5 Marzo 2024

Tackle large volumes of data with new solution from SLB for Azure Data Manager for Energy

As the energy industry continues to innovate, companies find themselves balancing the ever-growing demand for energy with the desire to work toward more efficient, sustainable operations. Decision makers spread across the globe rely on accurate data to improve confidence and minimize risk, so harnessing the power of data has become a central tenant of energy companies’ success as they push to evolve. However, different types of data and the variety of file types that energy companies manage daily make it difficult to access and analyze the data efficiently.

That is why energy companies around the world are using Microsoft technologies, including Azure Data Manager for Energy. This cloud-based OSDU® Data Platform maximizes customer performance by being truly interoperable across the exploration and production data landscape. It can integrate with industry datasets, applications, and other cloud services, which makes it easier for employees throughout an organization to access the data they need quickly and efficiently. These sources may include other data platforms for asset performance, the internet of things (IoT), or production, but also databases that may still be deployed on-premises before migration to the cloud can take place. Data siloes slow productivity and complicate workflows—optimizing access to high quality data is crucial for success.

Azure Data Manager for Energy

Accelerate your journey to energy data modernization and digital transformation

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The Microsoft partner ecosystem is a key component in how Microsoft delivers technology, services, and cloud-to-edge solutions for our customers. SLB—one of Microsoft’s strategic partners in the energy sector—designed the Enterprise Data Solution to work seamlessly with Azure Data Manager for Energy, easing data ingestion, management, and discoverability for domain applications.

Enterprise Data Solution from SLB facilitates day-to-day workflows

Designed to reduce the friction of dealing with large volumes of data traditionally stored in different silos, Enterprise Data Solution from SLB features a user-friendly, inclusive interface that facilitates the process of data ingestion, curation, and accessibility. Enterprise Data Solution from SLB allows customers to unlock data with a single click instead of running multiple steps to get the same results. This makes it easier for a variety of end users to ingest different data types and formats and access data faster. In addition, the curation of data along this pipeline is aided by several AI-enhanced tools, from more streamlined unstructured data ingestion, data quality control, contextualization, and data mastering, reducing the need for manual intervention.

A diagram showing data curation and enablement includes artificial intelligence and machine learning which includes deep learning, natural language processing and computer vision. That curation and enablement of data can then be ingested, curated, discovered, and consumed with Enterprise Data Solution from SLB from a solid data foundation.

Both traditional and new energy technical workflows are optimized when data and application interoperability are achieved. For example, handling large volumes of seismic data (access, ingestion, and streaming) can be dramatically improved with Enterprise Data Solution from SLB. The typical cost for handling these workloads is also reduced significantly, speeding up workflows and allowing users to incorporate as much diverse domain data as possible. Geoscientists and engineers can run more scenarios in different applications, compare results with their colleagues, and ultimately liberate the most accurate data quickly.

“Having the Enterprise Data Solution from SLB working with ADME is transformative. Workflow efficiency is vastly increased, and decision-making accelerated to levels that are impossible to achieve without it. Pairing the two technologies enables AI to work at full effect in the energy sector. AI plays a dual role, it enhances data quality, accessibility, and utilization, which in turn enables it to drive innovation across the entire planning to operations life cycle.”

Jamie Cruise, Product Leader, SLB

Key features of Enterprise Data Solution from SLB

The key features of Enterprise Data Solution from SLB include:

Ingest: Collect, ingest, and stage data easily from desktop or other file sources for document transcription and parsing. For example, you can use a cloud-style file drop for changes to files and get automated translation into the correct schema. This is increasingly aided by AI to reduce human workload requirements.

Curate: Data quality is at the heart of many of the challenges in the industry and causes a lot of wasted time. The Enterprise Data Solution from SLB accelerates curation and refining of datasets into trusted data products, liberating them with streamlined tools for data quality so they’re ready for consumption. These tools include AI for quality control and mastering.

Discover: Ready-to-use data products enable quick data-asset analysis and screening online for quick-to-create collections and consumption from domain workflows. Locating and accessing quality data is critical for decision-making. Enterprise Data Solution from SLB enables workflows to access the right data for stakeholders to easily discover, visualize, and use.

Consume: The Enterprise Data Solution from SLB makes it easy for analysts and others to access trusted data products from within their familiar applications and workflows, whether that is the Delfi™ digital platform, Petrel™ subsurface software, or Techlog™ wellbore software. With an intuitive user interface that’s accessible from a web browser, full data lineage, and project versioning are always available in an optimized format. Data can be shared and consumed in workflows such as seismic processing, machine learning seismic interpretation, and machine learning property modeling. In addition, this data is now easily consumable in machine learning workbenches such as Delfi Data Science or tooling available in Microsoft Azure. This cuts time to decision and action, critical components for a smooth production workflow.

Unlock downstream advantages within the Microsoft ecosystem

Once data is in Azure Data Manager for Energy, it conforms to the OSDU® Technical Standard and is a reliable platform for other applications to consume and re-ingest data iteratively. The interoperability of Azure Data Manager for Energy improves accessibility, traceability, and validity of data, allowing domain users and data scientists to deliver business outcomes faster.

Enterprise Data Solution from SLB helps customers take full advantage of Azure Data Manager for Energy by making it more efficient to ingest large amounts of quality, trusted, and traceable data into the platform. Ultimately, Azure Data Manager for Energy’s interoperability empowers customers by harmonizing data that can be leveraged across the Microsoft ecosystem.

Once this data is in the platform, there are many opportunities to take advantage of Microsoft Azure OpenAI Service to drive additional insights and efficiencies further downstream in Microsoft 365 applications. For example, end users can extract tables directly from ingested documents and generate Open XML documents that are ready to use in Microsoft Excel, where they can be more easily visualized.

Next steps

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Source: Microsoft Industry Blog