February 2020 – Technical Talk

BCGS Technical Talk – February 20, 2020

Speaker: Randy Enkin, Geological Survey of Canada – Pacific, Natural Resources Canada

Title: Linking Geology and Geophysics: Mineralogy and Lithology from Physical Properties

Date/Time: Thursday, February 20, 2020 @ 4:30pm PST

Location: 1st Floor Boardroom B (Suite 111), 409 Granville St. (UK Building at Granville and Hastings), Vancouver


Linking Geology and Geophysics: Mineralogy and Lithology from Physical Properties
Randy Enkin, Paleomagnetism and Petrophysics Laboratory and Section Head, Sedimentary Systems and Processes; Geological Survey of Canada – Pacific, Natural Resources Canada, Government of Canada

Effective geophysical mineral exploration requires an integrated approach to understanding the geochemistry, mineralogy, lithology, and geological processes that form deposit systems. Rock physical properties provide the link between geophysics and geology.  This presentation focuses on density and magnetic susceptibility, their distribution based on the Canadian Rock Physical Property Database (GSC Open File 8460), and the mineralogical settings of ferrous and ferric iron which explains their distribution. We move beyond simple categorization of rock types according to their physical properties, to developing a quantitative mineral mixing model based on 3 principal components:  QFC (quartz-feldspar-calcite), FM (ferromagnesian silicates), and M (magnetite). This model permits users of remote sensing data to quantify equivalent rock and mineral types, and develop a spatial view of geological processes.

Based on Enkin, Hamilton, and Morris (2020). The Henkel Petrophysical Plot: Mineralogy and Lithology from Physical Properties. Geochemistry, Geophysics, Geosystems, 20, https://doi.org/10.1029/2019GC008818



KEGS/BCGS Roundup Breakfast 2020

KEGS/BCGS Roundup Breakfast – Tuesday, January 21, 2020

Speaker: Dr. Craig Hart, Director, Mineral Deposit Research Unit, (MDRU),
University of British Columbia

Title: Smarter Exploration Opportunities are in the gap between Geology and Geophysics

Date/Time: 2020-01-21 @ 7:30am

Location: Princess Louisa Room, The Fairmont Waterfront Hotel
900 Canada Place, Vancouver, BC V6C 3L5

Registration: Online at www.kegsonline.org (Deadline Jan 19, 2020)


Smarter Exploration Opportunities are in the gap between Geology and Geophysics

Craig Hart, Director MDRU (Mineral Deposit Research Unit)

Mineral exploration is a process of progressive area reduction down to the extent of an ore body. Decision-making throughout this process, including from the initial land acquisition, is strongly informed by geological maps the distribution of geological features, so a good geological map is the best exploration decision-making tool. However, most geological maps are wrong. They are representations of observations on sparse data (outcrops) assembled and subjectively interpolated with the benefit of the map maker’s accumulated experiences. Fortunately, all geological maps can be easily, and often significantly, improved with the integration of information from geophysical and physical property datasets thus providing a superior decision-making tool. These improvements can be made at all scales from regional scales to map limits of large tectonic elements like terrane boundaries, to simply improve every regional-scale (1:500k to 1:25k) geological map ever produced, to the drill target scale where the geometry of geological features can be better discerned.

The opportunity to improve geological knowledge from geophysical data is huge since the vast majority of geophysical datasets inform on regional to property scale geological frameworks, not orebodies, but most of this data is never utilized. Most geologists lack the skills to extract geological information from geophysical data other than using crayons to indiscriminately draw lines. MDRU have developed a range of tools and approaches to defining and extracting geological features from geophysical data that range from simple and pragmatic to the complex integration of derived datasets.

Understanding relationships between rocks and geophysical responses requires an understanding of rock physical properties. Although most exploration geologists are familiar with magnetic susceptibility and density data since it is routinely collected during core logging, few geologists know how to evaluate and utilize the data to interpret geological features. So although there is increasing recognition of the potential value of collecting physical property data, utilizing these data either to interpret regional geophysical datasets, to create geological models, or to constrain inversions remains an on-going challenge.

The geological information available at the surface is mostly too sparse and limiting to provide a confident base to inform smart exploration decisions, particularly in regions of cover. So ultimately geological maps should be replaced with 3D models of the geological framework of the upper crust. This effort is best done using a contiguous, data-rich environment where geological and geophysical data sets are informed by physical properties and constrained geophysical inversions that are integrated by an experienced geoscientist, probably driving a set of Machine Learning algorithms.

About the Author:

Dr. Craig Hart;
B.Sc. McMaster University (1986), M.Sc. University of BC (1995), University of Western Australia (2005).

