2023 SPE Europe
Starting on October 2, 2023
Is your Company interested to support the organization and delivery of the 2023 SPE Europe Energy GeoHackathon? Click HERE
The Energy GeoHackathon
The SPE Europe Energy GeoHackathon aims at educating and disseminating knowledge to all the participants on how Data Science applications can support Geothermal Energy Developments and drive the Energy Transition.
The event is organized by a diverse team of volunteers from different SPE Sections in Europe and from International Technical Sections moved by the desire to “make the Energy Transition happen” in a datafied and sustainable way.
A formal registration and the payment of a ticket is required to participate to SPE Europe Energy GEOHackathon.
Bootcamps (October 2023)
A four-week bootcamp sessions on data science and geothermal energy will begin on October 2, 2023. Data scientists and industry experts will deliver weekly sessions to equip participants with the relevant technical knowledge to understand the challenge and be ready for the Hackathon.
▪ Non-SPE Members: €35
▪ SPE Members & Geothermal Professionals : €25
▪ SPE Students, Unemployed, Retired : €10
▪ Financial Sponsors (Employees): Free
SPE MEMBERS (comprehending Unemployed & Retired) must specify their Section of belonging & Member ID to be able to purchase a ticket for €25
GEOTHERMAL PROFESSIONALS must register using their Corporate email address to be able to purchase tickets for €25
SPE STUDENTS must specify their Student Chapter & Member ID, and register using their University email address to be able to purchase tickets for €10 - requests for registration sent not using Universities' email accounts will not be considered.
FINANCIAL SPONSORS' EMPLOYEES must send and email with object "SPONSOR EMPLOYEE REGISTRATION" using their Corporate email address to firstname.lastname@example.org - requests for registration sent not using Sponsors' email accounts will not be considered.
Hackathon (November 2023 - December 2023)
Please, click on the button below if your and your company want to collaborate with us on the delivery of SPE Europe Energy GeoHackathon. One of our team members will contact you as soon as possible to discuss together the best way to take part to the initiative.
All the employees working for a company supporting the event will have free access to both bootcamps and hackathon competition.
Seismic inversion and facies classification are two important techniques to understand the subsurface and reservoir characteristics for geothermal energy development.
The main challenges in seismic inversion are the non-uniqueness of the solution, the low-frequency component in the data and the prior information required. There are often multiple possible solutions that can fit the same data and the low-frequency content and prior information are often lacking. Facies classification in seismic data, on the other hand, involves grouping similar rock units based on their seismic reflection pattern and underlying physical properties. The challenge here is that rock properties can vary significantly within a single facies, often below seismic resolution and masked by noise, making it difficult to accurately define and differentiate between them. Both techniques require careful interpretation and validation, and a thorough understanding of the geological setting in order to make an accurate estimate of the formation properties.
Machine Learning (ML) has made significant steps in establishing the relation between seismic data and the causative rock parameters. ML can predict at great speed causative rock parameters from seismic data, but much ambiguity remains.
ML seismic inversion of acoustic impedance for identifying reservoir properties for geothermal deployment
Bonus Question 1: ML facies classification
Bonus Question 2: ML seismic interpretation of horizons or units
Data from the SCAN 2D seismic campaign will be used for this Hackathon.
A data-driven prediction and ML classification of reservoir properties from seismic data and well logs can enable solutions for:
Computationally efficient workflows to interpret large volume of dataset obtained from seismic campaigns
Identifying new features and facies using unbiassed AI workflows contributing to geothermal field developments
Speeding up the interpretation of the seismic data
Insights on the first two editions of the SPE Europe Energy GeoHackathon
40+ hrs of Certified Training