This blog post was co-authored by Kapil Raval, Principal Program Manager at Microsoft.
Bluware develops cloud-native solutions to help oil and gas operators improve exploration and production workflow productivity through deep learning by empowering geoscientists to make faster and smarter decisions about their subsurface and today announced a collaboration with Microsoft for the next generation of automatic interpretation. InteractivAI™, a solution built on the Azure implementation of the OSDU™ Data Platform.
Together, the two companies offer a comprehensive solution that combines the Microsoft Cloud implementation of the OSDU™ Data Platform with Bluware’s underground knowledge. Global energy companies are reinventing themselves for the future, balancing priorities between sustaining the growing demand for new forms of energy, carbon emissions and fossil fuels. Innovative solutions such as cloud computing and machine learning are playing a key role in this transition.
Bluware offers interactive deep learning to meet the energy giant’s seismic interpretation challenges. Solutions that run natively on Azurecalled Interactive AI™.
InteractivAI™ is utilized by the organization’s exploration and reservoir development teams to accelerate the interpretation of seismic events and geological data that may have previously been missed, misinterpreted, or taken too long to interpret. and improve results by helping geoscientists identify geophysical features.
By using a data-centric approach, applications are uniquely capable and allow users to: Train and infer at the same timeImagine running deep learning in real-time where the interpreter is providing feedback that the operator can actually see as the network suggests interpretations on the fly. This includes data results that are not easily visible or very difficult for the human eye to see. This interactive workflow delivers more accurate and comprehensive results in hours rather than months, resulting in higher quality exploration and reservoir development.
Interactive deep learning approach
Blueware is pioneering the concept of “interactive deep learning,” where scientists stay in the metaphorical “driver’s seat” and steer networks as they learn and adapt based on the teachings of their interpreters. Tuning and optimizing the training of the dataset provides immediate feedback to the network, adjusting weights and biases accordingly in real time.
Bluware differs from other deep learning approaches that use neural networks pre-trained on multiple data sets. It’s something the user has no control over, as they have to rely on networks trained on unseen data, created with an unknown set of biases.
The basic parameterizations exposed to scientists in these traditional approaches give the illusion of network control without actually transferring significant control to the user. Processing times can take days or weeks. possible, and scientists can provide feedback to the network only after training is complete. At that point, you have to start the training all over again.
of Interactive deep learning approach is a data-specific approach focused on creating learning and training models that best suit the geology you work with. Unlike traditional deep learning approaches, the idea is to start with an empty, untrained network and train it while labeling it to identify features of interest. This approach is not limited to salinity or faults, but can also be used to capture shallow hazards, injections, channels, bright spots, etc. This flexibility allows professionals to explore a myriad of possibilities and alternative interpretations within their area of interest.
The energy company initially conducted a two-month assessment of multiple experts across its global asset team. The results have been remarkable, and organizations continue to add users. In addition, Bluware provided the company’s IT team with the blueprint for the Azure Kubernetes Service (AKS) implementation that accelerated and scaled this Azure-based solution.
A seismic data format designed for the cloud
As companies continue to wrestle with massive and complex data streams, such as petabytes of seismic data, the pressure to invest in digital technology increases. Bluware has adapted to this emergency and offers a cloud-based format for storing seismic data. Volume Data Store™ (VDS). Microsoft and Bluware have worked together to natively enable his VDS as part of the Microsoft Cloud implementation of the OSDU™ Data Platform. It allows developers and customers to connect to stored seismic data and deliver interactive AI-driven seismic interpretation workflows using InteractivAI™ SaaS.of Azure app source.
Bluware and Microsoft are collaborating in parallel to support key customers in the energy industry, including moving petabytes of data to Azure Blob Storage in cloud-native VDS environments.
Revolutionizing how energy companies store and use seismic data
Bluware designed InteractivAI™ not only for seismic workflows, but also for the trends shaping the future of the energy sector. By creating a cloud-native data format, energy companies can scale and get more out of their data while reducing costs and speeding workflows, leveraging the power of Azure to make more accurate decisions. You will be able to put it down quickly.
About Blueware
In 2018, a group of energy-focused software companies namely Bluware, Headwave, Hue, and Kalkulo AS merged to form Bluware Corp., empowering change, growth and a sustainable future in the energy sector. I was.
As businesses move away from fossil fuels and toward cleaner energy sources, the combination of new industry standards, cloud computing, and AI is essential for businesses to adapt quickly, work smarter, and stay profitable. Companies that adapt more quickly gain a significant advantage over their competitors. For more information, see: blueware website.
