Oil and Gas

Think leak first

How the oil & gas industry can mitigate catastrophic subsea leaks

By Raouf J. Hadad, P.E., MBA and Han Hsien Seah, MEng September 29, 2020
Source: OOC Subsea Leak Detection Working Group, Advanced Monitoring Subcommittee

The Gulf of Mexico’s aging oil & gas production infrastructure represents both an opportunity for bringing on low-cost subsea developments, and an ever-growing threat of catastrophic leaks, along with all its associated environmental, financial and reputational damage. Evolving technologies, actionable metrics and improved control room operator competencies provide new insights and promise.

The Gulf of Mexico (GOM) is home to some of the most extensive submarine pipeline networks in the world. Over 40,000 miles of pipe were installed for hydrocarbon transport and chemical utility service since 1948, with approximately 17,000 miles of this network still actively used to transport as much as 1.8 million barrels of oil per day from offshore GOM fields.

Much of the currently active pipeline network was installed in the 1990s through the 2010s, although a significant number of these pipelines were already operating when Intel fabricated the very first microprocessors in the 1970s. The rate of new pipeline construction has been declining for over a decade, yet oil production from the GOM set record highs in 2019. This is due to new subsea tiebacks and production platforms that leverage existing infrastructure to reduce development times and improve capital efficiency.

This trend of reusing existing infrastructure means that pipelines will be operated beyond their initial design life. As pipelines age, they are subject to internal and external corrosion, fatigue from pressure and thermal cycling, damage from accidental anchor drags, contact rubbing with other pipelines at crossings, and occasionally, external forces like hurricanes and mudslides. Pipeline coatings can be damaged and sacrificial anodes eventually need to be replaced. Poor welds may also fail unexpectedly in older pipelines. Moreover, many of these subsea pipelines cannot be intelligently pigged so it is difficult to quantify their actual condition.

Today, the average age of GOM pipelines is 23 years, and this will continue to increase as the existing infrastructure is called upon to produce new subsea tiebacks. Good inspection and maintenance of the aging pipeline system will be paramount for ensuring the safe production of GOM oil & gas in the decades to come.

Persistence of leaks

However, despite best efforts at maintaining good integrity, leaks still occur, putting oil on the water. Every year, hundreds of offshore oil spills are reported to the National Response Center. Most of these spills are small, but every few years a major spill incident releases thousands of barrels of oil into the Gulf of Mexico, garnering nationwide attention and outrage. Most recently, subsea leaks in May 2016 and October 2017 resulted in 2,100 and 16,000 barrels of oil spilled, respectively. While the root cause of these two failures differed, they did share two common gaps — a lack of subsea leak detection (SSLD) alarming systems and inadequate operator training in leak detection. This lack of leak awareness directly led to significant delays in shutting down the leaking pipeline.

Figure 1: Age and status of subsea pipelines in the Offshore Continental Shelf of Gulf of Mexico, as of June 2020 (Source: BSEE Data Center, www.data.bsee.gov)

Figure 1: Age and status of subsea pipelines in the Offshore Continental Shelf of Gulf of Mexico, as of June 2020 (Source: BSEE Data Center, www.data.bsee.gov)

Applying leak detection to pipelines that connect the subsea fields to the host platform has been particularly challenging as these fields are often located in deeper waters, so the hydrostatic pressure of the water column reduces the effectiveness of traditional leak detection methods such as the flowline pressure safety low (PSL). These pipelines also carry full well stream multiphase fluids, which exhibit complex flow behavior. Flowmeter instrumentation on subsea wells and flowlines is also limited, precluding use of mass-balance leak detection methods. Even when subsea multiphase flowmeters are available, for a variety of reasons, the measurements may not agree with the topside flowmeters.

