Webinar and In-person: An Introduction to Supervised Machine Learning

Short abstract:

In this talk, we will gently introduce the concepts of machine learning, so there is no need for any prior experience to attend this presentation.  We will focus on supervised machine learning where we train a mathematical model to learn relationships from past data to predict future data.  This is the first talk in a series of supervised machine learning talks and so we will focus on the foundations.  We will present how machine learning is applied in Equinor through a specific case called “Real Time Fluid Identification” where we use historical data from PVT tests and advanced mud gas data to help predict the gas oil ratios to support subsurface teams on real-time drilling decisions.  We will also cover a case example of supervised machine learning in your everyday life.  Using this business example and a case from our daily lives, we will “look under the hood” on how machine learning actually works and what makes it work well.  By the end of this talk we hope to have demystified the “buzzword” of machine learning and prepare you for the next talks in the series which will go into more depth on different types of machine learning applications, such as to time-series data, images, and language.

Bio presenter 1:

Elliot Humphrey is a Data Scientist at Equinor, working on creating data-driven solutions to solve subsurface challenges. He has a PhD in Geology and enjoys working in teams that support decision making through the use of spatial data science and machine learning.

Bio presenter 2:

Margarete Kopal is a Petrophysicist at Equinor.  She received her M.Sc. in Geology 2003 from the TU Bergakademie Freiberg, Germany. Margarete joined Equinor as a Principal Petrophysicist in 2013, before becoming an Engineer for Reservoir Technology by changing scale from logs to core plugs within the Special Core Analysis group. Margarete’s interests include data processing and data science to extract and unlock rock and fluid properties, as reflected by her various professional assignments.

FORCE seminars have previously been fully booked with waiting lists so you are encouraged to sign up as soon as you know you will attend.

 Participation fees:

FORCE members: Free
Non-members: NOK 1000,- / 500,- (webinar)
University: Free
Student: Free

How a webinar works

You register as usual through the registration button above. Once you are registered you will get an invitation via email to join this webinar. 
FORCE uses Teams Video for this webinar, and has proven to work successfully. 

We recomment that everyone joining turn off their camera and microphone when joining.
If you have any questions you can use the chat or wait until the end of the talk.

FORCE seminars have previously been fully booked with waiting lists so you are encouraged to sign up as soon as you know you will attend.

Once you have registered, you will receive an outlook invitation with the Teams link. You will receive the link a few days prior to the webinar. 
You cannot forward the link to people who is not registered. 

Important information:
You can register as a FORCE member and pay "FORCE member" price if you are an employee of a member company.
All FORCE member companies are listed here.

Payment is made online by credit card. Please note that no refunds will be given after you have signed up. If you for any reason can not attend the workshop, you are welcome to send a representative, just inform Linn Smerud as soon as there are changes.