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  • Spotfire® Energy Solutions

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    Energy is a digital business. Use Spotfire® analytics with applied data science to solve the most complex industry problems.

    September 2024 update: note that this article is currently being edited.

    Introduction

    Today’s energy companies simply cannot improve their margins, grow their profits, or outperform their industry peers without leveraging data. The oil and gas industry is changing rapidly. Regulatory pressure, changing customer expectations, and an intensive focus on efficiency compel energy companies to change the way they do business. Whether the focus is exploration and extraction, transportation and storage, or refining and delivery, Spotfire analytics can help organizations work smarter in all that they do.

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    Recent Engagements

    SPE ATCE (New Orleans, LA, 23–25 September 2024)

    SPE Annual Technical Conference and Exhibition (ATCE) is the leading technical energy conference and exhibition for global E&P professionals. Michael O'Connell talked about Visual Data Science & AI Tools for Subsurface Data.

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    Digitalization in Oil and Gas (Houston TX, September 4-5, 2024)

    This year, the focus is on leveraging AI and generative AI, driving sustainability and workforce development, and achieving operational excellence through digitalization.

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    IMAGE24 (Houston TX, August 26-29, 2024)

    IMAGE '24 highlights traditional petroleum geoscience topics while uncovering the latest energy market trends, science, and opportunities.

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    Reuters, Data Driven Oil and Gas (Houston TX, June 11-12 2024)

    Data Driven Oil & Gas USA 2024 is the go-to global meeting point for upstream’s digital visionaries, where 400+ major and independent operators, service companies, global tech giants, and innovative startups will foster solutions-oriented dialogue, form commercial relationships, and share business-critical strategies to overcome progress blockers and propel the upstream digital transformation. @Michael OConnell Talked about Leveraging AI for Upstream Success. 

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    Spotfire Solutions by Use Case Domain

    Spotfire Copilot in Energy

    Spotfire Copilot™ is a free, natural language extension to the Spotfire® platform. It leverages large language models (LLMs) to augment business intelligence and artificial intelligence, all in Spotfire. Copilot applications in energy has many use cases. In our example we used the Spotfire Copilot to help with transforming Oil and Gas specific data (LAS and DLIS) files into a format that can be understood by Spotfire. Copilot was also used to provide quick data insights and some domain related questions.

    For More Information:

    Realtime Well Completion Survey

    Using Spotfire to monitor and analyze real-time data coming from Oil Field during completion process, we also used data functions to further analyze and estimate the ISIP (Instantaneous Shut-In Pressure). 

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    For more information: 

    Realtime Intelligent Equipment Surveillance 

    The Intelligent Equipment Accelerator provides a reference architecture and code assets for building telemetry monitoring solutions inside of equipment hierarchies. It is primarily configuration-driven which allows a flexible object hierarchy based on the generic concept of Entities. Attached to these Entities are Devices which represent data producing sensors. The platform illustrates how capturing sensor telemetry can be used to gain business insights.

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    For more information:

    Historian Data Replay and Analysis

    The Data Replay Accelerator for Spotfire® is used to capture and replay in real-time data from historian systems like OSI PI, OPC UA, or a other repository. When an anomaly or trigger condition is detected, it retrieves a configurable amount of data before and after the anomaly, and gives operators the capability to replay this data for observation in a Spotfire® dashboard.

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    For more information:

    Drilling and Completion Accelerator

    The IoT Drilling Accelerator is a platform to consume drill head data from Oil Rigs, perform Analytics on the data and present to Drilling Engineers. The Analytics are performed in Real Time and the results sent to Spotfire® and Live Datamart dashboards. This gives an up to date view of Rig state and the ability to detect anomalies as they occur.

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    For more information:

     

    Optimum Well Placement Analysis

     

     

     

     

     

     

    Benefits of Digital Transformation and Applied Data Science for the Energy Sector

     

    Why are so many energy companies determined to digitally transform? Modern companies cannot improve margins, grow profits, or beat their peers without gaining insights from their data. To get the full benefits from data, they must transform every business function?from analytics to operations to marketing.

    Spotfire® Analytics: Analytics Capabilities for Energy

    Energy is a digital business. Top to bottom, Spotfire® analytics with applied data science and TIBCO® integration software play across the spectrum, solving the most complex industry problems.