Following the GOM subsea leak incidents in 2016 and 2017, and at the request of the BSEE GOM region director, a subsea leak detection subcommittee was formed under the offshore operators committee (OOC), where representatives from BSEE and the oil & gas industry met to discuss concerns about the lack of effective subsea leak detection strategies and solutions. Through this collaborative forum, the OOC committee guidelines focused on a two-pronged approach:

Advanced subsea leak detection monitoring: recommendations on the use of existing process data and control systems to monitor and detect a large leak and shut down in a timely manner.

Training and competency: building and sustaining SSLD competency within the control room operators (CROs) and changing the offshore culture regarding leak detection to “Think leak first.”

The operator’s controls philosophy and the condition of the existing control system on a given facility will drive whether the SSLD logic is implemented within: a) the subsea master control station, b) topsides process control system or c) as a standalone SSLD surveillance station.

Depending upon the available subsea instrumentation, a combination of these protection methods can be incorporated within the control system to cover the full spectrum of SSLD during steady state, transient, and shut-in conditions:

  • Conditional rate of change (C-ROC)
  • Rate of change (ROC)
  • Static pressure comparison with hydrostatic
  • Meter in, meter out (MIMO)

Diagnosis and cure

Subsea leaks are rare events, with a limited amount of (often proprietary) real-world process data available to train or validate leak detection methods. This is analogous to financial fraud detection, where in the vast majority of cases there is no fraud, but when fraud does occur, it is unlikely to look exactly like the last fraud case. Being too specific in defining what constitutes fraud (or a leak) carries the risk of completely missing future incidents — an unacceptable result.

C-ROC overcomes this “overfitting” problem by simplifying the leak detection indicator to a single feature: the rate of change of pressure of a subsea flowline inlet. The laws of physics demand that the pipeline’s internal pressure will rapidly shift towards the external hydrostatic pressure if integrity is lost. Unfortunately, many other normal operating modes and transients also cause rapid shifts in pipeline pressure, both upwards and downwards. This means the ROC method has high sensitivity (it will detect an actual leak with high likelihood) but poor precision (there will be many false positives).

To improve its precision, several conditions are imposed for alarming. These conditions are carefully selected to identify when non-leak transient events are occurring, with a high degree of confidence, and without accidentally misclassifying an actual leak which would result in missed detection. Thus, C-ROC inherits the high sensitivity of the ROC method while also maintaining an acceptable frequency of false alarms, enabling it to be a sustainable and effective subsea leak detection method.

Although C-ROC is conceptually simple, care must still be taken when implementing it on a given subsea system. Produced fluid properties, subsea system architecture, pipeline dimensions, sensor availability/reliability, data bandwidth and spare processor capacity will determine how best to design and configure C-ROC. More aggressive pipeline operations can also trigger additional false alarms, so it is not surprising to see false alarms recur every few weeks with the same crew. Just deploying C-ROC and forgetting about it is not enough because system flow behavior can change over time.

Once the SSLD system is deployed, it is important for the operators to continue to monitor the system and fine-tune it.  Successful implementations include incorporating robust performance monitoring metrics to quickly diagnose any deficiencies or inaccuracies, and to audit important indicators such as uptime, sensitivity and availability. Properly integrated system health monitoring makes it simple to: a) identify the cause of false alarms due to incorrect parameter settings, changing well/flowline conditions or operator actions; b) identify incorrect parameters that could have the SSLD system stuck in a reduced sensitivity state, which could lead to missed detection of real leak events and create a false sense of security; and c) demonstrate the efficacy and historical performance of the subsea leak detection system to regulatory inspectors.

Figure 2: Subsea Leak Detection Methods – Detection Speed and Sensitivity Comparison (Source: OOC Subsea Leak Detection Working Group, Advanced Monitoring Subcommittee)

Figure 2: Subsea Leak Detection Methods – Detection Speed and Sensitivity Comparison (Source: OOC Subsea Leak Detection Working Group, Advanced Monitoring Subcommittee)

Operators are tasked with: a) constantly improving their control room operators’ competency, and reducing dependency on onshore engineering personnel to identify a subsea leak versus other conditional anomalies such as slugging or transient states; b) changing the culture in the control room to “Think leak first;” and c) evaluating and documenting the CRO competency and performance.

