Emissions Forecasting for Non-Operated Assets in the Oil and Gas Sector

Greenhouse gas (GHG) emissions have become a central concern in the oil and gas industry, which is one of the largest contributors to global emissions due to its reliance on fossil fuel-based processes. As the sector faces increasing regulatory pressure and societal expectations for environmental responsibility, the ability to forecast emissions has become essential. Emissions forecasting enables companies to anticipate future environmental impacts, align with sustainability goals, and make informed strategic decisions. This paper presents a methodology for forecasting GHG emissions from non-operated assets in the oil and gas sector, addressing a critical gap in current environmental management practices. Given the limited access to operational data and the absence of a standardized global approach, the proposed methodology offers a consistent framework for emissions forecasting. It establishes a correlation between emissions and long-range asset plans, incorporating key sources such as fuel consumption, flaring, venting, and fugitive emissions. The process involves defining input parameters, developing linear regression models based on historical data, correlating gas volumes with fuel projections, and calculating CO2-equivalent emissions. Validated with operator data, the model has proven to be both accurate and practical. This approach not only enhances emissions monitoring and reporting but also supports strategic decision-making and sustainability initiatives at the corporate level, contributing novel insights to the existing body of knowledge in emissions management for non-operated oil and gas assets.