In the new normal of low oil prices, upstream companies need to review their operating models. Approaches that worked in boom times are not as viable at $40/bbl to $55/bbl. Industry margins have been squeezed so much and for so long that traditional responses such as rig shutdowns and layoffs are struggling to deliver the cost reductions needed. The situation is not helped by additional challenges such as the sector’s aging infrastructure and workforce.

Cut cost, schedule and risk in greenfield projects

The current market environment has caused many upstream players to cancel or defer greenfield projects. However, some are exploring different project execution models. They are investing in more fully integrated digitalized approaches using standardized designs, which are easier, cheaper and quicker to pursue in the downturn. Additionally, they can quickly replicate for even greater profitability if and when prices improve.

Traditionally, about 64% of greenfield projects face cost overruns. And nearly three-quarters also finish late, which further impacts profitability.

Through a new digital project execution model, ABB, in close cooperation with its customers, has proven it is possible to reduce capex and opex by 20% to 30% while accelerating completions by 25%.

Four elements drive the new model (Figure 1). First, virtualization, emulation and simulation lead to more efficient project engineering in the FEED and design stages. Cloud engineering provides improved access to common designs, workflows and tools. Second, digital marshaling with flexible input/output (I/O) channels decouple software from hardware, allowing these activities to be completed in parallel instead of sequentially as before. Select I/O by ABB, for example, allows each I/O channel to be undeclared until just before commissioning, thus minimizing rework. Third, standardization simplifies design and eliminates the need for factory acceptance testing of hardware. Finally, automated data management eliminates many manual steps, reducing scope for human error.

Newer, smaller players such as Lundin Petroleum or joint ventures such as Aker BP have the scope to develop even more disruptive business models. Smaller and more nimble, such operators can more easily explore nontraditional, fully automated production solutions.

Subsea

Despite the downturn, investment in subsea remains strong. This is due in part to the unmanned nature of such solutions that will eventually deliver excellent returns on investment, with capex savings as high as 50%.

With production lines moved to the seabed, more autonomous, remote-controlled equipment will be deployed and managed by onshore operators making decisions using data from long step-outs.

Of course, the difficulty inherent to long step-out systems means that only about 40 such systems have been successfully installed to date, most within 40 km (25 miles) from shore, by a few companies. ABB, however, has mastered the technology that allows long step-out systems beyond 40 km. The Åsgard subsea gas compression project, for example, has a 47-km (29-mile) step-out offering 2-by-15 mega volt amps (MVA). And under a joint development program with Statoil, Total and Chevron, ABB is developing new subsea power solutions to transmit power from shore up to 100 MW over distances up to 600 km (373 miles) and to power equipment at depths of up to 3,000 m (9,842.5 ft). ABB expects this technology will be ready for first pilot installations in 2019, enabling oil and gas extraction farther and deeper than currently achievable.

Reconfigure and optimize ongoing operations

Existing installations face a different set of challenges. Operational downtime in an oil and gas facility can be up to $1 million per hour, so maximizing uptime is key. Keeping production flowing, however, is made more difficult given that many assets are already beyond their expected lifespan. Indeed, it is estimated that around half of all large maintenance projects in mature oil fields are a result of old infrastructure.

Digitalization can help by using real-time condition and asset health monitoring to reduce downtime while reducing the time and expense required to fix issues. Reactive maintenance in an unforeseen, urgent set of circumstances is considerably more expensive than that which is planned. Unfortunately, reactive maintenance remains all too common.

With a digitalized approach, assets are instrumented, interconnected and intelligent, reporting their location, status and other key metrics remotely and automatically.

This facilitates preemptive condition monitoring using systems with predictive data modeling to trigger maintenance orders and prevent breakdowns before they happen. Digitalization also helps determine the optimal way for these assets to interact with each other by providing a view of the entire asset life cycle. Also, asset management can be integrated with other functions and systems such as enterprise resource planning and documentation, thereby enabling even better cost control.

For example, PetroAmazonas EP in Ecuador achieved seven extra days of productivity from reduced downtime due to real-time access to data and remote diagnostics service for preventative maintenance supplied by ABB.

Collaborative operation centers between plant sites, headquarters, or company hub locations and suppliers can yield further benefits. With remote monitoring, troubleshooting and management, staff numbers can be reduced while extending facility lifetimes. This saves cost and, perhaps more importantly, improves safety by decreasing the number of people working in hazardous environments such as remote offshore rigs. Norske Shell, for example, in its Draugen and Ormen Lange fields, has achieved 300 fewer person onboard days and 300 fewer site nights. This tight partnership with ABB has helped Shell achieve 99% uptime most months with more than $1 million in savings and has doubled the lifetime of each site.

At a more extreme level of digitalization, facilities can be entirely automated. At the Al Nasr Field in the Arabian Gulf ABB supplied power and telecoms for seven unmanned platforms and delivered reduced maintenance costs and improved uptime.

Digitalization also can help companies cope with the fact that some 50% of the oil and gas’ workforce is expected to retire in 10 years, taking with them decades of real-world experience and insight.

The digital revolution is making dumb machines smart, facilitating communication between assets and humans. Oil and gas information systems can now even create virtual copies of the physical world by enriching digital plant models with sensor data. These smart ecosystems can aggregate, visualize, analyze and prioritize Big Data to help less-experienced human operators solve problems quickly. Increasingly, machines are making decisions on their own—only escalating issues for human resolution when necessary (e.g., conflicting goals).

While low oil prices are creating many challenges, digitalization offers a range of promising solutions for both greenfield and brownfield sites.

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