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:

New model 205 decreptiometer

Studies of 6 Pegmatite deposits

A study of the Gejiu tin mine, China

A magnetite study - Bergslagen region, Sweden

Exploration using palaeo-hydrothermal fluids

Using opaque minerals to understand ore fluids

Decrepitation using Fe-oxide opaques

Understanding baro-acoustic decrepitation.

An introduction to fluid inclusions and mineral exploration applications.



 Interesting Conferences:


AOGS, Honolulu, June 3-8 2018

PACROFI 14, Houston, June 11-18 2018

AAG 2017 at RFG2018, June 16-21 2018, Vancouver, Canada

IMA 2018, Melbourne Aust., Aug 13-17 2018

IAGOD, Salta Argentina, Aug. 28-31 2018

ACROFI-2018, Beijing, Sept. 11-17 2018

SEG, Keystone Colorado, Sept. 22-25 2018

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

-----2019-----

AOGS 2019 Singapore

SGA, Glasgow Scotland, Aug. 27-30 2019


Comprehensive Geology Conference Calendar


Software used in Baro-acoustic decrepitation presentation and interpretation.

Although geology and mathematics are often uncomfortable partners, the baro-acoustic decrepitation data benefits greatly from graphical presentation software and some statistical methods. All of the interpretation is done on a Linux system, running the OpenSuse linux operating system, but the "colour" of linux (or even the operating system type) is largely unimportant. The main programs used are:
With the added python module, Scidavis was used for the first of the deconvolution plots. It does work, but can be tricky to drive and is critically dependent on the start parameters. The default start parameters fail to lead to convergence, so fitting must be done manually to allow more appropriate starting parameters to be set. In addition, it will by default allow the component populations to go negative, which is  unrealistic. This behavior has to be stopped with appropriate choice of settings before the curve fit is started. Normally, the inbuilt "automatic-fit" option automatically plots the individual component curves and the fitted curve as well as the original data curve. But when using manual fitting, the system no longer plots the component curves. Additional python code was written to read in the curve parameters and add these component curves to the final plot. This scripting also allows automated title and legend addition so the plots are of presentation standard. Although the software does eventually perform reliable and realistic curve fits, it is hard to drive and sometimes requires numerous attempts.  Scidavis was used for the curve fitting interpretation of the Brusson mine, Italy and the Malanjkhand mine, India. A much more convenient curve fitting program was subsequently found - fityk (see below).