Data-Driven Greenhouse Gas (GHG) Accounting Software for Nigeria's Oil and Gas Sector

Abstract Greenhouse gas (GHG) emissions management and reduction targets to meet regulatory requirements in the oil and gas industry are anchored on an accurate transparent quantification and reporting of GHG emissions. In Nigeria, the current GHG quantification and reporting practices are largely manual in nature and fragmented, with an inadequate integration with operational and financial information systems, leading to the emergence of data quality deficiencies, a lack of transparency, and a lack of traceability in the entire value chain. The existing world-recognized GHG accounting procedures, such as the IPCC Guidelines, GHG Protocol and the API Compendium, are difficult to implement in Nigeria because of difficulties in data collection, the dearth of digital infrastructure, and the inability to match with the domestic operational environment. Therefore, this paper developed a Nigeria context-sensitive data-driven GHG emissions accounting software for the oil and gas industry. The framework is envisioned to automate the process of accounting emissions, data processing standardization, and the combination of GHG emissions measurements (based on estimated emission factors for activities) and operational and analytics. The procedure is based on the API Compendium, and automated data ingestion and estimation of Scope 1 and Scope 2 emissions, to comply with the environmental, social and governance (ESG) reporting requirements. The software architecture was tested using a Nigerian context-sensitive oil and gas operational. The findings show that the solution enhances the trustworthiness, auditability, and strategic value of GHG emissions accounting while providing scenario-based decision-support functionality for evaluating reduction plans and their financial cost. The developed software can assist policy makers to make evidence-based policies to decarbonize the oil and gas sector. The developed computer-based framework can be replicated beyond Nigeria once operational local data are available.