 1 Site 2 Site 3 Site 4
Sieve Size (US
Standard)
% Retained Roundness Sphericity % Retained Roundness Sphericity % Retained Roundness Sphericity % Retained Roundness Sphericity
#16 0.1
0.92 0.96 0.4 0.91 0.87 0.3 0.91 0.87 0.6 0.67 0.86
#18 0.1
0.83 0.88 0.4 0.87 0.90 0.7 0.87 0.90 1.1 0.84 0.88
#20 0.8
0.75 0.85 1.1 0.83 0.87 1.5 0.83 0.87 1.7 0.85 0.85
#25 2.2
0.77 0.81 3.5 0.77 0.83 4.1 0.77 0.83 4.1 0.82 0.83
#30 6.6
0.78 0.83 5.2 0.82 0.83 7.2 0.82 0.83 6.3 0.80 0.78
#35 14.6
0.76 0.78 9.1 0.79 0.78 11.5 0.79 0.78 8.8 0.78 0.76
#40 17.6
0.73 0.77 10.2 0.79 0.77 12.7 0.79 0.77 9.7 0.76 0.76
#45 22.9
0.74 0.75 12.9 0.76 0.76 14.2 0.76 0.76 11.6 0.72 0.75
#50 20.0
0.70 0.72 10.2 0.72 0.73 11.4 0.72 0.73 10.2 0.68 0.73
#60 10.3
0.65 0.71 8.2 0.67 0.72 9.6 0.67 0.72 10.2 0.65 0.72
#70 2.2
0.61 0.70 5.3 0.63 0.70 5.7 0.63 0.70 7.2 0.62 0.71
#100 0.8
0.34 0.63 7.9 0.23 0.49 6.4 0.23 0.49 9.3 0.49 0.61
#200 0.4
0.19 0.54 16.5 0.22 0.43 8.1 0.22 0.43 11.3 0.24 0.38
PAN 1.5
9.2 6.6 8.0
20/40 41.0 0.7595 0.797 28.0 0.79275 0.79925 35.6 0.79275 0.79925 28.9 0.79175 0.784
30/50 75.1 0.7 0.8 42.4 0.8 0.8 49.8 0.8 0.8 40.3 0.7 0.8
40/70 55.3 0.7 0.7 36.6 0.7 0.7 40.9 0.7 0.7 39.2 0.7 0.7
4 sites
GradStat8
GradStat8
GradStat8 –cont.
Planning
{
{
{
ArcGIS – Raster block allows x,y,z arithmetic
Block modeling
{
Data used to build…..
• 3d model of subsurface
• Estimate potential resource
quantity
• Data gaps, uncertainty & risks
• Risk/benefit of additional data
collection
• Resource Valuation Model ($$$)
• Stronger than diamonds
• Lighter than water
• Cheaper than dirt
• Available everywhere
Ideal Proppant….
Tom Gapinske
Summit Envirosolutions
1217 Bandana Blvd. N
St. Paul MN 55108
(651) 472 2468
tgapinske@summite.com

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Qualifying Frac Sand Resources Using Cutting Edge Technology

  • 1. Qualifying Frac Sand Resources Using Cutting Edge Technology
  • 2. Sample prep & handling Data correlation PSD as decision tool PSD for “fingerprinting”
  • 3.
  • 4. Conclusions  Camsizer  Quick  Reliable  21st Century upgrade for PSD and more  Sample Handling Key to Reproducible Results  Natural variability on material is different that manufactured product  Use statistics & trend charts for big data sets vs. time
  • 5.
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  • 16. { “representative sample….” • Analyzing Representative Samples • Standardizing Testing ….. Methods Techniques Equipment • Quality Assurance/Quality Control - QA/QC
  • 17.
  • 18.  NEVER scoop always use sample splitter  No mechanical agitation like RoTap  Clusters and “coating” source for discrepancy  Smaller sample size – unforgiving!! Camsizer vs. Rotap learnings
  • 19. Sample prep Air dry Split & weigh Wash, wet sieve – P200 Dry and calculate %loss Micro photograph Archive sample
  • 20.
