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Data analytics. Process optimization. Machine learning. AI. IoT.  Words and phrases that increasingly appear in conversations around the oilpatch these days.

The reality for the oil and gas industry is that the sector has always been as much or more about data as it is hydrocarbons. Conversely, it sometimes seems that the petroleum industry has plenty of data, but not necessarily information and knowledge.

Clearly, enhanced data analytics could have a significant impact on the drilling and completion cost curve over time. Some of the data-driven technological advances in the E&P sector include the usage of machine learning and data analytics to define landing zones and optimize completions in real-time, predictive analytics to avoid drilling issues in advance, and downhole optics to identify where the rock may be inhospitable for fracking, potentially resulting in fewer stages.

Beyond well construction applications, data analytics could lead to cost-effective improvements in production operations, as well as optimizing more mundane areas such as inventory management.

With data becoming a key input for driving growth for both operators and service companies -- enabling businesses to differentiate themselves and maintain a competitive edge -- this raises an important question: Is it possible for a company to measure the value of its data? 

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There are three reasons organizations might want to understand the value of their data: monetization, internal investments, and mergers and acquisitions.
Organizations may want to monetize data by selling it or marketing data products. First, an inability to understand data’s value can result in mispriced products. Secondly, most organizations are very reluctant about what data they expose to outsiders. Good valuation approaches might help understand if selling their data would really affect their competitive position or the ability to realize their own benefit from it.

Understanding the value of data can help prioritize and direct investments in data and systems, while inaccurate valuing of data assets can be costly to shareholders during mergers and acquisitions.

Current accounting practices do not permit data to be capitalized on the balance sheet. However, accounting companies are coming forward with approaches to value intangible assets in general and information assets in particular. Most of these data valuation methods descend from existing asset valuation or information theory. 

Another method, the “prudent value” approach, values data sets based on the extent to which they could be used to advance key business initiatives. Mapping data to valuable outcomes can support ROI arguments based on expected outcomes for IT investment. It can also guide monetization efforts by relating the value of the decisions of third parties with respect to the data they use to guide the price they might pay for access.

In order to realize full value from these data analytics/process optimization efforts, oil and gas companies will have to take stock of their data, how they are leveraging it, and ultimately evaluate what is and isn’t useful.