APPLICATION OF CATCHMENT ANALYSIS TO REGIONAL STREAM ...

APPLICATION OF CATCHMENT ANALYSIS TO

REGIONAL STREAM SEDIMENT DATA SETS

Dr. Dennis Arne

Consulting Geochemist

PGeo (BC), MAIG (RPGeo), MAAG (Fellow), MCIM

Telemark Geosciences/CSA Global

AIG Exploration Geochemistry Symposium – December 3, 20181


Statement of problem

Background to catchment analysis

Examples of interpretive approaches

Using catchment analysis to plan surveys

Conclusions

OUTLINE

ACKNOWLEDGEMENTS

Former colleagues at CSA Global & ioGlobal

Yao Cui, British Columbia Geological Survey

Funding from Geoscience BC

Support from the AIG WA branch to attend


STATEMENT OF PROBLEM

How do we correct stream sediment data for the effects of variable

geochemical background due to different lithological units?

How do we take into account surficial processes such as scavenging

of metals onto secondary Fe and Mn oxides, clay minerals or organics?

How do we correct for the differential effects of dilution in catchment

basins of differing area?

What is the optimal catchment area for sampling and has the region

been effectively sampled? (i.e. are there opportunities for further

exploration? Are we over- or under-sampling).



THEMATIC MAP VS TARGETING PRODUCTS

How do we get from this …. To this?(From Arne et al., 2018)


GRIDDED PERCENTILE IMAGE OVERLAIN WITH STRUCTURAL TRENDS

(From Arne & Blumel, 2011)Or this?


Collate sample information and analytical data

Verify location datums and analytical units

Geochemical data conditioning

Determine optimal analytical data set and data quality

Treat values below lower limits of detection

Obtain DEM at suitable resolution

Pit-fill to remove topographical sinks

Derive or import hydrology layer

Validate sample locations against hydrology

Locations may need adjustment

Generate individual catchments for each sample

Each sample to be attributed with entire catchment

Attribute samples/catchments with lithological information

Geological legends must be simplified for statistical analysis

CATCHMENT ANALYSIS METHODOLOGY


DERIVATION OF CATCHMENTS - 1

Derived from digital elevation model (DEM).

Suitable data sources include Shuttle Radar

Topography Mission (SRTM – 30m resolution

at equator) or Advanced Spaceborne

Thermal Emission and Reflection Radiometer

(ASTER – 15 to 90m resolution), plus other

commercial satellite, government and

geophysical survey elevation data.

Note minor locational issues with some of

these data sets.

Project area is the White Gold District, Yukon

Territory, Canada.

SRTM DEM for the White Gold District, Yukon, Canada.Squares are 25 km2. Black dots are mineral occurrences.

White Gold District



Regional Geochemistry Survey samples

from British Columbia, Canada were mainly

collected prior to the widespread use of

GPS.

i.e. physical transcription of data from paper maps

and manual entry into GSC database (plenty of scope

for error!)

Original topographical maps used to locate

samples may have been inaccurate

compared to present day terrain data.

Sample locations were adjusted to lie on

correct drainage, based on original

topographic maps.

Sample location from Vancouver Islandre-located onto TRIM hydrology layer with scan

of original paper map sheet as background

(From Arne & Brown, 2015)



Previously done by tracing out the

heights of land surrounding the

catchment basin by hand.

Now automated using a number of

software packages – note that not all

allow determination of a catchment

from an arbitrarily located sample

point rather than a stream outlet.

Generally iterative as location

problems are recognised by

nonsensical catchments.

Sample points are from the Yukon

regional geochemical survey (RGS)

program.

Sample locations in green with derived catchment basins in orange outlines.


A low -80# Au from the Yukon open file

data in the stream leading from Golden

Saddle led to the assumption that stream

sediment data didn’t work in this area.

While subtle anomalies are present at

Golden Saddle and the Coffee deposits

using raw element data, an index using As

and Sb levelled for dominant catchment

lithology provides an enhanced response.

Note that the raw Au is only weakly

anomalous at Golden Saddle if an

average of the primary and field duplicate

sample are plotted.

WHITE GOLD DISTRICT, YUKON TERRITORY, CANADA

(From Arne & MacFarlane, 2014)


Raw data

Residuals following regression against regolith control elements

Data levelled by dominant catchment lithology

Data levelled by presence/absence of a particular unit

Data levelled by catchment weighted background value

Multiple regression analysis using catchment geology

Productivity analysis

Weighted sums model

Weighted sums model adjusted for catchment area size

Residuals following regression against principal components

Machine learning algorithms

DATA ANALYSIS APPROACHES

Inc

rea

sing

ma

the

ma

tica

l co

mp

lexity

NORTH VANCOUVER ISLAND CASE STUDY


• Data compiled for 1835 samples in total

• Catchment basins delineated for 1725 samples


IMPORTANCE OF LITHOLOGY

• Geology is interpreted in terms of lithology, rather than map units.

• The distribution of Cu is clearly influenced by the Karmutsen basalt; difficult to

distinguish Cu anomalies associated with porphyry Cu deposits in those areas.


Raw Cu DataMt Hall Gabbro?


LEVELLING Cu DATA FOR LITHOLOGY

• Levelling by dominant lithology or presence/absence of basalt both reduce

lithological effects.


Levelled by Dominant Lithology Levelled by presence/absence basalt


WEIGHTED AVERAGE BACKGROUND VALUES

• Average background values have been estimated for most lithologies.

