This webinar features a 45-minute presentation by Dr. Carrie Laudon (CV below). An interactive Q&A with Dr. Laudon will follow her presentation.
The webinar will be held two times. See the time of the webinar in your region.
Title: Identify Reservoirs by Combining Machine Learning, Petrophysics, and Bi-variate Statistics
Presenter: Dr. Carrie Laudon
Date: Tuesday/Wednesday, 1/2 June 2021
What you will learn in this webinar:
Set up petrophysical properties as a discrete categorical variable to apply bi-variate statistics.
Test the statistical relationship between machine learning neurons and reservoir properties.
Generate histograms of machine learning neurons and petrophysics to identify reservoirs.
Apply the machine learning classification results to stratigraphic analysis and prediction.
The tools of machine learning, petrophysics, well logs, and bi-variate statistics are applied in an integrated methodology to identify and discriminate reservoirs with hydrocarbon storage capacity. While the use of any one of these methods is familiar, their application together is unique. The webinar presents the process and results from two different geologic settings:
Conventional: Channel slope and fan facies environments offshore Mexico
Unconventional: Niobrara chalk and shale formation in the U.S.