AlphaIQ foresight fractal markAlphaIQ
v1.0

Use cases

Six engines, sequenced the way an engagement should be: measurable operational savings first, regulatory enablement second, differentiated technology third, strategic advisory last.

Offshore logistics
Phase I · Immediate ROI
90 days default horizon
Diesel and deck-cargo supply to a Santos Basin pre-salt cluster, comparing direct port-to-platform routing against fixed and self-propelled offshore hubs.

The problem

Pre-salt units sit 200 to 300 km offshore. Every drilling and production campaign depends on a choreography of supply vessels, berths, weather windows and tank levels, and the cost of getting it wrong is not the charter rate — it is deferred production. A spreadsheet sized on average demand cannot see the queueing and weather interactions that actually cause a unit to run dry.

How the model tackles it

Each vessel is an agent with a five-state machine, each producing or drilling unit an agent with its own consumption, tank and reorder trigger. An AR(1) significant-wave-height process gates cargo transfer and degrades transit speed. Mobile drilling units relocate mid-campaign, which is what makes a fixed hub position sub-optimal and gives a self-propelled hub something to chase.

What it is worth commercially

Fleet sizing and charter decisions, hub business cases, and an auditable emissions-intensity number per cubic metre delivered. This is the engine with the clearest and fastest payback, which is why it leads the engagement.

Headline finding

The hub cases reach an acceptable service level with one fewer chartered vessel and roughly 40% fewer steamed miles than direct supply. The self-propelled hub's advantage over a fixed one is second-order at this cluster geometry and grows with demand heterogeneity — a result worth stating plainly rather than overselling.

Reported metrics

Cost per well-day
Charter cost
Fleet utilisation
Stockout hours
Waiting on weather
kgCO₂e per m³
Nautical miles
Service level

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