Data Analytics
Our clients have billions of dollars invested in subsurface data. Our Data Scientists can help to integrate data from multiple
sources to unleash the power of analytics.
- Dynamic & real time analytics
- Performance and Predictive Analytics
- Data quality analysis
- Strategic insights
- Analytics workshops
- Custom Analytics Data Modeling
Subsurface Data Analytics Insights and Opportunities:
Data analytics provide reports and dashboards that are synchronized to an oil and gas company’s subsurface data. Our consultants have the
ability to extract insights from subsurface data through our powerful analytics tool, Katalyst 360.
Katalyst 360, a self-service data analytics environment that gives you the ability to gain insight into the subsurface data within your
organization and extract the most value from those data assets.
The Katalyst 360 analytics platform gives oil and gas companies a 360 degree view of their subsurface data. Users can utilize provided analytics dashboards that measure project status, data completeness and process efficiency. Users can also customize their subsurface data analytics reports to truly unleash their data’s potential.
The subsurface metadata within iGlass is the starting point, and plans are to further enrich the environment with additional data, including oil and gas operational data and public data, enabling predictive and prescriptive analytics. Hands-on workshops and consulting services (link to consultants page) will be available to help clients use the analytics to better understand and gain insight from their data. Finally, Katalyst’s subsurface consultants can create custom solutions to achieve your specific objectives.
Exploratory Data Analysis:
Obtain a quick understanding of your subsurface data assets to understand what data has been loaded to date. Uncover insights and opportunities that lead to prescriptive actions to improve the value and quality of subsurface data assets.
Data Completeness :
Analyzing data completeness allows you to locate and identify gaps in a dataset, and also map out actions to correct the situation. When dealing with seismic data for example, field, navigation and supporting documentation such as observer’s reports are needed in order to reprocess the data. When you have a complete dataset, the value of that data is much higher.
Data Quality:
Find metadata gaps and inconsistencies within specific database fields and resolve to improve database organization, searchability and usability. Most searches and orders start from a map, so data that is not visible is much harder to find. The ability to check map visibility enables users to rectify issues and make data easier to find and utilize.
Entitlements and Ownership :
Get entitlements and ownership under control. Proprietary data can be marketed for license or sale, earning revenue rather than simply sitting on the shelf. On the flip side, exposing data for sale that has indeterminate ownership could lead to messy issues, so proving entitlement to data is critical.