Digital Forms, Mobile Apps, IoT, Data Analytics, and Machine Learning in the Oil and Gas Industry

Recently, I had the pleasure of interviewing Cody Cupp, CEO of the UNEE Group based in Houston, Texas. UNEE focuses on Digital Transformation. We discussed how Petrochemical, O&G, and Energy customers are undertaking Digital Transformation, and this blog shares with all of you Cody’s insights that he has gleaned from actual customer implementations.

These industries focus on Minimizing Risk, Increasing Safety for Resources, Optimizing the Workforce, and Operational Excellence. In order to achieve these objectives here is what O&G companies are deploying:

Digital Forms: O&G firms have a great number of paper-based forms they have to fill. These are related to Environmental, Health, and Safety (ESH). They are now converting these forms to Digital, collecting data on mobile devices, and integrating that data with back end systems directly. These forms work offline and are dynamic. From a User perspective, filling a complex multi-page form is far easier on a tablet than on paper. It leads to better data quality also.

Mobile Apps: Customers are also deploying mobile apps in the Field for Data Collection. Both smartphones and tablets are being used for this. Again, these apps work offline and can send data to backend systems directly. Readings for meters, Inspections, and Work Orders can all be managed via mobile apps instead of filling the paper.

Internet of Things (IoT): Companies are deploying smart sensors, smart meters, and smart cameras on assets to collect data more frequently and accurately. For example, Utilities data is being captured by Smart/Digital meters that can help analyze utilities usage. The data from the Smart meters is fed into an IoT Gateway that consolidates all the information in a backend Utility Management System. This allows for better chargeback of utility consumption to customers thus increasing revenues. It also enhances Customer Service at the same time. Also through Smart Cameras, clients are looking at ways to reduce the risk that can identify leaks in real time by analytics assisted image analysis.  This can increase safety significantly.

Machine Learning/Artificial Intelligence: With advancements in data science, computing, and data integration platforms, customers can now leverage these digital transformation toolkits to optimize their business. Leveraging business intelligence, machine learning, and artificial intelligence, these industries have many options for driving costs down through the reduction of operational bottlenecks, asset management, and supply chain optimization. On the top line, these same technologies can be used to optimize assets to find new revenue streams, increase customer satisfaction, and provide overall business transformation into leaner, more agile enterprises.

Business Benefits:

Increase in Revenues, Reduced Costs, Enhanced Safety, and Superior Customer Service are being experienced by customers who have gone Digital in O&G.

Lessons Learned:

There are various points that need to be kept in mind:

  • Data Quality: At the beginning, one should define how the data should look. Various departments like Operations, Maintenance, and Customer Service have their own views of the data. Your data governance models should be able to support these varying views even if the data sources are the same.
  • Understand Your End User: The focus should be on answering the business question and truly understanding the stakeholder(s) process.
  • Quick Wins: Projects with a Quick Win should be selected initially to generate momentum.
  • High Priority: Tackle the Business Problem that is the most important.

As always, please share your feedback or related ideas you may have by writing to us at unvired@sales.io.

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