Important considerations

Experience over several years researching, designing, implementing, and sustaining subsea leak detection systems informs three areas as important considerations for operators seeking to install or modify SSLD systems.

Carefully select the control system in which to implement the SSLD logic, considering the subsea MCS, topsides PCS/DCS, or installing a standalone surveillance SSLD station. Consider the following questions:

  • Does your existing control system (subsea MCS or PCS/DCS) on the offshore facility have sufficient memory and processing power to handle the SSLD logic?
  • Do you need to implement the SSLD logic across several offshore facilities? And if so, do they have the same control system?
  • Do your offshore facilities have aging/obsolete control systems with limited available support?
  • Does your control system OEM/integrator have experience in implementing the SSLD logic?

These questions will help guide selection of the appropriate SSLD system. Where the Subsea MCS or the DCS/PCS has the necessary memory and processing power, where the same hardware design is implemented on a significant majority of the offshore facilities, and where the OEM/integrator has the requisite experience and capacity to support the SSLD system, then an integrated implementation within the MCS or DCS/PCS is a practical solution.

In contrast, a recent case for a GOM independent operator illustrates a not-uncommon, hybridized environment, in this instance, a deployment of SSLD logic to six disparate facilities:

  • The facilities considered were all acquired from different operators and had different levels of complexity.
  • Some of the facilities had control systems that were aging/obsolete and had limited resources and support.
  • The control systems on the various facilities were supported by different OEMs/integrators.

The ideal scenario in this instance was not to attempt retrofitting the existing installations for a single-supplier solution, but to use standalone SSLD surveillance stations with industry-standard hardware/software routines and customized interfaces to the topsides control systems. The standalone SSLD surveillance station option allowed for a swift, high-quality and economical solution. The interface management effort by the operator was limited, and all that was required of the subsea OEM or topsides DCS/PCS integrator was to provide the data addresses for the necessary values in the chosen native communication protocol.

Additional considerations

Ensure that the SSLD control system includes integrated key performance indicators (KPIs) to monitor the SSLD availability and sensitivity. This is crucial for the accuracy, maintenance and sustainability of the SSLD system. The KPIs will identify any deficiencies of the initial settings and detect the changing dynamics of a flowline. This should not increase the cost of the SSLD implementation, especially if carefully considered during the SSLD design.

Promote culture change for Control Room Operators: “Think Leak First.” Cost control pressures and time constraints are a given in the industry. However, once the initial CRO training is complete, there needs to be an actionable plan in place for continuous improvement. The training is not a one-time exercise, but an element of organizational change management focused on a paradigm culture shift in the control room. Competency and CRO culture are inseparable. Superior SSLD technology alone is not enough. When the technology is coupled with a highly skilled control room operator whose mindset is a “Think Leak First” philosophy, the catastrophic environmental, financial, and regulatory damage of a subsea leak can be avoided.


Raouf J. Hadad, P.E., MBA and Han Hsien Seah, MEng
Author Bio: Raouf Hadad, COO, Ocean Edge Services, is a professional engineer licensed in the states of Texas, Louisiana, and Ohio. Hadad has a Bachelor of Science in Electrical Engineering (BSEE) from Baylor University, and holds an MBA from the Jones Graduate School of Business at Rice University. He also serves on several international oil & gas industry standards steering committee groups. Han Hsien Seah, principal engineer for Ocean Edge Services. Seah holds a Master of Chemical Engineering from the University of Cambridge, and a Micro Masters in statistics and data science from MIT. Prior to joining Ocean Edge Services, he founded and managed the subsea leak detection program for Shell’s US GOM Deepwater Operations. Seah is the original inventor of the C-ROC leak detection algorithm and remains actively involved with the industry’s efforts to improve its capabilities and performance in subsea leak detection.