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PESA WA: July Technical Lunch – Data-Driven Analytics for Petroleum Well Logs Interpretation

Thursday, 18 July, 2019 @ 12:00 pm - 2:00 pm


Guest Speaker: Dr. Irina Emelyanova

Dr. Irina Emelyanova leads the team of Geoscience Data Analytics (GDA) at CSIRO Energy.  She is a Mathematician by training with extensive experience in the development of data-driven solutions for time series prediction, spatiotemporal data modelling, data fusion and pattern recognition. Through advanced analytics, the GDA team develops novel data analytics solutions for improving representation of vertical and spatial heterogeneity of subsurface in geophysical and petrophysical models.

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PESA WA invites you to our July technical luncheon with guest presenter Dr. Irina Emelyanova from CSIRO Energy.

“Data-Driven Analytics for Petroleum Well Logs Interpretation”

Presented by Dr. Irina Emelyanova


The modern world is experiencing a paradigm shift how we store, process and analyse data sets due to the boom driven by Big Data. Data-intensive science is considered to be the fourth paradigm of science these days. It is seen as a data-driven style of science, where Artificial Intelligence (AI) tools including Machine Learning (ML) are heavily used to help specialists to manage, analyze, and share data.

This talk will overview the key AI and ML mathematical concepts by clarifying the meaning of the buzz words; explaining the key algorithms in simple terms and highlighting their advantages and limitations. Several examples of AI and ML applications for well log data interpretation developed by the Geoscience Data Analytics team form CSIRO Energy will be presented to demonstrate the value of data-driven solutions for subsurface characterization.

Talk Outline:

1. Big data and Data-driven analytics:

– Big data revolution (what and why; new algorithms needed)
– Paradigm shift (four science paradigms; data intensive science emerged)
– Data-driven analytics (terminology, methods and main players)

2. Artificial Intelligence methods overview (theory explained in simple terms, advantages and limitations):

– Supervised (Artificial Neural Networks, Support Vector Machines, Boosted Decision Trees, Random Forest)
– Unsupervised (k-means, Self-Organising Maps, Spectral Clustering)
– Ensemble and deep learning (definitions and methods)

3. Examples of data-driven solutions for oil and gas applications:

– Supervised prediction of total organic carbon from core and log data
– Unsupervised identification of electrofacies from well logs
– Semi-supervised hierarchical clustering of well logs for characterization of continental sandstones
– Seismic – well log data integration for prediction of geological facies from seismic data


Ticket Prices:

Member (Early Bird): $69.00

Concession Member [Retired, Graduate or Hardship] (Early Bird): $59.00

Student Member (Early Bird): $39.00

Non-Member: $99.00

Early bird pricing ends Monday 15th July at 5pm (AWST).
Member (Non-Early Bird): $79.00.

All ticket sales close at 5pm (AWST) Tuesday 16th July.

Refund Policy: Refunds are only applicable if notified in writing to WA-secretary@pesa.com.au prior to the close of ticket sales.


Thursday, 18 July, 2019
12:00 pm - 2:00 pm
Event Categories:
  • Venue

    Parmelia HIlton
    14 Mill Street
    Perth, WA 6000 Australia
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