Craig Hart is the Director of MDRU – Mineral Deposit Research Unit at the University of British Columbia (UBC) where he initiates and facilitates a wide range of mineral exploration industry-sponsored research projects that focus on gold and porphyry systems, regional metallogeny and exploration methods. Craig has degrees from McMaster University (BSc 1986), University of British Columbia (MSc 1995) and University of Western Australia (2005) spacing academic intervals over three decades separated by employment in industry and government. Craig previously worked as a Senior Research Fellow at the Centre for Exploration Targeting at the University of Western Australia (UWA) in Perth where he pursued research gold metallogeny of China and Mongolia. Most of Craig’s early career was with the Yukon Geological Survey where he undertook regional mapping and metallogenic surveys in the northern Cordillera. He played a significant role in developing intrusion-related gold models, and understanding redox controls on regional metallogeny.

Craig has considerable field and mapping experience which he integrates with geochronology, geochemistry and geophysics to develop new exploration concepts and targets. He has raised >$20M in research funding to contribute to the training of more than 40 graduate students and 20 senior researchers. He provides advanced ore deposit and mineral exploration training to students and industry, has given presentations and short courses throughout the world, and consults to a range of major and junior explorers. Dr. Hart was awarded the Geological Association of Canada Boldy Award for the best mineral deposit-related presentation in 2005, and was the SEG Distinguished Lecturer of the Society of Economic Geologists in 2010. In 2016 Craig led his team to 5th place in the Integra Gold Rush Challenge, and also took home the “Audience Choice Award” for his engaging presentation.

BCGS 2019 Fall Symposium: Geophysics Applications to Environmental, Civil and Mining Engineering Studies

The BC Geophysical Society is proud to present the 2019 BCGS Fall Symposium “Geophysics Applications to Environmental, Civil and Mining Engineering Studies”

Brought to you with support of our sponsors.

SponsorLogos_WebThe theme is engineering geophysics applied to civil and mining engineering projects, groundwater investigations, and environmental studies.

One of the main focuses will be on tailings storage facilities (TSF) and the recent dam failures that have been well publicized recently.  The topic will be reviewed by leading geotechnical and geophysical experts introducing the challenges of monitoring TSFs and providing case studies showcasing a variety of geophysical applications. The day will then open up to innovative geophysical applications in groundwater investigations, metal detection, subsea pipeline monitoring and hazard assessment. The talks will cover a range of cutting-edge technologies from GPR, 3D seismics, HR gradient magnetics, electromagnetics, to borehole logging, AUV and 4D database management.

Date: Friday, October 11, 2019
Time 8:00 am to 5:00 pm PST
Registration Cost:
– Non-Member Price $150
– Member Price $130
– Student Price $30
Registration link is below
Location: UBC Robson Square, 800 Robson St, Vancouver, BC, V6Z 3B7

Symposium Schedule: BCGS 2019 Fall Symposium Schedule

Symposium Abstracts: BCGS 2019 Fall Symposium Abstracts


Please register in advance of the symposium. Your registration is guaranteed once payment has been received. The attendee name must be entered for registration to be complete. Confirmed Speakers do not need to register.

A half day (AM or PM) option is available. The half day rate includes lunch.

Registration is closed. Thank you for attending.

Co-Chairs: Graham Parkinson, Klohn Crippen Berger & Cliff Candy, Frontier Geosciences


David Chambers, Center for Science in Public Participation (CSP2) – From Bulletin 121 to Brumadinho: The Increasing Frequency & Severity of Tailings Facility Failures: Navigating the Decade 2020-2029.

Harvey McLeod, Klohn Crippen Berger – Safe design of tailings dams: how geophysics can help.

Graham Parkinson, Klohn Crippen Berger – The gamut of tailings dam geophysics.

Doug McConnell, DMT Geosciences – Failure is not an option: tailings dam investigations with geophysics and the Mount Polley review.

Michael Maxwell*, Robert Eso, Golder Associates – 3D electrical resistivity imaging (ERI) investigations of surface tailings facilities and underground mine operations.

Jan Francke, Groundradar Inc. – Radar imaging of TSFs and the potential of 4D tomographic monitoring.

John McGaughey, Mira Geoscience – The role of geophysics in quantitative geotechnical hazard assessment.

David Schieck, Echo Environmental & Geotechnical – Shear landstreamer profiling for dam and levee investigations: single pass MASW, P‐ & SH‐wave reflection technology.

Martin Karrenbach, OptaSense – Distributed fiber-optic sensing (DAS) in geophysical and engineering applications.

Riaz Tejani*, DGI Geoscience, Marcus Donaldson*, Qteq – Using borehole magnetic resonance to detect free and bound water in tailings and estimate hydraulic conductivity to predict resistance to static liquefaction failure in upstream tailings dams.

Cliff Candy, Caitlin Shaw-MacLaren*, Frontier Geosciences – Geophysical site investigations at the Bennett Dam.

