Here, we investigate the relationship between radiative forcing (heat warming) of carbon dioxide and its concentration in the atmosphere to better understand climate feedback and sensitivity.

We continue the discussion of the simple greenhouse model introduced in Part III.

By building on knowledge from the petroleum industry and experience of over 23 years of storing CO₂ in deep geological formations, we can make a new value chain and a business model for carbon capture and storage (CCS) in the North Sea Basin.

The basic idea behind CCS (Carbon Capture and Storage) is simple, but what are the main challenges and practical issues preventing a more global adoption of this method?

What would the temperature of Earth be without the atmosphere? By using simple physical models for solar irradiation and the Stefan-Boltzmans law for blackbody radiation, we can estimate average temperatures with and without atmosphere.

In Part II we look at Arrhenius’ seminal 1896 paper and see how it relates to blackbody radiation and absorption of infrared radiation by the atmosphere, taking a closer look at his model of the greenhouse effect.

Geoscience will probably play an important role in mitigating carbon dioxide emissions. In part one of this series, we discuss some history and physics behind the topic of climate change including the concepts behind blackbody radiation and Millankovic Cycles.

Part 2: Early developments of marine vibrators for geophysical acquisition techniques made by PGS.

Part 1: History & early developments of marine vibrators for geophysical acquisition techniques.

Part I: how to become an expert at solving differential equations in five minutes...

Brand new book from GEO ExPro & Bivrost Geo. All you ever wanted to know in an introduction to exploration geophysics – clearly explained and beautifully illustrated.

Most successes so far in deep learning have been based on supervised learning. The holy grail, however, is unsupervised learning.

“We need to go deeper.” Leonardo DiCaprio, in the film Inception (2010).

Once, artificial intelligence (AI) was science fiction. Today, it is part of our everyday lives. In the future, will computers begin to think for themselves?

Field Examples