Greenhouse gases emissions evaluation for prospective energy projects
Emelyn Ang A * and Munish Kumar AA ERCE APAC, Singapore, Singapore.
The APPEA Journal 62 S1-S6 https://doi.org/10.1071/AJ21106
Accepted: 11 March 2022 Published: 13 May 2022
© 2022 The Author(s) (or their employer(s)). Published by CSIRO Publishing on behalf of APPEA.
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.
Keywords: Australia, carbon, carbon audit, carbon costs, carbon credit, carbon forecast, carbon intensity, carbon mitigation, development, emissions, emissions forecast, energy, exploration, forecast, fuel consumption, fuel emissions, GHG inventory, greenhouse gases, lifetime emissions, Monte Carlo, oil and gas emissions, Scope 1 emissions.
Emelyn Ang is a Geoscientist at ERC Equipoise, based in Singapore. She holds a BSc degree in Environmental Earth Systems Science from Nanyang Technological University, with a specialisation in Geosciences. At ERCE, she has developed strong skills towards the evaluation of reserves, contingent and prospective resources, exploration, development and production projects, including economic/commercial evaluation. Her work includes volumetric calculation, geological risking, depth conversion and seismic interpretation. She is also familiar with logging and core analysis and as a geoscientist, routinely works with multitudes of data types and forms. Emelyn is also trained as a greenhouse gas (GHG) emissions inventory specialist, where she works with energy professionals to evaluate hydrocarbon project emissions, in accordance with ISO 14064 guidelines for emissions reporting. Aside from oil and gas, Emelyn has performed GHG evaluations for solar projects and downstream operations. |
Munish Kumar is currently a Staff Petrophysicist with ERCE based in Singapore, where he works on matter related to reserves auditing, M&A due diligence, technical expert support in legal matters and greenhouse gas evaluation and validation. His experience spans across most of Asia (Indonesia, Myanmar, Sri Lanka, China, Brunei, Malaysia (incl. Sabah)), PNG, Australia, Gulf of Mexico, Mexico, Alaska, Africa, Cuba, Russia, Ukraine and Brazil. He has previously worked as a Sr Petrophysicist with Total Asia Pacific Exploration (Singapore) where he focused on operational petrophysics and formation evaluation of assets in Asia, Australia and the Pacific region. Prior to this, he was a Sr Petrophysicist with ExxonMobil (Exploration, Development and Production) in Australia and Houston. He has a PhD in Physics and Engineering (Applied Mathematics and Physics) from the Australian National University (2010) and a BEng (Hons) in Electrical and Computer Engineering from the National University of Singapore (2005). His interests include multiphase flow in reservoir systems, core analysis, computer vision and image analysis, machine learning and data analytics applications to oil and gas challenges, renewables and carbon capture and storage. He is a member of the Society of Petrophysicists and Well Log Analysts (SPWLA) and Society of Petroleum Engineers (SPE). |
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