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A global engineering company have supported their energy client with a project analysing their operations at an underground natural gas reservoir in Northern Europe. The team used Lanner's WITNESS Horizon predictive simulation software to investigate whether the reservoir needed additional machinery to achieve the client’s operational goals.

The challenge: Determining whether a third compressor train was required to meet fluctuating demand

Throughout a year, the natural gas reservoir has three operating modes:

  • Injection Mode – Takes place in the summer, when the reservoir is filled from pipelines
  • Production Mode – During the winter, gas is extracted from the reservoir and delivered to nearby urban areas
  • “Trading” or “Shoulder” Mode – Across the spring and autumn months, the reservoir switches intermittently between Injection and Production Modes. This involves multiple quick start-ups and a wide range of pressures and volumes

At the start of the project, the reservoir had two compressor trains, which convert natural gas into liquid natural gas, and the team were tasked with determining whether its client needed to invest in a third train to meet requirements across the three operating modes.

The approach: Using predictive simulation to understand the reservoir’s complex, long-term operational requirements

The engineering company has used Lanner’s WITNESS Horizon predictive simulation software for more than 30 years, and for this project, the team used WITNESS to build a digital twin model of the reservoir and conduct a Reliability-Maintainability-Availability (RAM) analysis covering a 30-year period.

WITNESS offered the valuable ability to conduct continuous modelling of:

  • Fluids, pipes and tanks – to simulate the reservoir’s operation and status
  • Machine breakdown and repair – to simulate compressor train operations, failures and repairs
  • Times and dates – to simulate all 3 operating modes over the year

These WITNESS capabilities gave the team valuable insight to understand future reservoir operations and compressor train requirements – factoring in seasonal demand, operational modes and maintenance requirements. Importantly, the model also showed the impact of random events, such as train failure and trading mode variability.

The outcome: capital expenditure savings in excess of $10 million

Based on the analysis of the data created by the WITNESS model, the team were able to conclude the existing two compressor trains could continue to meet the reservoir’s needs.

Over the 30 years simulated within the model, the third compressor train had no impact on production during the summer's Injection Mode. During winter's Production Mode, there were some instances where having only two trains reduced the rate at which gas was delivered to users. However, over the 30 years models, this only represented 0.06% of operational time, meaning the significant investment was not justified.

The company was therefore able to save its client the substantial capital expenditure – plus ongoing operating and maintenance costs – associated with a third compressor train.

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