The oil and gas industry is undergoing systemic change. Market pressures are forcing us to change the way we do business, and advances in technology are allowing companies to adapt to the changing marketplace. Constraint management is one of these new ideas. It adopts a holistic approach to the power of data that allows for the easy implementation of proactive measures to preclude any events that might cause downtime and optimize all stages and aspects of production, from subsurface to surface and equipment replacement human resource allocation.
This kind of holistic approach has not always been considered. In the past, timetables were used to estimate the integrity of the equipment. Not only was this approach somewhat unreliable and labor-intensive, but it also failed to be cost-effective. More recently, predictive maintenance has been widely implemented. Predictive maintenance is an improvement on the old timetable-based equipment integrity checks—it uses data centric insights, often based on machine learning, to extend equipment lifecycles or identify problems in actionable times. It also requires less manpower than timetable-based maintenance. However, it is equipment-centric and often restricted to specific equipment failure modes, and it still requires a significant amount of man-hours.
Constraint management is the next step forward from predictive maintenance. Constraints exist throughout a facility. Some examples of constraints include tank storage, flow rates, and the amount of chemicals injected. Constraint management is basically the set of activities that involves identifying, notifying, and resolving constraints in an operating environment to eliminate unplanned downtime. The scope is broader than operations and maintenance and can typically involve other facility risk management activities, such as environmental and safety procedures. It provides a system-centric, holistic view that focuses on improving the performance of equipment maintenance and chemical and mechanical processes and personnel allocation. Because it allows for big-picture management of the operating environment, eliminates data silos and personnel isolation, and instead fosters collaboration, coordination, and efficiency.
This transformative approach to process management is made possible using various techniques of machine-learning data analysis, physical models, and artificial intelligence throughput to a visualization platform. PetroVisor™ integrates data from sensors distributed throughout the well, the pump, and the surface facilities into preprogrammed automated workflows, then displays the resulting analytics all in one place on a dashboard, producing alerts based on the end-to-end workflows so that petroleum engineers or operations personnel can optimize their systems to eliminate unplanned downtime and keep production flowing. For example, rather than simply being informed that a flaring event could occur or is occurring, the operator is alerted that a hot rotating bearing is wearing out, which is causing improper fuel intake, and that improper fuel intake could potentially cause a flare. An asset manager can then proactively take the necessary steps to avoid a flaring event, thus saving the facility from unplanned downtime.
Many other solutions to unplanned downtime exist that involve data analytics, but they are typically employed in a fractured framework of different visual analytics and spreadsheets and disparate software platforms stewarded by semi-isolated teams working toward other goals. Constraint management is game-changing, then, because it is all about how systems are integrated. Rather than focusing on a piecemeal approach to systems, it unifies systems, looking for the multiple conditions that could cause an event and empowering operators to approach production as a whole and take proactive measures rather than reactive ones. This approach not only can reduce or eliminate downtime, but it also promotes personnel collaboration, reallocating the necessary manpower for operations, and ultimately saving money while increasing production.
As the industry moves into the future of energy production, management methods that take advantage of cutting-edge technology to prioritize efficiency and collaboration will be crucial to every company’s survival. Constraint management is the future of production optimization in this new landscape.