By Allan Browne, global business line manager field products and services, ROSEN Group, UK
Pipelines are the primary oil and gas transportation mode due to the economic and safety benefits over alternate methods, with an average of more than two thirds of product transported in high-pressure pipelines around the world. In fact, they carry more than double the volume of product transported compared with ships and also significantly more than rail and road.
These valuable assets need to be maintained and replacement can be expensive, especially since many of today’s pipelines are more than 40 years old, meaning maintenance efforts and the associated costs are higher.
Operators need to transport medium from point A to B efficiently, continuously and at minimal cost while ensuring they achieve the best possible availability and throughput. When flow through a pipeline is restricted, there is a direct impact on operations and costs. Flow instabilities, thermal issues, blockages and restrictions, containment loss and operational fluctuations can all affect the safe and economical transportation through pipeline assets.
How can this be assessed? What potential improvements can be made and to what extent?
Who can assess this AND implement any changes required to achieve maximum efficiency? How can improvements be measured and monitored to ensure changes are effective?
ROSEN’s Pipeline Performance Framework (PPF) addresses these questions and recognises the importance of maintaining these assets and the challenges operators face daily.
The framework identifies areas that will improve pipeline throughput, performance and efficiency while reducing maintenance costs, thermal issues and blockages, by utilising consultancy, engineering, technological monitoring support and cleaning solutions services.
Situation analysis and data gathering
The first step of the PPF focuses on the current hydraulic efficiency of the pipeline system compared to what it was designed for. At the design stage, appropriate pipe materials, diameter, length and configurations are established with certain pressures, flow rates, product mixes and environmental and safety factors in mind.
In this consultancy phase, additional information such as historical and current data regarding operations, the product being transported, cleaning performance is also gathered to identify ways to optimise performance and realise potential efficiency gains.
Data assessment and analysis
In the second step an engineering assessment collects data which is securely stored in a data management warehouse and carefully reviewed and analysed by ROSEN experts. In addition to the hydraulic analysis – which may look at the measured flow rates, velocities and system pressures – additional flow assurance assessments and modelling, pigging feasibility studies, cleaning effectiveness evaluations and cleaning tool design reviews can also be undertaken.
Options identification and selection
The next step sees the reviewed data translated into options or identified areas for potential improvement, considering the gap between design and operational practice, as well as current throughput and efficiency performance. Our experts may point to required changes in operation, pressure management, batching, cleaning frequency, cleaning tool design, cleaning approaches, etc.
Next comes the execution phase where one or more of the improvement process steps or system modification recommendations is implemented. Examples could include:
- A modification in pipeline cleaning services.
- Execution of field support services.
- Inventory management and refurbishment services.
- Pigging feasibility and optimisation.
- Pressure and flow management assurance monitoring, etc.
It’s one thing to analyse a system’s performance and efficiency, identify areas for improvement and implement changes to optimise system throughput, but it is another thing to see effects that enhance these elements in action. This is why steps five and six of the PPF provide monitoring support, real-time reporting and visualisation of performance in action.
In step five, experts can collect, store and readily access pipeline cleaning data utilising an instrumentation and app-based service, providing a secure, organised repository for all cleaning data and making it easier for operators to monitor trends and ensure data is never lost – while also making data retrieval more efficient.
Each cleaning run in a pipeline presents an opportunity to collect tangible information about the type, volume and nature of debris removed out of the pipeline as well as about the condition of the utilised cleaning pig. When pigs are fitted with instrumentation like gauge plates or a pipeline data logger (PDL) more information can be gathered from within the pipeline and, if cleaning pigs run routinely, it becomes possible to trend changes over time.
Cleaning analytics for more performance
To optimise the process, an end-to-end solution to collect, process and analyse cleaning data can be used, ensuring confidence in the cleaning program and pipeline conditions. ROSEN’s Cleaning Analytic Service (CAS) uses a phone and tablet app to collect data at the launcher and receiver without the need for an internet connection. Once an internet connection is available, the data is uploaded to ROSEN’s Online Repository for storage and dashboard visualisation.
An integrated environment allows for a more proactive approach to maintenance by collecting valuable data during the cleaning program and cataloguing it for future use.
To ensure the needs of the operator are considered, CAS is provided in two levels:
Level 1 – Basic assessment
Data such as pipeline operating and trap conditions, pig configurations, post-run pig condition, debris type and volume, cup/disk wear, gauge plate measurements and photographic evidence is collected in the field via the app and uploaded to the Online Repository. Featuring a dashboard of predefined KPIs and automatically generated reports, the database provides an overview of all cleaning runs so operators can quickly view the data and draw their own conclusions.
Level 2 – Enhanced assessment
In addition to Level 1, intelligent cleaning pigs containing a PDL are also used, with the purpose of capturing more-detailed information, such as system pressure, differential pressure across the pig in the pipeline, flow velocities, temperature profile, pig stalling, and pig rotation. Experts then analyse the captured data and identify trends, evaluate the efficiency of the cleaning campaign and offer opportunities for improvement, as well as recommend run frequencies and pig configurations, and conduct proactive flow-assurance modelling.
This makes CAS a key component of the PPF in the trend monitoring stage as it is in reporting and visualisation. We recognise the importance of quantifying improvement changes through monitoring, reporting and adjusting operational and maintenance parameters to sustain throughput, maintain savings and therefore decreasing downtime.
Reporting and visualisation
The last step of the framework provides essential feedback to ensure throughput optimisation is monitored so operators can see the effects of the improvements implemented in real time. Guidance is provided for any minor changes required to stay on track and we can illustrate cost optimisation and performance increase in a dashboard report which trends data and key performance indicators over time.
In addition, the PPF ensures that where adjustments are implemented and ongoing monitoring is maintained to quantify improvements, operators can rely on continued support in the form of engineering and consultancy, and feasibility study services when required.
By analysing the captured data using the dashboard, judgements can be made about the efficiency and effectiveness of cleaning campaigns. It also makes it possible to identify optimisation needs and enables users to make the right decisions on cleaning tool configuration and cleaning campaigns.
This will ultimately improve throughput, cleaning efficiency and effectiveness. Throughput is more assured in the knowledge the pipeline conditions are suitable and provides a higher level of confidence that a line is ready for further inline inspections, ultimately increasing first-run success rates.
This article featured in the September edition of The Australian Pipeliner.