Mel Best, Bemex Consulting Int’l – The Peace project aquifer study.

Kevin Kingdon*, Len Pasion, Black Tusk Geophysics – The application of the UltraTEM metal detector to mining environments.

Peter Kowalczyk, Karen Weitemeyer*, Ocean Floor Geophysics – Using AUV Electric Field measurements to monitor the integrity of cathodic protection systems on subsea pipelines.

David Huntley, GSC ‐ NRCan – Proactive Infrastructure Monitoring and Evaluation (PRIME) Installation in Canada: Protecting National Railways by Monitoring an Active Landslide near Ashcroft, BC (Poster).

August 2019 – Technical Talk

BCGS Technical Talk – August 12, 2019

Speaker: Professor Eun-Jung Holden, University of Western Australia

Title: Developing Data Science Applications in Geosciences: An End-User Focused Approach

Date/Time: Monday, August 12, 2019 @ 4:30pm PST

Location: 4th Floor Conference Room, Room 451, 409 Granville St. (UK Building at Granville and Hastings), Vancouver


Developing Data Science Applications in Geosciences: An End-User Focused Approach
Professor Eun-Jung Holden, Geodata Algorithms Team, UWA

Understanding complex subsurface geology is a challenging task where interpretations are performed using diverse types of geoscientific data. The Geodata Algorithms Team at UWA has been working closely with the minerals industry for the past 12 years and developed machine-assisted solutions to improve the efficiency and the robustness of geological interpretation. This talk will present a number of applications of automated image analysis and machine learning, which were  developed by the team in recent years in partnership with mining companies.  They include drillhole data analysis and integration methods which are currently used by industry end-users; on-going research on advanced drillhole data visualisation and interpolation methods; and on-going development a geological knowledge mining system for exploration reports using text mining.


Professor Holden received her BSc, MSc and PhD in computer science from the University of Western Australia.  Her postgraduate and postdoctoral research focused on developing visualization, automated image analysis and machine learning techniques for hand gesture recognition.  Then in 2006, she made a transition to geoscience and now leads the Geodata Algorithms Team at UWA.  The team effectively spans the boundaries of computational science and geoscience and links academia and industry.  Three suites of their data analytics algorithms were commercialized, namely CET Grid Analysis and CET Porphyry Detection extensions for Geosoft’s Oasis Montaj; and Image Structure and Interpretation module for Advanced Logic Technology (ALT)’s WellCAD, which are marketed and licensed by Geosoft (based in Canada) and ALT (based in Luxembourg) respectively.  She is currently leading the UWA-Rio Tinto Iron Ore data fusion projects which aim to achieve machine-assisted modelling of geology/resource through transformational and interpretive data science solutions.  Her research team won the UWA Vice Chancellor Award in Impact and Innovation in 2015.

June 2019 – Technical Talk

BCGS Technical Talk – June 20, 2019

Speaker: Mike McMillan, Computational Geosciences

Title: Machine Learning in the Natural Resources Industry – examples and applications for mining, oil and gas and water exploration

Date/Time: Thursday, June 20, 2019 @ 4:30pm PST

Location: 4th Floor Conference Room, Room 451, 409 Granville St. (UK Building at Granville and Hastings), Vancouver


Machine learning and artificial intelligence (AI) are all the rage in 2019, and we take a look at recent applications of AI across a wide spectrum of problems in the natural resource industry. These vary from mineral and water prospectivity mapping to airborne induced-polarization detection, to borehole classification and seismic horizon picking. These new developments use deep convolutional neural networks to train the computer to detect subtle patterns across many geoscience data layers in order to help (and importantly not to replace) the geoscientist. Given a data-rich region with many overlapping geoscience data layers, the key is to come up with a well-defined question with examples of training labels. In the training labels we want both positive outcomes (ie. what you’re actually looking for) and negative outcomes (ie. what you’re definitely not looking for). These labels can be anything from gold-assays, rock types, fault types to salinity values in water. The type of label doesn’t really matter as long as it represents the thing or things you’re trying to find (or not trying to find). The areas without labels are the unknown regions that the machine learning algorithm will try to predict on based on signatures it learns from the training labels. In some settings this may be predicting gold grades in un-drilled areas, it may be predicting which electromagnetic decays have induced-polarization responses, or it may be predicting the likelihood of a water aquifer occurring in a remote region of the desert. The convenient aspect of these convolutional neural networks is that the algorithm architecture can be used to answer a multitude of questions, depending on the input training labels. This means that unlike geophysical inversion where a completely different code is required for magnetics, gravity or electromagnetics, we can generally use one AI framework, with some minor tweaks, for every problem. In this manner, we can throw in all available data sets and collectively use this information to help answer relevant questions that will help drive a data-driven cost-effective exploration program.