Petroleum Systems Risk Assessment: Providing Quantitative Insights Through the Combination of Modelling and Machine Learning Techniques

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Disciplines: Data Science and Engineering Analytics | Management

Course Description

This course will cover key aspects of a quantitative and (more) objective petroleum risk assessment – a cornerstone for robust decision-making.

The course begins with an overview of petroleum systems and traditional qualitative risk assessment methodologies (table-based, Italian flags…). Then, after describing some limitations of such traditional techniques, it presents a novel approach embedding petroleum systems modelling, to integrate the current state of geological knowledge, and machine learning techniques, to build quantitative and objective risk assessments. Fundamentals of petroleum system modelling will be presented as well as techniques to identify and quantify remaining geological uncertainties. A session is dedicated to the presentation of the machine learning strategy followed to perform the analysis robustly and in an operational timeframe. The last part of the course concentrates on the presentation of an application case-study in the Levant Basin, Eastern Mediterranean.

No other course covers the future of petroleum systems risk assessment and offers insights on the combination of machine learning techniques with modelling to enhance risk assessment for petroleum exploration.

Learning Level

Introductory to Intermediate

Course Length

1 Day

Why Attend

At the end of the course attendees will have:

1. An understanding of the basis of Petroleum systems analysis
2. Knowledge on integration of uncertainties in petroleum system models and methods to perform quantitative and robust risk assessment
3. Understanding of the machine learning techniques used to perform risk assessment through physics-based simulations.

Who Attends

Explorationists and petroleum geologists involved in prospect and play assessments, basin modelers and petroleum system analysts, exploration managers and exploration decision-makers.

CEUs

0.8 CEUs are awarded for this 1-day course.

Cancellation Policy

All cancellations must be received no later than 14 days prior to the course start date. Cancellations made after the 14-day window will not be refunded. Refunds will not be given due to no show situations.

Training sessions attached to SPE conferences and workshops follow the cancellation policies stated on the event information page. Please check that page for specific cancellation information.

SPE reserves the right to cancel or re-schedule courses at will. Notification of changes will be made as quickly as possible; please keep this in mind when arranging travel, as SPE is not responsible for any fees charged for cancelling or changing travel arrangements.

We reserve the right to substitute course instructors as necessary.

Instructors