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10 December 2020

The 2020 EAGE Norman Falcon Award

The 2020 EAGE Norman Falcon Award

During the Award Ceremony of the 82nd EAGE Conference & Exhibition, Dr Quinten Boersma received the 2020 EAGE Norman Falcon Award. His paper ‘Linking natural fractures to karst cave development: a case study combining drone imagery, a natural cave network and numerical modelling’, was chosen as the best paper published in Petroleum Geoscience in 2019.

25 November 2020

Looking for possible tombstone by using GPR

In March 2020, Dominique Ngan-Tillard and Deyan Draganov were approached by the foundation Jewish Westland, who manages the cemetery in Naaldwijk, and asked whether it would be possible to use non-invasive geophysical methods to look for possible tombstones lying under the ground surface of the cemetery.

25 November 2020

NENnovation award for the Energy Quay Wall

NENnovation award for the Energy Quay Wall

A consortium led by CRUX Engineering, including TU Delft, TU Eindhoven, Gooimeer and Duurzaam Opgewekt Energiesystemen, have won the NENnovation award for the Energy Quay Wall. Phil Vardon, Ivaylo Pantev and Jorrit de Vries are involved from TU Delft.

09 November 2020

Hydrogen Underground Storage

Hydrogen Underground Storage

Hydrogen underground storage is a key element of the Delft Subsurface Storage Theme. Hydrogen production at North Sea, alone, is aimed to target 3-4GW power by 2030 and 10 GW by 2040. Hadi Hajibeygi has been interviewed recently about the role of geoscience in hydrogen energy sector, which was arranged by Delft Energy Institute. In this interview he addresses subsurface storage of hydrogen in salt caverns.

09 November 2020

Femke Vossepoel in Women in Data Science (WiDS)

Femke Vossepoel in Women in Data Science (WiDS)

Margot Gerritsen of Stanford University hosts the Women in Data Science (WiDS) specifically for the younger generation (high school students, BSc students). The most recent episode features Femke Vossepoel. In this podcast, she talks about her life as a data scientist and explains how data-assimilation tools can be used to improve COVID-19 forecasting models.