Abqaiq 2.0: Saudi Grid & Compute Co-Location

Electrical grid dependency mapping. Correlates sovereign compute capacity buildouts with legacy energy infrastructure vulnerabilities, modeling localized power availability following precision strikes.

Saudi Arabia's push to become an AI hub relies on the same power grid targeted in the 2019 Abqaiq drone attacks. This assesses the implications of co-locating strategic compute infrastructure with petroleum assets that have been military targets.

Infrastructure Co-Location Risk

8 data centers, 7 petroleum facilities, 12 co-location pairs. Indirect disruption model: grid co-location with targeted petroleum infrastructure. Active: Abqaiq 2019 ReplaySaudi data centers share power grid infrastructure with the world's most targeted petroleum facilities. The 2019 Abqaiq attack (0% intercept rate, 18 drones, no interceptions) is the proof case. Active: Abqaiq 2019 Replay

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Saudi data centers in the Eastern Province share grid infrastructure with the world's most-targeted petroleum facilities. The September 2019 Abqaiq–Khurais attack achieved 0% intercept across 18 drones, removing 5.7 mb/d of crude processing capacity for two weeks; co-located data centers would lose power as collaterally as the refineries did. 12DC–petroleum pairs sit within grid-coupling distance.

Methodology →SEC annual report · Aramco 2024 · CSIS / UN Panel of Experts S/2020/326 · IISS March 2026

Active scenarioAbqaiq 2019 Replay

Co-Location AnalysisEach Saudi DC paired with the nearest petroleum facility on the same grid zone, with shared-substation flag and exposure rationale.12 DC–petroleum pairs

Grid & SubstationsEastern / Central / Western 380 kV zones, named substations, and which facilities draw from each — the operational basis of co-location risk.3 zones · 8 substations

Attack HistoryStructured ledger of 2019–2022 Aramco strikes — projectile counts, intercept rates, damage class, restoration days. The empirical floor.6 events

Attack Scenario DetailsReference cards for each modeled attack — precedent, payload, primary targets, collateral DCs, expected outage duration.4 scenarios

MethodologyIndirect-disruption model (grid → DC), severity formula, air-defense gap analysis, and source authority tiering for SEC + Aramco data.