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International

3rd Asia Pacific meeting on near surface geoscience and engineering

Wednesday, November 4, 2020
0800
1700

Welcome to the 3rd Asia Pacific Meeting on Near Surface Geoscience & Engineering

2 - 4 November 2020, Chiang Mai, Thailand

The European Association of Geoscientists & Engineers (EAGE) is excited to announce that the 3rd Asia Pacific Meeting On Near Surface Geoscience & Engineering event is coming to Chiang Mai, Thailand. We look forward to welcome all of you to join us in beautiful Thailand in November 2020.

Abstracts submission is now closed and papers' reviewing are on-going.

This event was originally planned on 20 - 22 April 2020 and postponed to 2 - 4 November 2020! 

 

Please click here to view the event.

Important Dates

Abstract Submission Deadline30 June 2020

Registration Open1 January 2020

SEGJ Seminar4 November 2020

ERT Short Course4 November 2020

3rd NSGE Conference2 - 3 November 2020

EAGE Geo-Quiz3 November 2020

Field Trip- Doi Inthanon National Park1 November 2020

3rd Asia Pacific meeting on near surface geoscience and engineering

Tuesday, November 3, 2020
0800
1700

Welcome to the 3rd Asia Pacific Meeting on Near Surface Geoscience & Engineering

2 - 4 November 2020, Chiang Mai, Thailand

The European Association of Geoscientists & Engineers (EAGE) is excited to announce that the 3rd Asia Pacific Meeting On Near Surface Geoscience & Engineering event is coming to Chiang Mai, Thailand. We look forward to welcome all of you to join us in beautiful Thailand in November 2020.

Abstracts submission is now closed and papers' reviewing are on-going.

This event was originally planned on 20 - 22 April 2020 and postponed to 2 - 4 November 2020! 

 

Please click here to view the event.

Important Dates

Abstract Submission Deadline30 June 2020

Registration Open1 January 2020

SEGJ Seminar4 November 2020

ERT Short Course4 November 2020

3rd NSGE Conference2 - 3 November 2020

EAGE Geo-Quiz3 November 2020

Field Trip- Doi Inthanon National Park1 November 2020

3rd Asia Pacific meeting on near surface geoscience and engineering

Monday, November 2, 2020
0800
1700

Welcome to the 3rd Asia Pacific Meeting on Near Surface Geoscience & Engineering

2 - 4 November 2020, Chiang Mai, Thailand

The European Association of Geoscientists & Engineers (EAGE) is excited to announce that the 3rd Asia Pacific Meeting On Near Surface Geoscience & Engineering event is coming to Chiang Mai, Thailand. We look forward to welcome all of you to join us in beautiful Thailand in November 2020.

Abstracts submission is now closed and papers' reviewing are on-going.

This event was originally planned on 20 - 22 April 2020 and postponed to 2 - 4 November 2020! 

 

Please click here to view the event.

Important Dates

Abstract Submission Deadline30 June 2020

Registration Open1 January 2020

SEGJ Seminar4 November 2020

ERT Short Course4 November 2020

3rd NSGE Conference2 - 3 November 2020

EAGE Geo-Quiz3 November 2020

Field Trip- Doi Inthanon National Park1 November 2020

ASEG Webinar - SA/NT Branch: Searching for the Beaumont Children and Other Adventures in Unmarked Grave Detection

Tuesday, June 2, 2020
1230 AEST
1330 AEST

Branch hosting the event: SA/NT

Title: Searching for the Beaumont Children and Other Adventures in Unmarked Grave Detection

Presenter: Dr Ian Moffat

Date: Tuesday 2nd June 12:30 pm AEST

 

Abstract:

The reliable detection of unmarked graves is one of the most important challenges faced by community groups, industry and law enforcement agencies. Burials are ubiquitous in the archaeological and forensic record however these features are challenging to locate with conventional techniques. Geophysical methods are often used for this purpose due to their non-invasive nature and rapid site coverage however graves remain a difficult target due to their subtle response and small size. This presentation reviews a number of grave detection projects, including the search for the Beaumont Children and mapping WWII graves from the Battle of Tarawa, to discuss current best practice in this field.

