A demand narrative that reads convincingly in a boardroom and a market study that survives a lender's independent technical adviser are two different documents. Most of the gap between them is method, not conclusion.
Small-scale LNG projects and terminal developments fail financing far more often on the market study than on the engineering. Not because the demand case was wrong, but because it was asserted rather than built — a narrative stitched from published forecasts and country-level growth assumptions, without the disaggregation and sensitivity work a lender's technical adviser needs to sign off on.
A demand narrative says gas will displace diesel and fuel oil in a given market because it is cheaper and cleaner, cites a regional LNG demand forecast, and concludes the project is well positioned. It is not wrong, exactly — it is just not a model. It has no offtake-level granularity, no sensitivity to price and currency, and nothing that lets an independent reviewer trace a conclusion back to an assumption and challenge it.
A demand model, by contrast, is built bottom-up from identifiable end-use segments — power generation, industrial fuel switching, marine bunkering, city gas — each with its own substitution economics, competing fuel prices, and adoption timeline. It produces a range, not a point estimate, and every input in that range is traceable to a source or an explicitly stated assumption. That traceability is what a lender's technical adviser is actually testing for; not whether the number is optimistic, but whether it can be interrogated.
| Desk narrative | Bankable study | |
|---|---|---|
| End-use segmentation | ||
| Competing-fuel price modelling | ||
| Sensitivity & scenario ranges | ||
| Traceable source per input | ||
| Offtake-side credit view |
Terminal siting, pipeline routing, and last-mile distribution economics are geographic questions that determine which segment of theoretical demand is actually reachable at an acceptable delivered cost. A demand centre 400 kilometres from the nearest viable terminal site behaves very differently in a financial model than one 40 kilometres away — and that difference only shows up if the market study is built alongside a genuine site and infrastructure feasibility view, not handed a market number from a separate desk exercise.
We build demand models bottom-up from end-use segments, with the sensitivity ranges and traceable sourcing a technical adviser expects to see — integrated with site and infrastructure feasibility, not bolted on afterward.
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