Working together with strategic partners, TIBCO® and The University of Texas, our internal Upstream Energy Data Science team has tested and validated existing machine learning algorithms using the vast S&P Global data to solve common E&P challenges, the team has also created proprietary algorithms, workflows and data models to ensure your asset team spends more time understanding the outcomes of machine learning rather than implementing, building, and training AI technology. With thousands of manhours invested in pairing domain experts with data scientists, Analytics Explorer was purpose-built to fast track big data analysis while incorporating robust visualization tools so your teams can see the data in the way that resonates most with their investigation.
Benefits include:
- Next-level collaboration with a cross-disciplinary dataset allowing for reduced uncertainty and risk
- Improved productivity with dynamic data connections and automated workflows
- Optimized analysis by applying algorithms from leading-edge data science research
- Enhanced value of data by combining S&P Global data solutions and insights with your proprietary data
Figure 1. Analytics Explorer dashboard, powered by TIBCO Spotfire®, visualization results from Principal Component Analysis and Self-Organizing Map techniques applied to seismic attributes workflows for facies delineation, resulting in more accurate interpretations.
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Figure 2. 3D view of wellbores colored by formation zone penetrated by horizontal wells. This visualization is made possible through the integration between KingdomTM Geoscience and Analytics Explorer percentage in zone computes through proprietary algorithms.
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Figure 3. KingdomTM Geoscience map view of enhanced geological features in the North Sea basin, resulting from Analytics Explorer machine learning techniques applied to seismic data.
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Figure 4. Analytics Explorer dashboard, powered by TIBCO Spotfire®, visualization results using multi-variate techniques for identification of multiple lithology types and fluid variations across a reservoir.
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Analytics Explorer has built-in connections with the following S&P Global Commodity Insights solutions and services:
Users of Analytics Explorer can also ingest their proprietary or third-party data stored in a SQL/PostgreSQL database to create new insights and understanding.