Bio:

Ian Moffat is an ARC DECRA Senior Research Fellow in Archaeological Science at Flinders University where he undertakes research in the application of earth science techniques in archaeology. He has previously held research positions at the University of Cambridge and the Institute for Mediterranean Studies. Ian holds a PhD from the ANU and a BA and BSc (Hons) from UQ. In addition to his academic career he has worked at Ecophyte Technologies, Precipice Training and Archaeometry Pty Ltd.

 

NSW webinar - Geophysical Characterisation for the Dredging of the Marine Industry Park, Darwin

Wednesday, May 20, 2020
1800 AEST
1900 AEST

The NSW Branch of the ASEG invite you to join us on ZOOM for the next talk in the ASEG Webinar Series. 

Please join us on Wednesday 20th May, 6:00 pm (AEST) for a talk by Simon Williams from GBG Australia.

Geophysical Characterisation for the Dredging of the Marine Industry Park, Darwin

This presentation covers the use of multiple marine geophysical methods to help characterise the geology and geotechnical challenges for preliminary design of dredged access channels to a proposed marine industry development site in Darwin Harbour. The main geophysical methods utilised to characterise the geological materials where single-channel seismic reflection and densely spaced continuous marine seismic refraction. 

Please bring your own drinks and nibbles.

 

Register Now: https://us02web.zoom.us/webinar/register/WN_HN4mk5BkQxW3bMGrvthdSw  

After registering, you will receive a confirmation email containing information about joining the webinar. Contact secretary@aseg.org.au if you have any questions. 

Update structural Models in Real Time using Machine Learning

Thursday, June 25, 2020
8 AM US Central Time
9 AM US Central Time

Date

Time (AWST)

Time (ACST)

Time (AEST)

25/06/2020

21:00:00

22:30:00

23:00:00

https://seg.zoom.us/webinar/register/WN_IkCzXT6aT8mE5qY_3YR0yg

Topic

Update structural Models in Real Time using Machine Learning

Description

This presentation and demonstration will focus on a machine learning workflow in the upstream Oil and Gas domain to predict formation tops by applying artificial intelligence and machine learning techniques to learn the well logs signatures. This deep learning model provides high quality predictions to aid the geologists in picking lithology markers consistently and in an accelerated fashion thus boosting their operational efficiency. The self-learning model, which is a unique differentiator of dataVediK and encompasses the detection of outliers and data quality issues and their subsequent validation and suggested corrections to improve the quality of data in an automated fashion during the model training process. The demo will then showcase a real-time drilling solution built using this ML model, whereby the formation tops are predicted, and the structural model is updated automatically as the GR log is acquired.

Time

Jun 25, 2020 08:00 AM in Central Time (US and Canada)

Simple Applications of Machine Learning in Subsurface Characterization

Thursday, May 28, 2020
8 AM US Central Time
9 AM US Central Time

Date

Time (AWST)

Time (ACST)

Time (AEST)

28/05/2020

21:00:00

22:30:00

23:00:00

https://seg.zoom.us/webinar/register/WN_Fc-YD7ScSZevv-Nw4iN7xw

Topic

Simple Applications of Machine Learning in Subsurface Characterization

Description

Dr. Misra will present few case studies on the use of machine learning techniques. In the first case study, neural network models generate NMR T2 distribution in the absence of NMR logging tool. In the second case study, simple data-driven models generate compressional and shear travel time logs in the absence of sonic logging tool. In the third case study, machine learning assisted the segmentation of SEM images of shale samples. This segmentation method involves two steps, feature extraction from SEM images followed by random forest classification of each pixel in the SEM image. In the fourth case study, machine learning was used to process CT scan images to predict the subsurface geomechanical properties.

