Data Analytics Session TBC

Data Analytics Session TBC

04 Sep 2018, 15:45 - 17:15

Crombie A
Language:
English

Session Title: Data Analytics Session TBC

Session Moderator:

Satyam Priyadarshy, Technology Fellow & Chief Data Scientist, Halliburton

This session is to introduce a number of actual examples for companies pushing on in the data analytics space.


1545-1615 - 
Our journey and how we have set ourselves up to deliver at scale in the data analytics space.

Dan Jeavons, General Manager, Data Science, Shell


1615-1645 - 
Image Analysis derived from Autonomous Inspection  

Nick Hayward and Mike Atkins, Total

Abstract

TOTAL and Merkle Aquila are undertaking proof of concept projects to perform image analysis on asset integrity data collected by autonomous systems and IoT devices. The aim is to better understand the feasibility of these methods, and to demonstrate the benefits of robotic inspection with regard to improved safety, enhanced data capture and reduced operational costs.

This data science project is being undertaken in parallel with the OGRIP project (Offshore Ground Robotics Industrial Pilot), which is an 18 month industrial pilot by TOTAL in collaboration with Taurob, building upon the success of the ARGOS challenge (www.argos-challenge.com).

To facilitate the data science, a fundamental aspect of the project is the development of the technical architecture, enabling the transfer of data from the OGRIP robot and other IoT devices into a managed data store in a cloud computing environment.

The image analysis work involves the development of machine learning models that can perform a number of tasks, and allow for the inclusion of additional data types such as infrared and gas detection imagery. Broad tasks include

•Object detection to locate equipment in the industrial environment

•Anomaly detection across different pieces of inspected equipment

The project will be introduced, touching on progress to date, with a view towards exciting results in the second half of 2019.

 

1645-1715 - Big Data, Machine Learning, and Well Integrity: Applications to Real World Problems

Marcus Savini, R&D Manager, Strategic Technology Group

As the Oil and Gas industry moves towards digitisation and data-driven operations, users are faced with new challenges; mainly, effectively presenting and acting upon the wealth of data created. In the course of most discussions surrounding this topic one will almost certainly encounter the terms “Big Data” or “Machine Learning.” But what are these technologies, truly, and how might one leverage their power to promote well integrity, reliability, and efficiency? The proposed presentation will address these, and other related questions. Going beyond simple definitions, the proposed article aims to present clearly defined levels of system integration along with real world use cases to maximise potential benefit from the perspective of a service company. 

Contributors

  • Dan Jeavons

    Speaker

    General Manager, Data Science

    Shell

    Dan is passionate about innovation from data & analytics (a recurring theme throughout his career) but also has extensive experience in business...

  • Nick Hayward

    Speaker

    Total

  • Marcus Savini

    Speaker

    R&D Manager

    Strategic Technology Group

    Obtained a bachelor’s degree in computer science from the University of Louisiana at Lafayette in 2003 and shortly thereafter began work at Franks...

  • Dr Satyam Priayadarshy

    Moderator

    Technology Fellow & Chief Data Scientist

    HALLIBURTON

    Dr. Satyam Priyadarshy is a pioneer in the fields of data science, big data, analytics, and emerging technologies. Dr. Priyadarshy is the first Chief...

We use cookies to operate this website and to improve its usability. Full details of what cookies are, why we use them and how you can manage them can be found by reading our Privacy & Cookies page. Please note that by using this site you are consenting to the use of cookies.