Simulation delivers $10M CapEx savings on natural gas equipment

NG pipeline

Project facts

  • Client
    Global engineering company supporting an energy client
  • Location
    Northern Europe
  • Solution
    The company used Twinn Witness predictive simulation software to build a digital twin model of the reservoir and conduct a Reliability-Maintainability-Availability (RAM) analysis covering a 30-year period.
  • Challenge
    Determining whether a reservoir needed to invest in an additional compressor train to meet fluctuating demand for liquid natural gas.
  • Impact
    Based on the digital twin-powered analysis, the team were able to conclude that the existing two compressor trains would continue to meet the reservoir’s needs, saving more than 10 million dollars in capital expenditure.

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 (LNG). 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 solution

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

The engineering company has used our Witness predictive simulation software for more than 30 years. 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 made it easy for the team to understand future reservoir operations and compressor train requirements – factoring in seasonal demand, mode and maintenance. Importantly, the model also showed the impact of random events like train failure and trading mode variability.

Simulation made it easy to understand future reservoir operations – factoring in seasonal demand, mode and maintenance. The model also showed the impact of random events like compressor train failure and trading mode variability.

The impact

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 that the existing two compressor trains would 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 the 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 modelled, 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.

  • $10 million + capital expenditure savings
  • 30 years of reservoir operations modelled using Twinn Witness predictive simulation software
Briain O'Dowd - Director of Energy and Fuels

BriainO'Dowd

Director of Energy and Fuels