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STEINERT Elektromagnetbau GmbH

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Nordkalk

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  International Mining (IM)

 

 

11th Fennoscandian Exploration and Mining (FEM 2017)
Short Courses

 

PRE-CONFERENCE SHORT COURSE

Dates:

Place:      

Monday 30 October at 15:00 - 18:00
Tuesday 31 October at 09:00 - 16:00
Hotel Hullu Poro, Levi, Lapland, Finland


Spectral sensing technologies applied to mineral exploration & production

Prof. Carlos R. Souza Filho, The University of Campinas (UNICAMP), Brazil

Lecturer:
Prof. Carlos R. Souza Filho, The University of Campinas (UNICAMP), Brazil  

"Professor Carlos Roberto de Souza Filho is the Chair of the Research Group and Labs on Geotechnologies (VNIR-SWIR-TIR Spectroscopy and Remote Sensing, Geophysics, GIS, Geomathematics), at the Geosciences Institute, University of Campinas (UNICAMP), Brazil. He has developed numerous methods and applications of Geotechnologies in basic geology, resource exploration and planetary studies. He is the author of >120 PEER-reviewed articles and received a number of science awards and large projects during his career. He has supervised 22 MSc, 24 Ph.D. students and 14 postdoctoral researchers at UNICAMP between 1997-2016. He is a NASA-funded researcher on ASTER HyspIRI missions. He is currently the Associate Editor of the International Journal of Applied Earth Observation and Geoinformation." 

Goal: The focus of the workshop is on multi-scale applications of remote sensing technologies to mineral exploration, from rock core and mine wall rock data to airborne and orbital data.

Course description: Principles of visible, near infrared, shortwave infrared and longwave infrared spectroscopy. Mineral spectroscopy and interpretation techniques. Multispectral vs hyperspectral systems. Core imaging vs core profiling systems. Image processing and information extraction techniques. Applications in target generation at regional scale and in mineral and rock mapping at mine and borehole scale.

Details of content: A new array of passive remote sensors operated on ground, airborne (aircraft and UAVs) and orbital platforms with multispectral, hyperspectral and ultraespectral coverage in the VIS-NIR-SWIR-TIR range (0.4-14µm), now provides the geologic community with both public and proprietary data unprecedented in history. These Geotechnologies have aided in the discovery and sustainable production of mineral resources from innovative approaches.

In this workshop, we intend to address several successful case studies involving the use of such spectral sensing technologies in mining applications and development of these resources, as well as report on available and emerging systems tuned for geological applications in integrated and multiscale approaches. Among such systems stand out those considered for target detection in the field (eg Fieldpsec, OreExpress, Halo), in core logging (eg, SisuRock, Terracore, Corescan, Hylogger), in mine face mapping (eg, AISAFenix , HySpex), in airborne surveys (eg, AISA Fenix, AISA Eagle-Hawk-Owl, HyMap) and in orbital acquisitions (eg, ASTER, WV-3, Sentinel-2; plus soon to be launched sensors: eg, EnMap, HyspIRI). The most tangible importance to the segment of mineral resources is the demonstration that these instruments, data and derived information can be used systemically, from the continental to the deposit scales, providing critical insights for geologists. This workshop intends to show recent progress on these key topics and provide participants with some hands-on experience on data analysis and interpretation.

Who should attend? The course is designed especially for exploration geologists and geophysicists.

Course requirements: Participants will use their own laptops for hands-on exercises.

Short Course registration fee per person is

till 1 September 2017
from 2 September 2017        

360 €
460 €

Registration fee includes course programme and materials, lunch on Tuesday and refreshments during breaks.

Participants: Minimum 15, maximum 25 persons.

