09 June, 2020 Tulsa Oklahoma United States Virtual

American Association of Petroleum Geologists (AAPG)

Beginner's Guide to Unstructured Data and Machine Learning in Oil and Gas

9 June 2020
  |  
Virtual Event

 

Who Should Attend
This course is for people from the oil and gas industry without a background in machine learning, software engineering, or data science.
Objectives
To gain an understanding of what unstructured data is, its value, how it can be utilized, and its value to the oil and gas industry.
Course Content

Course will be held via Zoom: 9 June 2020, 9:00 am5:00 pm (CDT)

Now Available for Web-Participation
Originally scheduled to take place in person at ACE 2020 in Houston, this short course will now be held separately a stand alone event and will be available for online participation only.

This course is for people without a background in machine learning, software engineering, or data science. The purpose of the course is to help people who are immersed in the oil and gas industry to gain a practical understanding of what unstructured data is, what value there is in it, how it can be utilized, and why this is now relevant. Much of unstructured data mining is based on machine learning, so this course also seeks to instill memorable intuitive understanding of machine learning.

The course consists of these segments:

  1. The differences between structured and unstructured data will be explored, and emphasis will be placed on why unstructured data is crucial to firms in the oil and gas industry. The drastic inefficiencies created by mismanagement of unstructured data will be given context by the growth in private equity backing, the lower hydrocarbon price environment, the proliferation of data sources, and the aftermath of the big crew change.
  2. Attendees will engage in an interactive simulation of a typical oil and gas workflow involving structured and unstructured data.
  3. Incumbent solutions, including data file structuring projects and off-the-shelf enterprise search tools, will be considered. Each will be evaluated based on its ability to return accurate and relevant information to users in a useful format and at speeds that do not inhibit seamless operations.
  4. Attendees will engage in an interactive simulation of each of the two typical incumbent solutions to handle unstructured data.
  5. The basics of machine learning will be explained in simple and intuitive terms, including a few examples.
  6. Attendees will engage in an interactive application of machine learning to solve a problem. This application will be a simulation not requiring the use of any electronics.
  7. Three case studies will be explored showing results and highlighting value added of a new (to oil and gas) class of solution. The first study involved implementation of a tool to help workers navigate historical reports to extract knowledge to make better decisions in real time. The second study involved implementation of a tool to serve as a surrogate for a retiring subject matter expert so that less experienced employees could still get good answers to questions. The third case study has not been completed, yet, but it involves simply using a tool to automatically fill out missing fields in a database from data scattered across unstructured reports.
$400
$400
Expires on
09 June, 2020
Professional Fee
$100
$100
Expires on
09 June, 2020
Student Fee
40 People
Limit
0.8 CEU
CEU
  • The Zoom Link for this course will be included in your Registration Confirmation. 
  • Cancellations received on or before 18 May 2020 will be refunded less a $50 processing fee
  • Refunds will not be issued after 18 May 2020 or for "no shows."
  • You may substitute one participant for another. Cancellations or substitution requests should be emailed to Customer Service at customerservice@aapg.org.
Includes:
  • Course Materials
Technical Requirements:
  • Personal Computer
  • Internet Access
AAPG Headquarters
1444 S Boulder Avenue
Tulsa Oklahoma 74119
United States
+1 918 584 2555
Tulsa, OK - AAPG Tulsa, OK - AAPG Virtual 57035 AAPG Headquarters

Accommodation information is not yet available for this event. Please check back often.

 

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AAPG Non-endorsement Policy

The American Association of Petroleum Geologists (AAPG) does not endorse or recommend any products and services that may be cited, used or discussed in AAPG publications or in presentations at events associated with AAPG.