Industry: Oil and Gas Product: ModelRisk Application: Market demand analysis
Global oil demand sat at 102 Mb/d in 2024 — almost exactly the pre-pandemic peak. A deterministic forecast draws a single line forward from there. The chart below draws what the model actually produces: a fan of 50,000 demand paths to 2034, with the median, the P25–P75 band, and the P10–P90 envelope, against the dashed deterministic baseline that grows at a steady +0.5%/year.
By 2034 the median lands near 106 Mb/d, but the P10–P90 envelope runs from roughly 98 to 113 Mb/d — a 15 Mb/d spread that brackets both "demand still rising" and "demand has rolled over." IEA's central case projects 105 Mb/d by 2030; BP's Energy Outlook puts the 2035 range from 90 to 110 Mb/d depending on policy scenario; OPEC sees demand still rising into the 2040s. The decisions that depend on which of those is right — multi-billion-dollar refining capex, upstream sanctioning, midstream pipeline commitments — turn on which scenario, with what probability, and what the joint distribution looks like. An integrated oil and gas major rebuilt its 10-year demand model in ModelRisk around region-decomposed growth, energy-intensity decline, and a discrete scenario weighting of the substitution curve that is the single most important uncertainty in the entire forecast.
Regional GDP growth. OECD economies are modelled with annual log-Normal returns: μ = 1.6%, σ = 1.0%. Non-OECD with μ = 4.2%, σ = 1.5%. The decomposition matters because the elasticities of oil demand to GDP are very different — OECD is at 0.1, non-OECD closer to 0.6 — and a single global GDP collapses that into noise.
Energy intensity (oil/GDP). Continues its multi-decade decline at 2.0% ± 0.7%/year in OECD (electrification, efficiency standards), 1.0% ± 0.5%/year in non-OECD (slower structural transition). These trends are themselves probabilistic; an aggressive policy shift could pull either toward the lower bound.
Substitution / EV adoption. This is the variable for which a continuous Normal distribution would be wrong. The substitution curve is logistic, parameterised by the asymptote L and rate k, and the policy environment determines which logistic. The model uses a three-point discrete scenario distribution:
Substitution is applied 2× faster in OECD than in non-OECD, reflecting where the electric-vehicle stocks live and where the policy is. The total demand at year t is then:
\[ D_t = D^{OECD}_t \cdot (1 - 2 s_t) + D^{non-OECD}_t \cdot (1 - 0.6 s_t) \]
with s_t the cumulative substitution share at year t under the drawn scenario.
The deterministic baseline (+0.5%/year trend) is the dashed line in the opening chart. The probabilistic forecast is the fan around it, which widens to a P10–P90 spread of roughly 15 Mb/d by 2034 — about 15% of 2024 demand. The envelope is close to symmetric around the 106 Mb/d median: non-OECD GDP growth keeps the upper paths rising even against modest substitution, while the fast-transition scenarios pull the lower paths back toward and below the 2024 level.
This is the question the forecast actually exists to answer. Defining a structural peak the way a capex decision cares about it — demand in 2034 ending up below the 2024 level of 102 Mb/d, the curve having turned over and net declined — demand peaks before 2034 in approximately 25% of paths, almost entirely the fast-transition scenarios where OECD substitution outruns non-OECD growth. That is the probabilistic version of "yes, demand might peak by 2030." It is not 100% and it is not 0%, and a capital plan based on either extreme is mis-spent.
The 2034 demand distribution is single-peaked but broad, centred near 106 Mb/d with a long left shoulder, reflecting the discrete substitution-scenario structure: the fast-transition mass sits around 99 Mb/d, the central scenario around 106 Mb/d, and the slow-transition mass around 112 Mb/d. The three overlap into one wide hump rather than separating cleanly — which is exactly why the mean is a misleading planning number: roughly a quarter of that mass sits below the 2024 starting level even though the average is comfortably above it.
The substitution scenario dominates by a wide margin — the single most important input is which discrete trajectory the world is on. Non-OECD GDP growth is second. Energy-intensity decline rates rank third and fourth. The implication for the forecasting function is operational: invest in monitoring substitution leading indicators (EV penetration, policy signals, ICE-vehicle scrappage rates) rather than in higher-precision GDP nowcasting.
The question is not whether oil demand peaks before 2034 — it is the probability it does, conditional on policy and macro paths. Monte Carlo simulation in ModelRisk turns that probability into a number the capital committee can act on, and a $1.2B capex deferral is the price-tag of getting that probability right.