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Cloud Computing in Geoscience

Commentary by Eirik Larsen. Chief Solutions Officer, Earther Science Analytics
17 January 2022

Eirik Larsen, our co-founder and Chief Solutions Office,  shares some information on cloud technologies and the associated benefits that arise from the use of cloud.


What is cloud computing technology?


So, what exactly is cloud computing technology? It’s perhaps best viewed as the delivery of on-demand applications, using computer resources to access data. Most of us will have used the technology from our own private use of streaming services like Netflix and Amazon Prime. 

 

One example of cloud application is centred on remote desktop services. When used in this context, an individual can deploy software, originally developed to run on a desktop, within the cloud, or other remote machines. However, this solution comes with high rental costs and with multiple applications being used, there’s no system in place for interaction. This means the data silo problem remains unsolved as data remains locked in the legacy platform.


Alternatively, cloud-native software is built specifically to work within cloud environments before being deployed on cloud infrastructure. Storage and compute power are available on-demand, which means data can be liberated,  contextualised, and shared easily.  Its usage allows scaling of computing resources, which in turn provides a real cost saver as individuals only pay when they use the resources. 


Eirik also highlighted that there’s a lot of flexibility in terms of how cloud systems can be deployed, each bringing a  range of benefits once adopted.  He also explained why the cloud is being used. “The main driver for its use will be to support AI and machine learning,” said Eirik. “One of the pillars of machine learning, and the driver behind its growth outside oil and gas, is the availability of computing resources and high-performance computing services. Cloud technology also supports the use of Big Data to train robust generalising models, and even the machine learning algorithms themselves,” he added. In the geosciences space, at Earth Science Analytics, we have adopted these principles to access computing from multiple vendors, on-demand, when and where it’s required.



Unlock the value of your data with EarthNET


Our EarthNET solution connects energy company users with their internal and external data assets, with high-performance computing resources and  AI-powered geoscience software applications. This connectivity and the integrated applications allow EarthNET users to break out of the data and discipline silos and embrace truly integrated and cross-disciplinary data analytics workflows.


We are also building custom layers on top of this to position the data at the fingertips of those who need it in the form of our EarthBANK data platform. Integration with EarthNET enables users to access structured data such as wireline logs, core data, and seismic data. This can then be used to build models to infer properties of interest such as lithology, porosity, and permeability. When these properties have been inferred, the data is written back to EarthBANK, providing a rich repository of rock and fluid property data. 


If you would like to find out more about our EarthBANK data platform and how it connects cloud infrastructure with on-premise solutions, please get in touch.