Greenhouse gases emissions evaluation for prospective energy projects

Abstract

Greenhouse gas (GHG) inventory assessment, monitoring and auditing is becoming increasingly routine in oil and gas project evaluations. Already, some companies carry an ‘internal’ carbon cost reflected in projected capital and operational expenditure. Early evaluation allows for optimal planning of GHG mitigation and economic analysis inclusive of carbon costs, allaying concerns of investors and lenders. The challenge in evaluating pre-development, however, is the lack of real data and thus, uncertainties in field production. In this paper, we demonstrate the use of a Monte Carlo probabilistic method to better account for uncertainties in production, gas-oil ratio (GOR) and operation loads in a case study of a prospective oil field in offshore Western Australia. We compared the results to the scenario-based deterministic GHG emissions evaluation of the same field and found the deterministic estimates to be extreme representatives of the range of possible emission quantities, due to GOR and production uncertainties. From a breakdown of annual emissions, we also identified the emissions from flaring of excess natural gas to be one of the most significant mitigatable sources of emissions, due to the unexpectedly large production of gas over the project lifetime. Avoiding the flaring of excess gases alone could reduce the project’s emissions by ~44%. Through identifying these key sources and uncertainties, we are able to flag such unexpected, mitigatable sources of emissions at an early stage and provide a representative range of projected emissions, thus assisting the operator to make informed decisions in the field development.