Using application microprocessors for seismic

First practical application that I know of using the next thing after TPUs (Tensor Processing Units): ASICs or Application Specific Integrated Circuit. Ideal dedicated hardware for the massive seismic data and processing. Machine Learning (ML) algorithms build a mathematical model based upon representative sample data, known as ‘training data’, in order to make predictions or decisions without being explicitly programmed to perform the task. I limit my discussion here to supervised learning in the context of a potential application to seismic data image processing of a real marine seismic dataset, and then discuss how the computational scale of such exercises reinforce the need to develop computing technology that is customized for large ML problems.

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Well Failure Analysis by Kevin Ward

Article in LinkedIn.

How do you analyse well failure? Just to be clear upfront, I’m referring to geological failure, as opposed to engineering failure – I’ll leave that one for the engineers!

Well Failure Analysis by Kevin Ward.

Keywords: geology, well, Petrosys, dbMap

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