Oilfield-services firms are racing to provide end-to-end digital solutions

Over the decades, oil producers have collected reams of data on everything from drillings to well pressure, leaving them with unwieldy datasets that are not always easy to link to one another.

Digital-solutions providers are helping operators with decades of stored data (Image credit: iStock / sorbetto)

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But the industry is rapidly moving toward a more integrated, end-to-end approach, leaders in the digital field have told Upstream Intelligence. This trend is being driven by forward-thinking digital-solutions providers and demand from operators needing to improve efficiency and reduce costs.

“Things have changed even in the last three to six months,” said David Milam, Executive Vice President of Products at Wellaware, a data company servicing oil and gas producers. He said the drop in oil prices had forced companies into reducing head counts to such a degree that they are finding it hard to run certain processes with the amount of staff they have left.

A good digital solution can reduce operational costs by millions of dollars per year. Welder Exploration and Production, a Wellaware client, says it has saved $340,000 per year by using a digital solution to cut the cost of trucks, insurance and man hours, and an additional $265,000 by halving the length of downtime. Fewer incidents have occurred because there are now fewer operators in the field. The company estimated that the payback period for investing in the digital platform was four months.

In the oil and gas industry digital solutions are being provided not only by the big software providers but also by oilfield services companies such as Schlumberger, Halliburton, Baker Hughes and GE Oil & Gas, according to Upstream Intelligence’s recent Offshore Digital Services Report . They have typically focused on advanced production solutions, reservoir management, artificial lift solutions and remote operations.

Traditionally, the approach to providing a digital solution has been to build solutions for data collection; this has ranged from simple solutions such as storing data on a hard disk to more complex data systems. Each of these components has been dealt with in small segments – for instance, analyzing data from sensors or drill report data - but analyzing data across different silos took too much time to create any value, said Satyam Priyadarshy, chief data scientist for Halliburton Landmark.

The key to being able to analyze this data in a meaningful way is integration. The end goal is to be able to collect data from multiple sensors, multiple equipment and look at the problem one wants to solve, Priyadarshy said. Halliburton’s Landmark division has built an integrated modular platform called DecisionSpace which is able to tackle the task.

Components for an integrated solution

Terry Price, Industry Thought Leader and Associate Partner in Global Upstream Oil and Gas SME at IBM, listed integration, analytics, business process management (BPM), data warehouses and visualization as key components to an end-to-end solution.

The Internet of Things (IoT), which is about connecting devices on the Internet so they can talk to one another, is driving many of the methods and strategies for horizontal integration in global operations, Price explained. In terms of analytics there is an increased need to not only monitor production but also react. This could mean having predictive rather than reactive analysis, such as a program that can tell the operator by how much to adjust temperatures, pressures or chemical content to improve production processes, he said.

Price went on to explain that business process management has become a cornerstone discipline for companies that want to grow revenues quickly while controlling resource costs because good BPM provides the ability to process more with less effort and higher quality. Visualization is key to how oil companies use some of the data. It is also a way to engage a younger workforce. The solutions provided by data companies are almost universally customizable and can be tailored to the needs of individual oil operators, he said.

All those interviewed by Upstream Intelligence for this article said customization was a key part of their offering. In IBM’s case, there is no one model; Price said that in some cases the firm embeds advisors within client operations, but all need to have a degree of self-sufficiency.

He said: “These programs have been heavily customized to meet a particular assets need without re-use or sustainability as an object. The approach is to provide a toolbox of products that meet all the various demands of the business whilst respecting the need for integration with other tools and the enterprise. By applying an off-the-shelf set of products we can accelerate time to value and allow the client to grow within a controlled foundation stack. By having access to multiple products then the ability to meet all business needs can be mitigated.”

Cutting out the complexities

The first step in creating an end-to-end solution is understanding the data, software architecture and applications the client uses, what kind of infrastructure it has in place and which processes are automated, said Chris Lenzsch, Solutions Manager at EMC Digital Oil Field and Analytics.

This is followed by comparing the company’s analytics capabilities to best practices. The company providing digital solutions needs to understand the oil operator’s requirements, what results they want to achieve and how the oil company will measure success, Lenzsch said.

Priyadarshy said companies need to be able to access any sources of data quickly and easily, without too much complexity. A key to a good integral solution is the ability to connect data from multiple sources without having to create another new database or data warehouse just for that purpose.

Once a good application is created it becomes an ecosystem which shows the operator how to react to the visuals created by the data, he said.

With technology not sitting still the challenge now is not only to build integrated solutions which can handle the data that is currently available but also to handle the data that will be collected in the future using new and different technologies.

This is where Priyadarshy’s ecosystem metaphor fits into the picture.

By Vanya Dragomanovich