Database, Cloud, & IT / Transfer

Death by apps, first on your phone and now in O&G

How many apps do you use regularly on your phone? How many of them actually improve your day? What at first seemed like a blessing has turned into a curse as we flip through pages of apps searching for what we need. Most of these apps are standalone, made by different developers that don’t communicate with each other. We’re now seeing a similar trend in O&G with a proliferation in software, especially around analytics.

O&G has always been a data-heavy industry. It’s well documented that data is one of the greatest assets these companies possess. With the onset of unconventionals, both the types of data and the amount of data has exploded. Companies that best manage and leverage data will be the high performers. However, this can be a challenge for even the most sophisticated operators.

Data is collected throughout the well lifecycle from multiple vendors in a wide range of formats. These data types have historically been ‘owned’ by different technical domains as well. For instance, drillers owned the WITSML data, geo’s the well logs, completions engineers the frac van data, production engineers the daily rates and pressures. These different data types are delivered to the operator through various formats and mechanisms, like csv files, via FTP site or client portals, in proprietary software, and even as ppt or pdf files.

Each domain has worked hard to optimize their processes to drive down costs and increase performance. Part of the gains are due to analytics applications – either built in house or delivered as an SaaS offering from vendors – providing tailored solutions aimed at addressing specific use cases. Many such vendors have recently entered the space to help drillers analyze drilling data to increase ROP or to help reservoir engineers auto-forecast production. However, the O&G landscape is starting to look like all those apps cluttering your phone and not communicating with each other. This usually translates into asset teams becoming disjointed, as each technical disciple uses different tools and has visibility only on their own data. Not only is this not ideal, but operators are forced to procure and support dozens of disconnected applications.

Despite the gains achieved in recent years, certainly due in part to analytics, most shale operators are still cash flow negative. Where will we find the additional performance improvements required to move these companies into the black?

The next step in gains will be found in integrating data from across domains to apply analytics to the overall asset development plan. A cross-disciplinary, integrated approach is needed to really understand the reservoir and best extract the resources. Some asset teams have started down this path but are forced to cobble together solutions, leaving operators with unsupported code that spans Excel, Spotfire, Python, Matlab, and other siloed vendor data sources.

Large, big-name service providers are trying to build out their platforms, enticing operators to go all-in with their software just to more easily integrate their data. Not surprisingly, many operators are reluctant to go down this path and become too heavily dependent on a company that provides both their software and a large chunk of their oilfield services. Is it inevitable that operators will have to go with a single provider for all their analytics needs just to look for insights across the well lifecycle?

An alternative and perhaps more attractive option for operators is to form their own data strategy and leverage an analytics layer where critical data types can be merged and readily accessed through an open API. This doesn’t mean another data lake or big data buzz words, but a purpose-built analytics staging area to clean, process, blend, and store both real time and historical data. This layer would fill the gap currently experienced by asset teams when trying to piece their data together. Petro.ai provides this analytics layer but comes with pre-built capabilities so that operators do not need a team of developers working for 12 months to start getting value. Rather than an SaaS solution to one use case, Petro.ai is a platform as a service (PaaS) that can be easily extended across many use cases. This approach removes the burden of building a back end for every use case and then supporting a range of standalone applications. In addition, since all the technical disciplines leverage the same back end, there is one true source for data which can be easily shared across teams.

Imagine a phone with a “Life” app rather than music, calendar, weather, chat, phone, social, etc. A single location with a defined data model and open access can empower teams to perform analytics, machine learning, engineering workflows, and ad hoc analysis. This is the direction leading O&G companies are moving to enable the integrated approach to developing unconventionals profitably. It will be exciting to see where we land.

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