Published: January 14th, 2016
Visual analytics is an under-utilized information analysis technology that can be the savior of the oil and gas industry. The oil and gas industry is suffering through the effects of a severe and protracted price collapse. Every producer has stopped production at suddenly unprofitable wells and is examining every conceivable way to improve profitability of the remaining wells.
Here are the main impediments that oil and gas engineers face on the path to returning the oil and gas industry to profitability and how a visual analytics application overcomes these impediments.
Poor data access
Engineers face poor data access to the production performance, financial, asset characteristic and public well information they need to perform their production optimization work. Every application associated with a data source comes with a unique user interface, distinctive data definitions and a proprietary database schema in which the data is housed.
Visual analytics software offers engineers a single user interface that can query, report, graph and export data from multiple data sources. After the database access has been built once, the engineers can focus on production analysis rather than on learning the nuances of many applications and associated databases.
Hand-crafted data integration
Engineers are forced to rely on time-consuming, hand-crafted, complex Microsoft Excel routines for data integration. The Excel routines are very susceptible to data problems and subtle bugs that demand a lot of an engineer’s time to address.
Visual analytics software comes with the integration tools to make disparate database schemas appear uniform and integrated to the engineers. After the data integration has been built once, rather than tweaked daily, the engineers can focus on production improvement with confidence that the data is not misleading because of data integration bugs.
Poor data presentation
Engineers contend with the reporting and graphing tools limitations of Microsoft Excel or individual applications. No one can see interesting opportunities in endless rows and columns of data or in simple graphs. Production optimization requires the simultaneous display of multiple time series and the ability to click on any data point to drill into the data.
Visual analytics software offers the ability to turn these useless rows and columns into colour-coded time series of data where problems and possible solutions are immediately visible. Visual analytics software includes robust drill-down capability that takes engineers from the summary into the detail with very few mouse clicks and no new coding.
No data query flexibility
Engineers typically have access to functionality that produces excellent results for predefined queries and reports. However, all requests for revised queries or enhanced reports are addressed through a service request to the software development group that can take days, weeks or months to complete. Engineers need answers to more targeted queries in seconds or minutes and shouldn’t have to wait longer.
Self-serve visual analytics software offers a rich user interface to construct free-form queries and reports in real time with a few mouse clicks, no waiting and no arcane command language. With this capability engineers can focus on production optimization rather than on software development.
Poor visual analytics implementation
Engineers suffer through a frustrating inability to achieve business value from the mountains of data being collected daily by operations, peers and regulators. Often this problem is caused by poor execution of visual analytics projects.
Visual analytics implementation projects need to be competently planned and executed just like all IT projects. Success can be achieved by addressing the usual risks caused by people, technology and data.
Want to know more?
Annually, Gartner publishes its Magic Quadrant for Business Intelligence and Analytics Platforms report. The report contains an excellent summary of analytics concepts plus summary assessments of the many software vendors that are active in this space.
The monograph “How to use Analytics to improve Production” published by the Digital Energy Journal is worth scanning.
Can you share more ideas for how visual analytics applications have delivered benefits to your organization?
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