    Data science is a team sport. Data scientists, citizen data scientists, data engineers, business users, and developers need flexible and extensible tools that promote collaboration, automation, and reuse of analytic workflows. But algorithms are only one piece of the advanced analytic puzzle. To deliver predictive insights, companies need to increase focus on the deployment, management, and monitoring of analytic models. Smart businesses rely on platforms that support end-to-end analytics lifecycle while providing enterprise security and governance. Spotfire® Data Science software helps organizations innovate and solve complex problems faster to ensure predictive findings quickly turn into optimal outcomes.

    Upstream

    In terms of generating value at the Reservoir, Spotfire analytics is across the spectrum from where to drill, how to optimally complete, and how to operate.

    Examples of applied Data Science using Spotfire:

    Spotfire Real-Time AI Completions Solution - Sharp insights into completion tasks

     

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    Completion Demo Main Page.

    • Summary and Objective: We worked on this solution along with TIBCO and Spotfire partner Rivitt. The main goal of the solution is to provide an end-to-end solution for well crews and engineers to examine and monitor the real-time completion data (streamed live from the wellpad) and also to perform some data analysis tasks. In this solution, Rivitt will perform the data collection from the wellpad sensors, aggregating it and connecting it to TIBCO data streams, where we connect to that resource from Spotfire. We also have a TDV data source in order to write data back from the Spotfire dashboard.
    • Application landing page sections:
      • Overview: An overall glance at all the operations, quick KPIs, and locations of the currently active operation. This page also serves as a daily automated report to the management.
      • Treatment Plots (LIVE): Shows a live view of the treatment plot in addition to the current operation important parameters and activity
      • Wireline and Coiled Tubing: Shows the Wireline jobs history on the wellpad in addition to the Coiled tubing jobs.
      • Pad Metrics: A cost and time analysis per well and per stage over time. This section provides a clear comparison across the wells and within one well. It also gives a summary of the resource utilization
      • Stimulation Response: We used some unsupervised learning here performed using Spotfire Data Science to provide an estimate for the formation breakdown pressure and shut-in pressure.
    • Click here to visit the demo dedicated page.

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    Team Presentation to Completion Demo in Energy TechNight, Houston TX (Feb, 2022)

     

    Completion Process as an Example of Process Digital Twin.

     

    Value at the Reservoir

    The number of data scientists in reservoir characterization teams continues to increase, but most of their work is oriented toward predicting rock properties, fluid patterns, reservoir quality, production, and well performance. However, to analyze the data and accomplish their goals, they must spend a lot of time conditioning the data, interpreting logs, correlating wells, mapping structures, and generating seismic properties to get the attributes that will then be used to train predictive models, run classifications, and uncover hidden patterns.

     

     (3:32) you will see Spotfire examples for:

    • Deep Learning when analyzing Seismic data for reservoir characterization
    • Example of Drilling and Completions
    • Example of Halo Analysis
    • Example of Petrophysical Analysis

     

    Value at the Drill

    Get analytics right at the point of the drill bit and understand how to monitor the actual well path.

    Real-time determination of the best yet-to-drill path.

    Understand the state of your bit and bit wear.

     (1:45) you will see Spotfire examples for:

     

     

    Value at the Well

    Get the most out of assets!

    Production Surveillance, Data Operations, Model Inference, Asset Management.

     (1:46) you will see Spotfire examples for:

     

     

    Downstream

    Examples of applied analytics using Spotfire:

    Value at the Grid

    Operations Analytics in the Cloud

     

     (0:49) you will see Spotfire examples for value at the grid:

     

    Couple your insights with actions!

    Your data insight journey doesn't stop with exploration, and it's actually not complete without taking actions that are coupled with what you learned. Using the new Cloud Actions feature in Spotfire you can trigger an action based on what you see in your data. The demo below shows an example of using and executing specific cloud action in an energy trading demo:

     

    Peek into your historian data in seconds

    Accessing your OSIPI Data is pretty straightforward in Spotfire utilizing the power of OSIPI Connector in Spotfire. Using Asset Framework (AF) users can quickly build custom and complex queries without leaving the application. These connectors promote Spotfire custom expressions to produce highly customized and condition-based queries as shown in this Dr. Spotfire episode:

     

    Resources

    Read this community page that walks you through the OSIPI connection in Spotfire

    Renewable Energy

    Resources for the Energy Community

    Download pre-configured ML modules (R/python scrips ready to go)

    Webinars/Conferences

    DataSheets

    Other resources

     

     

     

     

     

     

     

     

     

     

     

     

     

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