October 2016
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Executive viewpoint

Data and analytics take hold in oil and gas production
John Genovesi / Rockwell Automation

The oil and gas industry is embracing and intensifying its use of data and analytics, learning what other industries have long known: tapping into the power of data can help you understand and improve your operations in virtually unlimited ways, or transform them entirely.

Producers are adopting a data-driven mindset, because operations are more complex than ever, with infrastructures expanding dramatically, and more sophisticated systems used in subsea and fracing operations. Regulatory pressures also are increasing. Additionally, new workforce challenges are emerging, as the pool of highly skilled workers shrinks, and more move toward retirement.

But it’s also a matter of continuous improvement. Operators are looking for new ways to increase production growth, refine processes, maximize use of existing assets, and minimize equipment downtime.

Unearthing data. Data collection has long challenged the industry. Unconnected legacy equipment, highly distributed and remotely located facilities, proprietary network silos, and various vendor databases, have limited companies’ abilities to collect, share and act on their own data.

For some time now, E&P companies have moved toward systems and technologies that enable connectivity. This is driving convergence of systems into a single, unified network architecture and the adoption of information-enabled “smart” technologies. This connected infrastructure is known as The Connected Enterprise. It connects people, processes and technologies.

The Connected Enterprise creates opportunities for companies to collect data from nearly any aspect of their operations, analyze it, and share it with decision-makers. This can help companies better understand equipment performance and health, and worker behaviors, as well as analyze long-term trends, optimize asset performance, create predictive maintenance strategies, and minimize failures and downtime.

Better insights into fuel cost savings. When Columbia Pipeline Group (CPG) wanted to modernize its entire control system across 16 states, one goal was to gain better insight into operational data, and better predict maintenance needs. Existing systems lacked the information management needed to optimize operations and didn’t integrate easily into the company’s data warehouse. Lack of a secure user access and authentication system also put information security at risk.

CPG installed a virtualized process control system that shares more information across facilities and up to the executive level, while also enabling remote access and improving security. The company also installed software applications that support system control, monitoring, reporting and data recording over EtherNet/IP.

According to Brian Sloan, automation and electrical engineering manager for CPG, the company is making more educated decisions. Thus, the company’s profitability is improving significantly.

Remotely monitoring offshore drilling equipment. Offshore, submersible pumps are critical to drilling platforms. One producer’s platforms, offshore Alaska, operate 24 hr/day. Downtime can cost this company $100,000 to $300,000/day.

To reduce downtime risk, the company upgraded to more efficient and reliable ESPs. It also uses a virtual-support service to remotely monitor the medium-voltage drives powering the pumps. The cloud-based service collects key equipment data, then notifies support engineers of potential issues or failures, the moment they are detected.

After being implemented, the remote-monitoring service detected and notified personnel of four incidents in the first two weeks. With historical data collected over time, the service also supports predictive analysis to help with maintenance or component replacements before a downtime event occurs.

Redefining business models. Onshore, heavy-duty vehicles that support fracing operations can cost upward of $1 million. They have many consumable components, with oil filters that need to be replaced every 200 hr to 400 hr. A complete engine rebuild is generally required after 4,000 hr to 7,000 hr of service. Vehicle downtime can cost $3,000 to $7,000/day. Also, because they tend to be used in remote areas, most producers keep a backup vehicle onsite, so production can continue if a vehicle goes down.

To understand these vehicles’ performance, and help operators maximize their uptime, equipment supplier M.G. Bryan turned to remote monitoring. The company uses cloud-based software that gathers control-system data from each vehicle and contextualizes it into meaningful information. The software provides insights into drivetrain and fracing performance for a single vehicle, or an entire fleet.

The instant visibility into remote-asset data has improved asset uptime and productivity for end-users. It also allows the OEM to shift its business model from monthly agreements to pay-by-use, giving the company a competitive advantage.

Only scratching the surface. The potential for data and analytics grows every day. For example, we are working with a producer to explore the use of real-time production allocation. This will involve capturing real-time, multiphase flow volumes from all of its wells. The firm can monitor these data to identify assets that deviate from expected production levels and focus on improving their productivity.

As more companies seek to capitalize on their data and become a Connected Enterprise, the decisions they make along the way will be critical to realizing long-term business benefits. Initial decisions should include using integrated control and information solutions; implementing a secure network infrastructure that supports seamless connectivity; and using operations-management software that facilitates fast reading of critical oil and gas production information for operators.wo-box_blue.gif

About the Authors
John Genovesi
Rockwell Automation
John Genovesi is V.P. and G.M. of the Information Software and Process Business at Rockwell Automation. He holds a BS degree in electrical engineering from Youngstown State University, and an MBA from Case Western Reserve University.
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