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  • 11 May 2020 6:55 PM | Kanita Khaled (Administrator)

    May 2020 Bulletin

    KEGS TORONTO TALK, MAY

    Register online to join the KEGS Toronto May talk!

    Date:   2020-05-12 @ 4:30pm

    VenueWebinar

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    https://attendee.gotowebinar.com/register/2771242498534384655
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    Password: 621480
    +17789072071,,95149535406# Canada
    +14388097799,,95149535406# Canada
    +1 778 907 2071 Canada
    +1 438 809 7799 Canada
    +1 587 328 1099 Canada
    +1 647 374 4685 Canada
    +1 647 558 0588 Canada
    855 703 8985 CanadaToll-free
    Find your local number:https://laurentian.zoom.us/u/arHSDrcxq

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    Register here to join the webinar presentation:

    Speaker David Schieck, MSc., P.Geoph (AB) P.Geo(ON)

    Bio: David started his career in high school with a summer job as a “jug-hound” in S. Alberta. He continued his interests in seismology obtaining a BSc. at the University of Western Ontario then worked as a 3D seismic processor/programmer for several years. Early 90’s he obtained an MSc with the newly established CREWES project at University of Calgary. He worked on analyzing Ground roll dispersion and some of the early ideas of ground roll removal from P-Sv processing. After working for a mining engineering firm acquiring high resolution seismic in the jungles of Suriname to identify high liquefaction clays, he started his own engineering seismic firm Geophysical Applications (GAPS) in Guelph, Ontario. GAPS acquired high resolution seismic for landfills, exploration for groundwater wells in the SW Ontario, underground storage facilities in Sarnia and Cape Breton, and Kaolin clay delineation in Nova Scotia as well as acquiring large scale O&G exploration projects in NE USA. GAPS was absorbed by a seismic exploration company in western Canada and, for a brief stint, David was hired as the operations geophysicist at Husky Energy where he championed slip-sweep acquisition and began to move groups there into shear wave processing. Recently David took advantage of the downturn in Oil exploration purchased two Envirovibes, built a 3C landstreamer from unused ARAM MkII equipment, then partnered up with Echo Seismic to start a new environmental and engineering division that is promoting shear-shear high resolution seismic. David has a unique combination of data processing, shallow seismic and shear wave seismic knowledge.

    TitleShear landstreamer profiling for dam and levee investigation: Single pass MASW, P- & SH-wave reflection technology

    Recent near surface seismic reflection developments using land-streamer have been commercialized in the Western Canadian by re-purposing former exploration seismic equipment. A 16,000 lb IVI Envirovibe is retrofitted with a 6,000 lb shear vibrator pack that can be rotated to transverse or inline orientation. An exploration ‘ARAM lite’ recording system has been mounted in the cab, 72X10Hz 3 component geophones are mounted on metal sleds spaced 1.5 m apart towed along by a kevlar belt along with vibe electronics and real-time GPS positioning. The high multiplicity and relatively large energy source enable non-intrusive high resolution, quantitative investigations in the range of 3 – 200m depths, not possible with any other geophysical methods.

    Shear wave velocities (Vs), within consolidated rocks, are typically ½ the corresponding compressional or P-wave velocities (Vp) means the Vp/Vs ratios~2). However, within unconsolidated soil materials the ratio of Vp/Vs is often within the range of 6-12. This means vertical resolution of shear wave data within the near surface material, even if recovered frequencies are ½ that of P-wave, are 3 to 5 times higher when time sections are converted to depth. Vp is affected by fluids whereas Vs is not, refraction is dependent on increasing velocities whereas reflection is not. The towed SH landstreamer is ideally suited to earth dam applications and other near surface problems. A combination of seismic methodologies including refraction, P-wave and SH-wave reflection and MASW can be achieved in a single pass. A quick discussion of the theory of these methods, examples of real data and case studies will be presented.


    KEGS OTTAWA APRIL MEETING

    Date:   2020-04-28 @ 4:30pm

    Venuesee below for link

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    Richard Smith gave me a kick in the behind this week to facilitate our April meeting with Tom's presentation. Richard will use his Laurentian account to host a Zoom based presentation. We will meet virtually Tuesday April 28 at our usual time, 4:30, using Richard's Zoom account.

    https://laurentian.zoom.us/j/95149535406?pwd=VytSZ2x6K2d2alFqTHovL2tsUTJ0UT09

    Meeting ID: 951 4953 5406

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    Dial by your location

    Please be sure to mute your microphone when you sign in. We will be accepting written questions throughout the presentation using the chat window.

    I hope to "see" a good turn-out on Tuesday!

    Speaker Tomas Naprstek, National Research Council Canada and Laurentian University (Ph.D. Candidate)

    Bio: Tomas Naprstek completed his B.Sc. in Physics at the University of Waterloo in 2012 and his Geophysics M.Sc. at Laurentian University in 2014. He is in the process of finalizing his Geophysics Ph.D. at Laurentian University which focuses on the interpolation and interpretation of lineaments in aeromagnetic data. Since 2016, he has worked at the National Research Council of Canada. His research there primarily focuses on developing new processing and analysis techniques for remote sensing applications, such as the geolocation of wildfire data and aeromagnetic compensation for unmanned platforms.

    TitleMachine Learning for the Interpolation and Interpretation of Aeromagnetic Data

    Due to the continually lowering barrier for entry of usage, machine learning methods are being applied increasingly in a wide array of fields, and offer a new approach to solving established problems. In this presentation, the potential use of machine learning for aeromagnetic interpolation and interpretation is explored. We investigate interpolation using support vector machines and random forests, and show how their user-driven approach to machine learning enables a small improvement over standard interpolation methods for aeromagnetic data. Following this, convolution neural networks are applied to the interpretation of lineaments in an effort to estimate their strike and depth from aeromagnetic grids. This deep-learning approach requires extensive synthetic data for training; however we show that the method is a powerful tool, and has the potential to quickly and effectively estimate multiple source parameters in entire aeromagnetic grids.

    Upcoming KEGS Ottawa Presentations

    That's it, that's all for now! I hope we will be meeting in person in September - or maybe even for a KEGS Ottawa BBQ later this summer!


  • 5 Apr 2020 3:00 PM | Kanita Khaled (Administrator)

    April Bulletin

    Bulletin Topics:

    • KEGS Toronto Talk: Downhole Physical Rock Properties and Televiewer Measurements - Borehole Data with a Purpose
    • SEG Virtual Lecture
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