π Goal: Forecast global crude oil production to support strategic planning, pricing analysis, and energy resource management.
π Dataset
Source: U.S. Energy Information Administration (EIA)
π Approach: Utilized historical production data and applied time series forecasting methods (likely ARIMA or Holt-Winters) to model trends and project future output levels.
Β Global crude oil production exhibits a seasonal and long-term trend, with fluctuations tied to geopolitical and economic cycles.
The model successfully captured historical volatility and projected a gradual production increase in the near term.
Anomalies in recent years (e.g., drops due to pandemics or market shocks) were accounted for in the model, ensuring robust forecasting.
β Impact:
Enables stakeholders in energy economics and supply chain planning to anticipate production levels and adjust strategies accordingly.
The analysis helps identify potential future supply shortfalls or surpluses, allowing stakeholders to proactively manage associated market and economic risks.
Insights derived from the forecast can guide strategic investments in new infrastructure, technology, or alternative energy sources, leading to more efficient resource allocation.
This forecast provides crucial, data-driven input for government policies (e.g., export quotas, budget planning) and corporate strategies (e.g., capital expenditure on new drilling, mergers and acquisitions, diversification).