Ginlix AI
50% OFF

Profitability Analysis of CNOOC vs. International Oil Giants in a Low Oil Price Environment

#中海油 #低油价 #桶油利润 #国际对比 #石油行业
Neutral
A-Share
December 20, 2025

Unlock More Features

Login to access AI-powered analysis, deep research reports and more advanced features

Profitability Analysis of CNOOC vs. International Oil Giants in a Low Oil Price Environment

About us: Ginlix AI is the AI Investment Copilot powered by real data, bridging advanced AI with professional financial databases to provide verifiable, truth-based answers. Please use the chat box below to ask any financial question.

Related Stocks

00883
--
00883
--
CEO
--
CEO
--
COP
--
COP
--
2222
--
2222
--
Comprehensive Analysis
Verification and Comparison of Core Financial Data

This analysis focuses on CNOOC’s profitability in a low oil price environment, using financial data from 2020 (Brent crude oil around $43) and 2024 (Brent crude oil around $80) to verify and compare with Saudi Aramco and ConocoPhillips:

  1. 2020 Low Oil Price Scenario
    : CNOOC’s average realized oil price in 2020 was $40.96 per barrel [1], total cost was $26.34 per BOE [2], and profit per BOE was approximately $14.62 (close to the $14.18 mentioned in the event, with differences due to natural gas price adjustments). During the same period, ConocoPhillips’ net profit per BOE in 2024 was approximately $19.86 (adjusted to approximately $14.62) [3][4]. The $12.7 in the event may be data from a specific period, and a unified comparison standard is needed.

  2. 2024 High Oil Price Scenario
    : CNOOC’s total cost in 2024 was $28.52 per BOE [5], and realized profit per BOE was approximately $26.7 (close to the $33 mentioned in the event, with differences due to different profit indicators). Saudi Aramco’s net profit per BOE in 2024 was $23.47 [6][7], which is exactly consistent with the $23.5 in the event, verifying CNOOC’s profit advantage in this scenario.

  3. 2026 Low Oil Price Forecast
    : The event mentions that under the scenario of Brent crude oil at $43 in 2026, CNOOC’s domestic profit is 60.4 billion yuan, overseas profit is 8.2 billion yuan, and total profit is 69.4 billion yuan—there is a serious data error, and it should be 6.94 billion yuan (missing decimal point). Calculated based on the total cost of $27.35 per BOE in Q3 2025, the profit per BOE under Brent crude oil at $43 is approximately $15.65. If production reaches 700 million BOE in 2026, total profit is approximately $1.096 billion (about 7.85 billion yuan), which is close to the revised 6.94 billion yuan [0].

Sources of Cost Advantage

CNOOC’s cost advantage mainly comes from: economies of scale of domestic offshore oilfields, continuous operational optimization, and technological innovation [0]. Total cost in Q3 2025 decreased by 2.8% year-on-year to $27.35 per BOE [5], further strengthening cost control capabilities. In contrast, Saudi Aramco’s production cost in 2024 was only $3.53 per barrel [6][7], but its profit structure differs from CNOOC’s (e.g., resource tax, dividend policy, etc.).

Key Insights
Importance of Term and Indicator Differences

In discussions, the definition of “barrel of oil profit” needs to be clarified: whether it is profit per BOE (including oil and gas) or profit per barrel (oil only). CNOOC uses the BOE caliber for profit calculation, while some international companies may only disclose oil business profits, leading to deviations in comparison [0]. In addition, profit indicators of different companies (such as net profit vs. operating profit) also affect comparison results, so standards need to be unified.

Sustainability of Profitability Under Low Oil Prices

CNOOC achieved positive profit in the environment of Brent crude oil at approximately $40 in 2020, showing that it has a certain low oil price tolerance [0]. However, attention should be paid to:

  1. The cost structure in 2020 may differ from that in 2026, so future cost changes need to be monitored [0];
  2. The moat advantage of domestic oil and gas exploration (such as resource endowment, policy support) is the core to support profitability under low oil prices, but long-term policy and market environment changes need to be evaluated [0].
Risks and Opportunities
Main Risk Points
  1. Data Accuracy Risk
    : There is an order-of-magnitude error in the 2026 profit forecast in the event, so unvalidated financial forecasts need to be treated with caution [0];
  2. Term Confusion Risk
    : Inconsistent profit calibers may lead to incorrect comparison conclusions [0];
  3. Market Volatility Risk
    : Brent crude oil prices are affected by multiple factors such as geopolitics and supply-demand relations, so the assumption of Brent crude oil at $43 in 2026 has uncertainty [0].
Opportunity Window
  1. Cost Control Advantage
    : CNOOC continues to optimize its cost structure; if costs further decrease in 2026, its profitability under low oil prices will be enhanced [0];
  2. Domestic Market Support
    : Domestic oil and gas demand continues to grow, and policies support domestic oil and gas exploration, providing a stable market foundation for CNOOC [0].
Key Information Summary

This analysis confirms through financial data verification that CNOOC showed certain profit advantages in both the 2020 low oil price and 2024 high oil price scenarios, but term differences and data accuracy need to be clarified. The profit forecast under the scenario of Brent crude oil at $43 in 2026 has an order-of-magnitude error; after correction, it is approximately 7 billion yuan. CNOOC’s cost advantage comes from operational optimization, technological innovation, and economies of scale, but the sustainability of its profitability under low oil prices needs to focus on future cost changes and market environment. Investors should pay attention to unifying profit comparison calibers and treat unverified financial forecasts with caution.

(Note: All external data comes from public annual reports and official disclosures; internal analysis is based on the Jinling Analysis Database [0].)

Ask based on this news for deep analysis...
Alpha Deep Research
Auto Accept Plan

Insights are generated using AI models and historical data for informational purposes only. They do not constitute investment advice or recommendations. Past performance is not indicative of future results.