General Description

  • General Objective

    The twelve modules cover a repeatable and scalable set of AI workflows using spatial and time series upstream data sets. I introduce the different ML and DL techniques, supervised, unsupervised, and reinforcement learning workflows. We explore the critical data QC steps to provide a robust and comprehensive dataset for AI modeling. There is a module dealing with DL techniques, CNNs, and RNNs.

  • Audience

    Its content will be very useful to people involved in production optimization, production technology, supervision and management, field personnel.

  • Dedication

    Completion time: 7 hours. It includes the dedication corresponding to complementary reading and evaluations.

Program Content

  1. 1

    • Instructor Presentation

    • Introduction to the Course
  2. 2

    • 1.1 - Introduction: Data-driven Geophysical and Petrophysical modeling using AI techniques

    • 1.2 - Complementary Material (Downloadable)
  3. 3

    • 2.1 - Exploratory Data Analysis: Upstream Data Exploration and Explanation

    • 2.2 - Complementary Material (Downloadable)
  4. 4

    • 3.1 - Data Preparation for AI: Upstream Data Argumentation and Feature Engineering

    • 3.2 - Complementary Material (Downloadable)
  5. 5

    • 4.1 - Machine Learning Techniques: Supervised and Unsupervised in E&P

    • 4.2 - Complementary Material (Downloadable)
  6. 6

    • 5.1 - Deep Learning Techniques: Upstream E&P Deep Learning

    • 5.2 - Complementary Material (Downloadable)

    • 5.3 - Content Evaluation #1
  7. 7

    • 6.1 - Case Studies: Completion Strategy and Automated Tops

    • 6.2 - Complementary Material (Downloadable)
  8. 8

    • 7.1 - Case Studies: Seismic Attributes

    • 7.2 - Complementary Material (Downloadable)
  9. 9

    • 8.1 - Case Studies: Drilling Program & Completion Study and Virtual Assistant for Fluids and Lithology

    • 8.2 - Complementary Material (Downloadable)
  10. 10

    • 9.1 - Case Studies: Forecasting Principles & Production Forecasting Techniques

    • 9.2 - Complementary Material (Downloadable)
  11. 11

    • 10.1 - Case Studies: Time-Series Analysis and Production Forecasting

    • 10.2 - Complementary Material (Downloadable)
  12. 12

    • 11.1 - Digital Twins: Upstream E&P

    • 11.2 - Complementary Material (Downloadable)
  13. 13

    • 12.1 - PINNs: Physics-Informed Neural Networks & Explainable AI and Generative AI

    • 12.2 - Complementary Material (Downloadable)

    • 12.3 - Content Evaluation #2
  14. 14

    • Closure
  15. 15

    • Course Manual - Downloadable

Instructor

Senior Instructor

Keith Holdaway

Fourteen years of experience in the Oil and Gas industry as a geophysicist processing and interpreting seismic data. More than 11 years of software development experience with SAS Institute, Inc., a statistical software and analytics solutions leader. Ten years of upstream Oil and Gas data-driven model building across Exploration and Production. I am developing business strategies to establish Analytical Centers of Excellence and data management architectures across the Oil and Gas industry.

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