In the most recent oil and gas digital trends survey from Accenture and Microsoft[1], two-thirds of upstream oil and gas professionals said analytics is one of the most important capabilities for transforming their company. The oil and gas industry is sitting on a wealth of data: from new geophones and logging tools to sensors, companies have access to massive and diverse data sets. The transformational impact of analytics provides a layer of insight on top of this data, helping to answer questions about what has happened, what could happen in the future and what steps should be taken next. As the industry moves towards an analytics-driven future, it should however heed the adage of ‘Garbage in, garbage out’. Analytics are only as good as the data that feeds them.

Good data management is a significant challenge for upstream oil and gas companies. Data volumes are now exceeding 10TB of data per day for a single well, for example. As this data pours in, it needs to be consumed by the business more quickly than ever before in order to make key decisions. In this drive for quicker access, quality is often sacrificed.

The typical technology architecture at oil and gas firms consists of four separate systems: ETL (extract, translate and load), MDM (Master Data Management), a data warehouse (or store) and some kind of analytics tool. As a result, there are multiple handoffs between disparate databases and systems with data often being manually moved between applications, and, in many cases, through an intermediate step, such as Excel.

Not only is this multi-application environment costly and cumbersome to maintain, but it also increases the potential for error in the data and introduces complexity in identifying, tracking and fixing data. Business users may be able to generate visually appealing reports in their business intelligence tools, but how accurate are they? Can users trace the source of data, the changes made to that data, by whom and when?

A more closely integrated architecture defined by workflows can help reduce the points of failure, enhance data quality and improve the data management process in general. With a solid data management foundation, combined with data collection and analysis more closely knitted together, oil and gas companies will be able to fully realize the potential of data, deliver accurate analytics and enable decisions to be made more quickly with the confidence that they are being made on good data.

Enterprise Data Management (EDM) from IHS Markit combines ETL, MDM and data warehousing into a single application, reducing support overhead, streamlining integrations and, importantly, empowering the user with full access to the data either within EDM or in any downstream analytics or BI tool. Data is validated, enriched and reconciled across multiple sources enabling full data lineage and a transparent audit trail.

By applying true data quality control measures, EDM eliminates the uncertainty and provides trusted data for analysis. Automating quality control also enables data managers to focus on the areas that need it most – the exceptions – and allows issues to be resolved before distribution downstream.

Removing the restrictions imposed by fixed data models, EDM leverages the models used by each company, eradicates the need for separate siloed data tools and enables all energy data, be it sub-surface, operations, midstream, economics or financial to be managed in a single environment.

To quote The Economist, “The world’s most valuable resource is no longer oil, but data”. If data trumps oil in terms of value, then surely this raw resource deserves some more attention.

[1] 2016 Upstream Oil and Gas Digital and Technology Trends Survey, sponsored by Accenture and Microsoft and conducted by PennEnergy Research<span/>

Nathan Amery, Director and Head of Strategy, EDM for Energy at IHS Markit
nathan.amery@ihsmarkit.com

Interested in learning more? Please visit EDM for Energy.

This article was published by S&P Global Commodity Insights and not by S&P Global Ratings, which is a separately managed division of S&P Global.