PESA QLD: Online Course – Data Science E&P Bootcamp – 2021 – Expressions of Interest
Monday, 5 July @ 12:30 pm - 4:30 pm (Australia/Brisbane time)Free
Data Science E&P Bootcamp
We live in Industry 4.0 era, which relies on Big Data Analytics. For meaningful Big Data Analytics, we need experienced and knowledgeable Data Scientists. However, there is lack of talent globally, on the other hand, there are very experienced domain experts in organizations. We can transform that talent to think, work, and create value like Data Scientists and add to their skill set, Data Science skills easily, through proven SMART approach to talent transformation. In last two years, we have graduated 400+ professionals globally that use Data Science in their jobs now. Our approach leveraged highly contextualized, customized, high-speed bootcamp/workshops with a balanced theoretical and hands-on experience, focused on the Oil & Gas industry.
Halliburton Big Data Centre of Excellence Data Scientists
No previous programming experience is required. Training will be delivered online, so you will need access to a modern computer with a stable internet connection. Anaconda (Python 3.7) will be required to be downloaded and installed (also Orange is optional).
Any additional packages or changes will be instructed accordingly.
5 days of 3 Hour long sessions (except first day, this session will be 4 hours). Data for various exercises will be provided.
We will leverage tools like Python, Orange, Power BI, Opensource Visualizations, etc. for the hands-on (depending on the requirement of the hands-on exercises).
Installations/configurations of Tools/Technologies Reading materials / Videos links will be provided.
Required Course material will be shared during and after the Workshop.
A maximum of 18 attendees will be accepted.
This course will only proceed the required numbers are reached through EOI.
EOI will be open until COB Friday 18th June.
Please register by booking a free ticket below to avoid disappointment.
|Presentation:||Data Science E&P Bootcamp Online Course 2021|
|Venue:||Participants will be provided with a MS Team link. Trainers will be broadcasting from
|Date & Time:||Session 1 – Mon July 5, 1:00-5:00pm (AEST)
Session 2 – Tue July 6, 1:00-4:00pm (AEST)
Session 3 – Wed July 7, 1:00-4:00pm (AEST)
Session 4 – Thu July 8, 1:00-4:00pm (AEST)
Session 5 – Fri July 9, 1:00-4:00pm (AEST)
|Cost:||Only payable on registration once course is confirmed
PESA Members: $950.00
Non- Members: $1150.00
Student/Retired Members (max 2): $750.00
Data Science E&P Bootcamp Online Course 2021
Session #1: General Theories of Data Science Including O&G Case Studies and Basic Theories of Artificial Neural Networks (4 hours)
This session will introduce the participants to data sciences, machine learning and artificial intelligence in the light of energy industry. The focus will be on the concepts of different machine learning techniques and algorithms in general. Additionally, a few real case studies applicable to solve energy industry problems will be discussed to make participants understand the concepts. Also, the session will discuss artificial neural networks (ANN) concepts to the participants, as ANN finds numerous applications for AI/ML driven solutions implementation. This session caters the conceptual understanding of different architectures of neural networks, namely, CNN, RNN, MLP, etc.
Session #2: Exercise – Facies Classification trough Data Driven Well Log Analysis (3 hours)
Supervised / Unsupervised approach will be used in this hands-on exercise for facies interpretation using well log data. Facies classification finds a valuable application to determine the reservoir or non-reservoir facies. Data driven approach will emphasise the value addition besides conventional petro-physical approach of solving a similar problem.
Session #3: Exercise – Well Log prediction from Seismic Attributes (3 hours)
A supervised machine learning technology will be used for synthetic log generation in this exercise. A novel approach will be discussed in this exercise, so the participants can generate their own synthetic log. These logs can be used further for static reservoir modelling. This exercise will also help the participants to understand the hyper-parameters of model tuning aspects.
Session #4: Exercise – Fossil Classification through Computer Vision Image Analysis (3 hours)
Computer vision will be used to do some image analysis of fossils. This supervised method can be very useful for the participants for implement the similar model for well core sections for identifying biomarkers or do bio-stratigraphic interpretation.
Session #5: Exercise – Short Term Production Prediction through Machine Learning Model (3 hours)
Prediction of the oil or gas production is the key for successful hydro-carbon business. Machine learning based approach finds a very good application in this scenario. In this exercise, the participants will earn about the concept of time series analysis and ANN will be used to predict the gas rate for time series data.
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