Skip to main content

Modelling risk and returns

Published by
LNG Industry,

Today’s LNG projects are facing complex investment decisions due to the large upfront infrastructure costs, shipping options and shifting global markets. Many of these challenges faced early in the project lifecycle, from pre-FEED and FEED studies to full final investment decision (FID), are decisions that must take account of real world uncertainty such as market volatility, fluctuating supply chains, equipment reliability, evolving operational policies and weather disruptions.

Those currently planning to enter the LNG market require large capital investment in order to build the necessary infrastructure. With such high costs at stake, investors need to be clear that facilities and shipping capacity are able to perform as expected in the face of such a volatile market and shifting supply chain.

From initial scoping studies to the FID, once feasibility has been established, designs for any new LNG facility need to be validated against both short and medium-term operational objectives as well as longer term strategic plans to ensure success.

Predicting success

Predictive simulation is a powerful technology that has been used to achieve this for many years. In fact, over 30% of the world’s LNG capacity and shipping operations have been studied, designed and validated using Lanner’s LNG Logistics Simulation software.

Predictive simulation allows project owners to experience visually how potential operational scenarios will play out across their infrastructure designs. This insight delivers a quantifiable, statistically accurate and unbiased projection of how proposed value chain facilities will function both in a steady state but also crucially how it will react under the stress of real world conditions. Predictive simulation offers the following advantages:

  • Visual experience of how future operations will play out.
  • Quantifiable, statistically accurate, unbiased projection of planned operations.
  • Demonstrates how complexity, randomness and tolerance levels affect plans.
  • Rapidly experiments and evaluates scenarios to understand feasibility and robustness.
  • Quickly and cost-effectively alters the modelled operation as the project matures so that analysis is future proofed.
  • Understands trade-offs and identifies the factors that impact key objectives so that unnecessary cost can be avoided.

The many elements of the LNG value chain each have subtle intricacies, performance variables and operating characteristics that present a variety of challenges when it comes to predicting performance. Lanner’s LNG Logistics Simulator contains a suite of modules, each specifically created to represent different elements of the value chain. Modules can then be selected based on the specific needs of individual projects, delivering an end-to-end analysis tool tailored to the project’s needs.

A case in point

One of Lanner’s customers recently proposed the addition of export facilities to its regasification terminal in Louisiana, US; a move that reflects shale gas viability across the continent.

The project proposes supplementing existing infrastructure with liquefaction trains and additional marine berths, storage tanks and complex marine traffic scheduling in order to begin exporting LNG from the facility to markets in East Asia and Europe.

The project team were tasked with using analytics to better understand future operating options, quantify risks and validate investment milestones to secure commitment and financing from the three commercial partners involved. They needed a model that would allow them to test, refine and validate key decisions during the planning stage, enabling them to balance the requirements from each partner and create a solid business case for investment.

With investment levels around the US$ 7 billion mark, accurate foresight was required into the operational capacity of the terminal so that its long-term import contracts could still be fulfilled while export operations were ramped up. In order to gain accurate projections of throughput and assess the storage capacity required to manage the import and export operations, predictive simulation was deployed.

Lanner was selected because of its depth of experience and expertise in the LNG industry, as well as the configurable modular design of its simulator, built upon its core WITNESS simulation platform. A key requirement was that models developed in the simulator could be re-configured and rapidly re-used by the project team to evaluate new conditions as the project itself evolved.

 Predictive simulation was used to prove that the terminal could operate effectively, with sufficient berthing capacity to avoid undue delay to shipping. One of the main considerations when looking at capacity was that the channel leading to the terminal was particularly congested and susceptible to tides and storms, limiting the number of vessels that could enter and leave at any one time.

The model mimicked the constraints in a ‘real world’ environment so that the project team could accurately test shipping schedules and correctly size the export facility to ensure output would be sufficient for all the partners involved.

Analysis of the projected scenarios confirmed that the terminal could comfortably cope with the planned requirements, but it also demonstrated that the company would require specific maintenance regimes and strategies to manage characteristics that would affect the steady state operation. Increased channel traffic, channel closures owing to bad weather, variable tanker ship sizes and arrival schedule disruptions, and the impact of an increased number of cargoes on train production would each have a significant impact on performance.

The analyses generated by Lanner’s LNG Logistics Simulator were fed into the business case confirming the viability of the new terminal and the predicted operational profitably as set out in the proposal. Through projecting future performance, risk was effectively removed from the project prior to the FID stage.

Real-world behaviour without real-world risk

As the above example demonstrates, predictive simulation mimics events to provide foresight into how a value chain would behave in the real-world against a spectrum of conditions and variables. It is unique in its ability to go beyond static data analysis to reflect dynamic process complexities, interdependencies and real-world uncertainties in order to visualise and predict future performance. Because scenarios can be tested and optimised before decisions are made, risks to performance are better understood and mitigated.

Both the demand and supply of LNG is on the rise driven by the diversification of its use, improvements in technology and lowering costs of extraction. It is difficult to predict exactly how the global LNG market will evolve but it is certain that the challenge of getting the risk/reward balance right is not going to get any easier. The foresight provided by simulators can help LNG value chain players predict how they can capitalise on this opportunity, minimising risk and maximising returns, gaining a clear advantage in this lucrative market.

Written by Steve Hemsley, Lanner, UK. Edited by

Read the article online at:

You might also like


Embed article link: (copy the HTML code below):