Join the 2021 GSH Geophysics in the cloud competition. Build a novel seismic inversion app and access all the data on demand with serverless cloud storage. Example notebooks show how to access this data and use AWS SageMaker to build your ML models. With prizes.
Key points are presented from the first of a series of LinkedIn articles where JSR Board Chairman Mitsunobu Koshiba provides thought provoking insights on business strategy in the context of trends in three time horizons. The short term is dominated by an increased acceptance of Modern Monetary Theory. The mid-term is a shift in the attitude to globalization from general cooperation to one of a battle for technological domination with accelerating advances. Long term holds a risk for geopolitical recession and China challenging the global economic hegemony of the dollar. Throughout all, technology is advancing at an accelerating pace.
To have a transformative impact, labs must reinvent workflows through digital technologies and skills, adopting a strong data culture. Innovation through digital-centric systems confidently produces new materials that meet customer specifications orders of magnitude faster than before, enabling broader business transformation.
The Digital Maturity Report uses a matrix to evaluate organizations digital maturity, determining whether they are lagging, competitive or leading based on the 5-core elements of Digital Maturity; Digital Strategy, Digital Skills, Digital Tools, Data & Data Flow, and Data Infrastructure.
Author: Ryan Swindeman, Scientific Software Developer
An effective, ‘at-home’ whiteboard solution needn’t be complex. A simple set-up is all, using a phone, held above a piece of paper (use books, boxes, or a stand to adjust the height of the phone). A lamp ensures the paper is lit sufficiently to be seen on a screen.
A key role of materials and chemistry R&D researchers is to invert the primary function of their labs – that of creating materials from chemical structures, formulations and processes – to one of determining the inputs that will produce materials with the desired properties with minimal iteration. This process can be significantly accelerated by ‘leveling up digitally’, ultimately transforming lab performance and its impact on the business.
Machine learning classification model learns complex printability window for inkjet printed polymer films using data from automated formulation and printing system.
In an example away from seismic, this shows a thin section, where machine learning techniques can be applied across multiple images, ones previously unused due to the significant demands of expert time, and difficulties in organizing and sharing data. See a demo at: https://www.enthought.com/industries/oil-and-gas/core-analysis/
The SubsurfaceAI custom deep learning application for seismic allows experts to annotate data, identify sequences and, in this example, define a fault complex. This forms the basis of a workflow that allows a seismic expert to apply deep learning to ‘interpret the way experts do,’ creating bespoke models for seismic interpretation.