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ACE SC 8 | Beginner's Guide to Unstructured Data and Machine Learning in Oil and Gas

American Association of Petroleum Geologists (AAPG)

Sunday, 7 June 2020, 8:00 a.m.–5:00 p.m.  |  Houston, Texas

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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

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. This course does not require any use of computers.

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.
Fee:
$400 Professionals
$100 Students
Limit:
40 People
Educational Credits:
0.8 CEU
Includes:
An open mind
Willingness to actively participate in group exercises
Course Materials
Refreshment Breaks

Venue

ACE SC 8 | Beginner's Guide to Unstructured Data and Machine Learning in Oil and Gas
George R. Brown Convention Center
1001 Avenida De Las Americas
Houston, Texas 77010
United States
(713) 853-8000

Instructor

Instructors

AAPG Instructor  
Inly

ft-sc important notes


Important notes regarding Field Trips and Short Courses

  • Before purchasing non-refundable airline tickets, confirm that the Field trip and/or Short course will take place as they may be cancelled if undersubscribed.
  • Please register before 22 April 2020. Field trips and/or Short courses cancellations, due to low enrollment, will be considered at this time. No refunds will be allowed after 22 April 2020.
  • Field trips and Short courses are limited in size and are reserved on a first-come, first-served basis and must be accompanied by full payment.
  • If you do not plan on attending the convention, a U.S. $30 enrollment fee will be added to your Field trips and Short courses fee. This fee may be applied towards your registration should you decide to attend the convention at a later date.
  • A wait list is automatically created if a Field trip or Short course sells out. The AAPG Global Convention Department will notify you if space becomes available.
  • AAPG will continue to take registrations for Field trips and Short courses that are not cancelled until they are either sold out or closed.
  • It is important that you note your gender when registering for hotel room assignments.
  • For Field Trips, you will receive an itinerary with details of meeting points, transportation with the trip phone numbers and email addresses of hotels and trip leaders prior to the event date.
  • Proper clothing and supplies are needed for the outdoors (hat, windbreaker, sturdy footwear and backpack).
  • Depending on location, temperatures can range from 40 to 70 degrees Fahrenheit with or without rain. Participants are advised to check local weather forecasts for latest updates.
  • Insect repellent and sun protection (sunscreen and hats) are recommended.
  • AAPG, the sponsoring organizations nor Field Trip leaders and their employers maintain insurance covering illness or injury for individuals.

Students

There are a limited number of discounted registrations available for students on a first-come, first-served basis. If a discounted space is still available, it will show up during the online registration process. If discounted spots are no longer available, you may register at the full fee; if we are able to add additional discounted spots, we will refund the difference at that time.