Applied mineral exploration methods, hydrothermal fluids, baro-acoustic decrepitation, CO2 rich fluids
Viewpoints:

How CO2 inclusions form from aqueous fluids

Understanding heterogeneous fluids : why gold is not transported in CO2 fluids

Gold-quartz deposits form from aqueous heterogeneous fluids: NOT from CO2 fluids

Inclusion shapes can prove heterogeneous FI trapping

Disproportional FI trapping from heterogeneous fluids explains gas-dominant systems

A discussion of H2 analysis by mass spectrometry

A mechanism to form H2 in the MS ioniser during analyses


News:

Sangan skarn Fe deposits, Iran

New model 205 decreptiometer

Studies of 6 Pegmatite deposits

A study of the Gejiu tin mine, China


Exploration using palaeo-hydrothermal fluids

Using opaque minerals to understand ore fluids


Understanding baro-acoustic decrepitation.

An introduction to fluid inclusions and mineral exploration applications.



 Interesting Conferences:


AGCC expo, Adelaide, Aust. Oct. 14-18 2018

-----2019-----

ECROFI, June 24-26, Budapest, Hungary

AOGS, Singapore, 28 Jul-2 Aug 2019

SGA, Glasgow Scotland, Aug. 27-30 2019


Comprehensive Geology Conference Calendar


Deconvolution of the Brusson mine data




The decrepitation curves of the Brusson samples show complex shapes and difficult to use in interpretation. By performing deconvolution of the curves we can find a subset of population distributions which add together to give the observed curve. It is then possible to compare samples using the parameters of the component sub-populations. A complete discussion of the study at the Brusson mine is here.

All of the Brusson samples were deconvolved using a mathematical software package. Although it is possible to deconvolve the data into gaussian distribution populations a lower residual error (better fit) is obtained by using a skewed gaussian distribution. It is reasonable to expect fluid inclusions populations to be skewed because of the increased likelihood of decrepitation of inclusions near grain surfaces. Skew can also be caused by changes in the gas content of inclusions during entrapment and quartz formation. During curve deconvolution a degree of user input is helpful to constrain the mathematics as the solution is not necessarily unique and some solutions lead to physically unlikely population groupings.

Some of the Brusson deconvolution data is presented here to show how well the method fits the data. At the completion of each fitting procedure, the parameters of the various sub-populations are recorded and used to prepare the tabulation of peak temperatures shown previously.



At the lower adit level a low temperature decrepitation peak is common, but not always present
h2036 1954 lowest

h2037 1954 lowest



At the mid-level adit, the quartz varies from complex with multiple populations to simple with only 2 decrepitation peaks.
h2044 1955 mid

h2048 1955 mid

h2049 1955 mid



At the upper adit level, low temperature CO2 caused decrepitation is still prominent.
h2052 1956 upper



Above the ore zone in carbonate host rocks, low temperature CO2 caused decrepitation is still present.

Note that the next 2 graphs are 2  fits to the same sample data assuming either 4 or 5 sub-populations. The 5 peak fit is slightly better than the 4 peak fit - but it is difficult to be sure exactly how many populations are really present in the data. The curve fitting does not necessarily lead to a unique result. However, multiple fits of the same data with the same number of assumed populations does lead to identical sub-population parameters.

h2053-4 1957 co3

h2053-5 1957 co3


Note the complexity of the sample with many fluid inclusion populations, indicating that this quartz is strongly zoned.

h2056 1957 co3



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