Sea1 Offshore Inc (SEA1) Fair Value & Analysis
Energy · NO · Market cap 4.1B NOK
Fair value as of: Jun 24, 2026
Analysis
Sea1 Offshore Inc (SEA1) currently trades at kr 25.50, while our model-based Fair Value estimate is kr 7.84 — implying the stock looks roughly 69.3% overvalued today. We read business quality at 95/100 (high quality), in the Energy sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).
About the company
Sea1 Offshore Inc., together with its subsidiaries, owns and operates offshore support vessels for the offshore energy service industry. The company operates through Subsea Vessels; Anchor-Handling Tug Supply (AHTS) Vessels; Platform Supply Vessels (PSVs); Fast Crew & Oil Spill Recovery Vessels; and Other segments. It provides offshore vessel activities, such as anchor handling and towing, platform supply, oil spill recovery, well intervention services, and subsea operations. As of March 2026, the companies fleet comprised of 15 vessels, including one offshore subsea construction vessel, two well-intervention vessels, six anchor handling, tug and supply vessels, two platform supply vessels, four fast crew, and oil spill recovery vessels. It operates in the North Sea, Brazil, Australia, Canada, Southeast Asia, South America and West Africa. The company was formerly known as Siem Offshore Inc. and changed its name to Sea1 Offshore Inc. in May 2024. Sea1 Offshore Inc. was founded in 20…
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How we calculate Fair Value
Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.
Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.