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  • 24. Proving the “method…” • Creating a “standard” sample • Splitting “standard” sample – maintain representative • Confirm to “ISO equivalence” • Establish statistically significant like vs. different
  • 25. Split sample into 5 parts. 4 splits used for ro-tap. 1 split used exclusively for CAMSIZER Run 3 of 4 samples in the ro-tap individually - once (saved 2, 3 and 4 to run through the CAMSIZER) Run 4th sample three times through ro-tap Split the one sample used for the CAMSIZER into 4 smaller parts Run 3 of 4 samples through the CAMSIZER once Run the 4th sample through the CAMSIZER three times Run sample 2, 3, and 4 from the ro-tap through the CAMSIZER
  • 26.
  • 27. Same split sample using sieves
  • 28.
  • 29. Same sample 3x Rotap
  • 30. Same sample 3x Camsizer
  • 31. All sets of Rotap data
  • 32. All Sets of Camsizer data
  • 33. Average of all Camsizer - Blue Rotap - Red
  • 34.
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  • 46. Site 1 Site 2 Site 3 Site 4 Sieve Size (US Standard) % Retained Roundness Sphericity % Retained Roundness Sphericity % Retained Roundness Sphericity % Retained Roundness Sphericity #16 0.1 0.92 0.96 0.4 0.91 0.87 0.3 0.91 0.87 0.6 0.67 0.86 #18 0.1 0.83 0.88 0.4 0.87 0.90 0.7 0.87 0.90 1.1 0.84 0.88 #20 0.8 0.75 0.85 1.1 0.83 0.87 1.5 0.83 0.87 1.7 0.85 0.85 #25 2.2 0.77 0.81 3.5 0.77 0.83 4.1 0.77 0.83 4.1 0.82 0.83 #30 6.6 0.78 0.83 5.2 0.82 0.83 7.2 0.82 0.83 6.3 0.80 0.78 #35 14.6 0.76 0.78 9.1 0.79 0.78 11.5 0.79 0.78 8.8 0.78 0.76 #40 17.6 0.73 0.77 10.2 0.79 0.77 12.7 0.79 0.77 9.7 0.76 0.76 #45 22.9 0.74 0.75 12.9 0.76 0.76 14.2 0.76 0.76 11.6 0.72 0.75 #50 20.0 0.70 0.72 10.2 0.72 0.73 11.4 0.72 0.73 10.2 0.68 0.73 #60 10.3 0.65 0.71 8.2 0.67 0.72 9.6 0.67 0.72 10.2 0.65 0.72 #70 2.2 0.61 0.70 5.3 0.63 0.70 5.7 0.63 0.70 7.2 0.62 0.71 #100 0.8 0.34 0.63 7.9 0.23 0.49 6.4 0.23 0.49 9.3 0.49 0.61 #200 0.4 0.19 0.54 16.5 0.22 0.43 8.1 0.22 0.43 11.3 0.24 0.38 PAN 1.5 9.2 6.6 8.0 20/40 41.0 0.7595 0.797 28.0 0.79275 0.79925 35.6 0.79275 0.79925 28.9 0.79175 0.784 30/50 75.1 0.7 0.8 42.4 0.8 0.8 49.8 0.8 0.8 40.3 0.7 0.8 40/70 55.3 0.7 0.7 36.6 0.7 0.7 40.9 0.7 0.7 39.2 0.7 0.7 4 sites
  • 51. {
  • 52.
  • 53. {
  • 54.
  • 55. { ArcGIS – Raster block allows x,y,z arithmetic
  • 57. {
  • 58. Data used to build….. • 3d model of subsurface • Estimate potential resource quantity • Data gaps, uncertainty & risks • Risk/benefit of additional data collection • Resource Valuation Model ($$$)
  • 59. • Stronger than diamonds • Lighter than water • Cheaper than dirt • Available everywhere Ideal Proppant….
  • 60. Tom Gapinske Summit Envirosolutions 1217 Bandana Blvd. N St. Paul MN 55108 (651) 472 2468 tgapinske@summite.com