 

PRE-CONFERENCE SHORT COURSE

Dates:

Place:      

Monday 30 October at 15:00 - 18:00
Tuesday 31 October at 09:00 - 16:00
Hotel Hullu Poro , Levi, Lapland, Finland


Advanced data analytics for mineral explorers - SOLD OUT

Prof. Eun-Jung Holden, The University of Western Australia

Lecturer:
Prof. Eun-Jung Holden, The University of Western Australia  

"Eun-Jung (EJ) Holden was trained as a computer scientist and made a transition to geoscience in 2006. She established and leads the Geodata Algorithms Team at the Centre for Exploration Targeting (CET) within The University of Western Australia (UWA). The team spans the boundaries of computational science and geoscience, and has been developing innovative geodata analytics tools by working closely with the Geological Survey of Western Australia (GSWA) and the resource industry. Their collaboration with industry resulted in three commercial software products, namely the CET Grid Analysis and the CET Porphyry Detection extensions for Geosoft Oasis Montaj, and the Image and Structure Interpretation Workspace for ALT's WellCAD, which are used widely by mining and petroleum companies and consultancies around the world. Their collaboration with GSWA over the past three years resulted in the development of the Integrated Exploration Platform, a GIS based data interpretation support platform for mineral explorers, which was launched as a GSWA product in 2016. The Team won various awards including Laric Hawkins Memorial Innovation Award at the 23rd International Geophysics Conference and Exhibition in Melbourne in 2013; and the UWA Vice Chancellor Award in Impact and Innovation in 2015."

Tom Horrocks, PhD candidate, The University of Western Australia

Lecturer:
Tom Horrocks, PhD candidate, The University of Western Australia

"Tom Horrocks is a PhD candidate at the University of Western Australia (UWA), where he is supervised by Prof. Eun-Jung Holden at the Centre for Exploration Targeting (CET). His research interests are in the application of machine learning and multivariate statistics to geological and geophysical data, including 3D inversions, wireline logs, and geochemistry. Tom's previous work includes automated lithology classification from wireline logs in the coal exploration domain, using neural networks to correlate shale markers in natural gamma logs in the iron ore exploration domain, and classifying crushed rock samples within a gold mine as ore or waste using photographs and hyperspectral measurements. More recently, he has developed an edge detection algorithm to visualise 3D inversions which he has applied to the Kevitas Ni-Cu-PGE deposit. Currently, he is developing a method for 3D prediction of talc alteration within Kevitsa." 

Goal: The focus of the workshop is on concepts and applications of image analysis, machine learning and visualization for datasets used by mineral explorers

Course description: Principles of image analysis, machine learning and visualization. Human driven computer assisted geological interpretation. Data analytics methods and tools for diverse datasets including regional scale spatial data, outcrop images, downhole data and visualizing geophysical inversions.

Details of content: There has been an increasing interest by the minerals industry to capitalize on recent advances in data science to maximize their return on investment on collecting diverse geoscientific datasets throughout exploration, extraction and processing. The biggest challenge for the mineral explorers (greenfield or brownfield) is addressing uncertainty in geological interpretation. Understanding complex geology using sparse and diverse observations (often at varying scales) is not a trivial task, where human biases play a key role which result in highly inconsistent outcomes amongst and even within individuals. Computational algorithms can assist geological knowledge discovery through various analytical steps such as recognizing patterns of interest through signal/image processing, machine learning or statistical methods. However the geological insights by an interpreter, albeit inconsistent, which contribute to geologically feasible interpretation outcomes are hard to model for computational algorithms, especially considering highly variable existing knowledge, diverse and complex geological settings, and availability of different types of data at different scales.

This workshop will deliver an overview of fundamental concepts on image analysis, machine learning and data visualization methods, and their applications while ensuring the data analytical methods are interpretable and geologists' insights can be incorporated into the data analysis workflow. Interpretation support methods and tools will be presented, including spatial exploration data from diverse sources for structural interpretation; and drill hole data for lithology modeling specifically for the Kevitsa Ni-Cu-PGE deposit. There will be hands-on exercise on Integrated Exploration Platform, a GIS based data analytics platform for ArcGIS which was developed in collaboration with the Geological Survey of Western Australia.

Who should attend? The course is designed especially for exploration geologists and geophysicists.

Course requirements: Participants will use their own laptops for hands-on exercises.

Registration fee includes course programme and materials, lunch on Tuesday and refreshments during breaks.

Participants: Minimum 15, maximum 25 persons.