Halliburton and AAPG are collaborating to bring to the AAPG community a Hybrid Physics-based deep neural network (DNN) Hackathon.
The objective of this hackathon, designed for domain geoscientists and engineers, is to hack the provided Python® code and develop DNN models for time series predictions of reservoir behavior. Please sign up with your company email address. We will authenticate participation using company email addresses. Download Brochure Hybrid Physics/DNN Integration The use of machine learning in oil and gas is on the rise. Deep learning models while showing a lot of promise have limitations when applied to oil and gas problemsSpecifically these limitations deal with being able to incorporate geoscientists’ understanding of subsurface physics into deep learning models Subsurface physics can be incorporated in one of many ways a subset being:Augmentation of training datasets for deep learning models using data generated by physics driven simulators, including physics-based models as a component in an ensemble of data driven deep learning models formally incorporating domain physics within the deep neural network structure Scope and PrerequisitesDomain meets DNN hackathon is designed for practitioners, data scientists, developers, decision-makers and includes hands-on Python coding experiments. OpenEarth™ Community (OEC) , a cloud-based environment will be provided. For this hackathon, participants will focus on Augmenting provisioned training dataset using a relevant physics based model Modifying and applying supplied algorithm to their own model New to Python Coding? Don't worry! Join us for the pre-event familiarization bootcamp on 16 July as well as leverage our expert team of volunteers at the hackathon. REQUIRED BOOTCAMP WEBINAR: 16 July, from 10 am - 12 noon CDT All participants must participate in the pre-event familiarization boot-camp webinar. The bootcamp will orient participants with Python-coding and OEC environment. You will receive log-in information via e-mail. Hackathon Agenda - 19 July 7.00 am – Doors open 7.45 am – Welcome and Introduction, Susan Nash, Director of Innovation, Science, and Technology, AAPG / Patrick Ng, AAPG Deep Learning TIG / Rekha Patel, Halliburton 8.15am – Hackathon Overview – Steve Ward, Chief Advisor8.30am Hackathon Begins – Srinath Madasu, Technical Advisor9.30 am Coding for the Scope 1 Starts12.00 – Lunch 1.00 pm – Coding for Scope 2 Starts3.30 pm – Presentations/Judging5:00 pm – Awards & Networking Thank you to our sponsors: Prizes Sponsor: Amazon Web Services Catering Sponsor: Petrabytes Patron-Level Sponsor: ExxonMobil Patron-Level Sponsor: DataVediK Hackathon Hosted by: