As time marches on, the technology and approaches for operation and maintenance in the oil field have remained largely unchanged over the decades. It seemed modernization lagged for the oil and gas industry—until now. The digitization of the oil field is occurring at an unprecedented rate—and the future of the intelligent oil field holds the promise of an open environment rich with analytics that dramatically improves personal and environmental safety as well as operational efficiency and production optimization.
Before digitization, oil field operators relied on very crude methods fraught with potential for human error. For example, the traditional method for evaluating and monitoring vent gas flaring to determine gas flow rate is to visually monitor the flame, estimate its length and the time the flame is present and then calculate the vent gas flow rate based on a “rule of thumb” relationship between the heating value of methane in British thermal units (BTU) per standard cubic foot (SCF). A visual inspection of a typical 20 foot flame elevated 30 feet from the ground and viewed at a 100 foot distance leaves an operator’s estimations open to significant error. Two inspectors would likely come up with two different measurements.
A similar challenge is presented with traditional manual flowback measurements. The traditional approach is to examine the difference in two frac tank liquid level measurements on a dipstick at two different points in time to determine fill rate. This is not a precise method.
One of the most significant reasons for the slow availability and adoption of modernization in the industry is the extremely difficult physical environment in which equipment is used and operators work. Unlike a sterile, controlled manufacturing facility, oil and gas fields are hazardous and certainly not clean. Everything is remote, which means every piece of equipment must be able to be disassembled and moved. This leads to a reliance on generator power, which isn’t necessarily a clean power. While the oil and gas environment on land is very challenging, it is even more so offshore.
It may seem counterintuitive that the oil field is gaining momentum at a time when the industry is experiencing a contraction. There are several key factors driving this innovation and enhancing the adoption of this technology.
Increasing personal safety is a major contributing factor, as the nature of the industry and operations can pose personal risk. Greater demands for and understanding of the importance of environmental protection is also driving this technological change to minimize negative ecological impacts, particularly those impacts caused by operational upset conditions. The drop in oil prices has accelerated the need to uncover greater cost savings across the board. This makes spill prevention even more important to avoid significant remediation and cleanup costs associated with an incident.
Reducing non-productive time is key in the relentless pursuit for cost savings, given current pricing conditions. Analyzing performance data has become essential. The digitization we are witnessing is engineering driven to optimize processes. In other industries, digitization may help reduce staff but in the oil and gas industry, it helps maintain rig personnel levels and allows them to do their jobs better and safer.
In the current state of the intelligent oil field, systems and equipment-performance monitoring are becoming more common. These capabilities provide alarms or alerts about current conditions or operational trends that ensure operators have a greater degree of response times to prevent issues from ever occurring.
For example, one user set a single point alarm on a secondary containments vessel to give 16 minutes' notice for a reportable discharge of drilling mud to the ground. By looking at the entire system and placing an alert on the mud gas separator, they were able to have 3.5 hours of response time. Contrast that with the traditional rule-of-thumb approach where you only have the ability to be reactive, and the advantage of digitization becomes very clear.
The key to digitization is to take an open-systems approach and integrate sensors so that one is able to process the relationships to those sensors in conjunction with the manufacturers’ equipment information. Compiling and integrating information can’t be performed in a vacuum—it is optimal to know what each piece of data means relative to each piece of equipment that has been purchased or rented.
One example is a frac flowback system. On this system, flowback operators can set alarms based on a desired response time. If they want 30 minutes' notice before a tank is going to overflow, by using intelligent sensors, the operators can process a rate of change over time to empower them to take corrective action. As that level changes, the operator receives fill rate data, which can then be used to graph the rate of change of a specific point. That’s a new capability and enables alarms and alerts to be set that are specifically designed for operators to have a greater range of acceptable response times.
Exciting applications are improving safety and efficiency. We can tell the intelligent alarms and alerts that are being set are driving the positive behaviors of operators to prevent spills. The proactive capabilities of digitization makes it possible to improve outcomes in specific areas such as performance or preventing upset conditions such as spills, shutdowns or failures.
Current sensor-driven optimization has been focused on each manufacturer’s proprietary equipment without taking upstream or downstream operations into consideration. In other words, sensors currently operate in a silo without integrating other data that is relevant but happening in other parts of the process with other pieces of equipment.
A better philosophy is to take an open-systems approach, which allows monitoring controls to achieve the maximum impact by considering the relationship, and communicating, with all pieces of equipment in a user’s entire system rather than only monitoring the readings of one manufacturer’s machinery. The importance of a systems approach becomes evident when you consider how to optimize a mud gas separator. If we understand a mud gas separator’s fill rate and know that the discharge valve is 100 percent open, then we know the only way to control the fill rate in that instance is to slow down the circulation rate in the drilling operation. By taking a systems approach, an operator could not only receive an alert about a condition in the mud gas separator but also an alert to address an issue with the mud pump that will remedy the issue. In this way, the mud pump and mud gas separator communicate with each other regardless of the make or model of each individual piece of equipment.
Oil field digitization will continue to evolve to embrace a systems approach so that the monitoring of upstream and downstream operations is highly integrated. As an integrated Internet of Things (IoT) systems approach materializes, large data files are going to be produced. At that stage, digitization is going to become very beneficial, thanks to big data analysis that can be applied to those large data files. Applying big data analytics to ever-growing data files will enable operators to model and determine relationships that are currently unknown or not understood that could be optimized to yield a significant impact on the entire system.
Five years ago, flowback was flowback and only considered how fast operators can remove water from the well to start producing. Now, intelligent monitoring and alerts allow operators to employ a strategic flowback strategy that enables them to balance flow rates and pressures to double the return on the well. The future of the intelligent oil field holds not only the ability to realize system improvements previously unattainable, but will also speed future developments in the industry as new system relationship information materializes.