• These have been used to calculate weighted average background values, which

were then used to calculate robust Z-scores ((observed – median)/interquartile range).


Z-score Cu “Residuals”



Methods based on levelling against known geology depend on the following

assumptions:

That the samples are located correctly

That the geology of the area is accurately known

That the lithological character of mapped units is known and consistent

That there are no minor but geochemically distinct lithological units in the area that

have not been mapped (i.e. black shales)

That erosion from all lithological units is similar so that the contribution from each unit

is consistent and represented by its areal extent within the catchment

Methods that make use of principal component analysis depend on the following

assumptions:

That the principal components represent recognisable geochemical processes

(lithology, scavenging, mineralisation)

ASSUMPTIONS USING CLASSICAL APPROACHES

PRINCIPAL COMPONENT ANALYSIS


• The most important principal components from

regional stream sediment geochemical data

usually reflect bedrock lithology.

• PC1 from northern Vancouver Island separates

felsic and mafic lithologies.

Sc

ale

d C

oo

rdin

ate

s

PC1

PC2

PC3

Felsic

Mafic

• PC1 provides a better discriminator for the Karmutsen basalt than raw Cu, which is

influenced by the Mt. Hall Gabbro.


Raw Cu Data Inverse PC1

PC1 VS RAW CU DATA

Raw Cu Inverse PC1


REGRESSION AGAINST PC1

• Cu can be regressed against PC1 (lithological control).

• High positive residuals represent Cu above predicted background.



METHOD VALIDATION

• Data processing methods were validated against known occurrences.

• Known occurrences in the upper 90th percentile plotted relative to the proportion

captured by raw Cu data.

21

Cu Occurrences No Cu Occurrences

>9

0th

Pe

rce

ntile

<9

0th

Pe

rce

ntile

True

Positives

False

Positives

False

Negatives

True

Negatives

Single Element Methods

Cu

Pro

du

ctiv

ity

We

igh

ted

Su

ms

Mo

de

l

WSM

* C

atc

hm

en

t A

rea



• Geochemistry in catchment areas >10 km2 mainly reflects regional background

• Catchments > 10 km2 have not been effectively sampled

Sampling Effectiveness

SAMPLING EFFECTIVENESS


CONCLUSIONS

The effects of elevated background metal contents are easily filtered

using a variety of methods of varying sophistication.

Processing methods using several commodity and pathfinder elements

weighted for the effects of dilution work best.

Existing mineral occurrences & deposits are more readily apparent and

new targets evident in processed data.

An empirical assessment of sampling effectiveness indicates whether

there are still exploration opportunities in under-sampled areas and defines

the optimal density of follow-up sampling.


REFERENCES


Arne, D.C. and Bluemel, E.B., 2011, Catchment analysis and interpretation of stream sediment data from QUEST South, British Columbia, Geoscience BC, Report 2011-5, 25 p. URL < http://www.geosciencebc.com/s/2009-023.asp> [November 2018]

Arne, D. and MacFarlane, B., 2014, Reproducibility of gold analyses in stream sediment samples from the White Gold District and Dawson Range, Yukon Territory, Canada. Explore, No. 164, p. 1-10. URL <https://www.appliedgeochemists.org/explore-newsletter/explore-issues> [November 2018]

Arne, D.C. and Brown, O., 2015, Catchment analysis applied to the interpretation of new stream sediment data from northern Vancouver Island, Canada (NTS 102I and 92L). Geoscience BC Report 2015-4, 41 p., URL <http://www.geosciencebc.com/s/Report2015-04.asp> [October 2017]

Arne, D.C., Mackie, R., Pennimpede, C., Grunsky, E. and Bodnar, M., 2018, Integrated assessment of regional stream-sediment geochemistry for metallic deposits in northwestern British Columbia (parts of NTS 093, 094, 103, 104). Geoscience BC Report 2018-14, 96 p. URL < http://www.geosciencebc.com/s/2016-028.asp> [November 2018]

Arne, D., Mackie, R. and Pennimpede, C., 2018, Catchment Analysis of Re-analyzed Regional Stream Sediment Geochemical Data from the Yukon. Explore No. 179, pp. 1-13. URL <https://www.appliedgeochemists.org/explore-newsletter/explore-issues> [November 2018]

Mackie, R.A., Arne, D.C. and Brown, O., (2015): Enhanced interpretation of regional stream sediment geochemistry from Yukon: catchment basin analysis and weighted sums modelling; Yukon Geological Survey, Open File 2015-10. URL <http://data.geology.gov.yk.ca/Reference/69462> [November 2017]

Mackie, R.A., Arne, D.C. and Pennimpede, C. (2017): Assessment of Yukon regional stream sediment catchment basin and geochemical data quality; Yukon Geological Survey, Open File 2017-4, 36 p. URL <http://data.geology.gov.yk.ca/Reference/79430> [October 2017]

http://www.geosciencebc.com/s/2009-023.asp

https://www.appliedgeochemists.org/explore-newsletter/explore-issues

http://www.geosciencebc.com/s/Report2015-04.asp

http://www.geosciencebc.com/s/2016-028.asp

https://www.appliedgeochemists.org/explore-newsletter/explore-issues

http://data.geology.gov.yk.ca/Reference/69462

http://data.geology.gov.yk.ca/Reference/79430

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