Time

May 28, 2020 08:00 AM in Central Time (US and Canada)

You can build your own models: Why you don't need to be scared of doing your own data science

Thursday, April 30, 2020
8 AM US Central Time
9 AM US Central Time

Date

Time (AWST)

Time (ACST)

Time (AEST)

30/04/2020

21:00:00

22:30:00

23:00:00

https://seg.zoom.us/webinar/register/WN_TfNBjh2dRBahnusg623fMQ

You can build your own models: Why you don't need to be scared of doing your own data science

Description

There are two ends of the "AI" spectrum that are often presented. On one end, AI is going to solve the world's problems one slide deck at a time. On the other, a PhD physicist will give you a "quick" run-through of a 4-hour deep learning with tensorflow in Python tutorial. In this session, we aim to land right in the middle of those two and provide a layman's view to getting started with data science and machine learning. Almost everyone has data and problems, but many don't have the expertise in technologies like Python or R to feel confident in getting started with machine learning. In this session, we will aim to help you better understand the concepts used in machine learning, how to set up problems, how to analyze and interpret your data, and finally, how to build models that can drive business value without ever needing to know Python or R.

Time

Apr 30, 2020 08:00 AM in Central Time (US and Canada)

The Fundamentals of Microseismic Monitoring

Wednesday, April 22, 2020
12 PM US Central Time
1 PM US Central Time

Date

Time (AWST)

Time (ACST)

Time (AEST)

23/04/2020

01:00:00

02:30:00

03:00:00

https://seg.zoom.us/webinar/register/WN_EtdnImjCTFWdRc2teFvWIw

Topic

The Fundamentals of Microseismic Monitoring

Description

In this webinar, participants will be exposed to the fundamental concepts of microseismic acquisition, processing, and interpretation in unconventional reservoirs. Through understanding the fundamental concepts of earthquake seismology, the common pitfalls and best practices within the industry associated with this technology are discussed.

Time

Apr 22, 2020 12:00 PM in Central Time (US and Canada)

Automating seismic data analysis and interpretation

Tuesday, May 12, 2020
11 AM (US Central Time)
12 PM (US Central Time)

Date

Time (AWST)

Time (ACST)

Time (AEST)

13/05/2020

00:00:00

01:30:00

02:00:00

https://www.knowledgette.com/p/automating-seismic-data-analysis-and-inte...

 

Format: Virtual Webinar. 45 min. presentation followed by 15 min. Q&A

Please note that two sessions will be given at different dates listed below.

Session 1, Wednesday, April 22, 2020, 8 pm to 9 pm US Central Time Register Here

Session 2, Tuesday, May 12, 2020, 11 am to 12 pm US Central Time Register Here

 

Abstract:

Recent developments in artificial intelligence and machine learning can automate different tasks in data analysis. I will discuss the quest for automation by tracking the development of automatic picking algorithms, from velocity picking in seismic processing to horizon picking in seismic interpretation. We will search for the limits of automation to discover the distinguishing qualities that separate human geophysicists from machines.

The automatic picking algorithm follows the analogy between picking trajectories in images with variable intensities and tracking seismic rays in the subsurface with variable velocities. Picking trajectories from local similarity panels generated from time shifts provides an effective means for measuring local shifts between images, with practical applications in time-lapse and multicomponent image registration, matching seismic with well logs, and data compression using the seislet transform. In seismic interpretation, automatic picking finds additional application for tracking fault surfaces, salt boundaries, and other geologic features.

The power of automatic picking is further enhanced by novel deep learning algorithms. The deep learning approach can use a convolutional neural network trained on synthetically generated images to detect geologic features in real images with an unmatched level of performance in both efficiency and accuracy. The lessons to learn from these developments include not only the potential for automation, harvested through artificial neural networks and modern computing resources, but also the potential for human ingenuity, harvested through professional networks.

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