
Scenario analysis
Scenario Analysis Methodology
We test the resilience of our portfolio of producing assets and sanctioned projects against the published scenarios from the International Energy Agency (IEA) which span a range of temperature outcomes: STEPS (2.4oC), IEA Announced Pledges Scenario (APS) (1.7oC) and Net Zero Emissions by 2050 (NZE) (1.5oC).
We use annual average free cash flow (FCF) generation as the assessed metric because it is a measure of our ability to fund future capital investment and shareholder returns and is unaffected by accounting treatment.
Our analysis uses the most recent pricing assumptions from IEA (in their World Energy Outlook 2024).1
The analysis applies a price on carbon for all emissions that exceed the profile created by our regulatory obligations, our net equity Scope 1 and 2 greenhouse gas emissions reduction targets of 15% by 2025 and 30% by 2030, and our aspiration for net zero equity Scope 1 and 2 greenhouse gas emissions by 2050 or sooner.2 The impact of carbon pricing upon Scope 3 emissions is accounted for in the demand (and therefore commodity price calculated) in each scenario by the IEA World Energy Model.3
Scenario analysis of Woodside’s portfolio
Woodside’s current portfolio is financially robust to a range of climate-related scenarios.
Scenario analysis is a tool which contributes to our assessment of the risks and opportunities related to climate change. There are many different scenarios and methodologies for producing them. Scenario analysis of our portfolio is conducted by varying our expected cash flows in accordance with the commodity prices provided by the IEA in those scenarios.
Scenario analysis on its own does not provide sufficient insight into future risk and opportunities on which to base business planning. Woodside does not adopt a single scenario for planning purposes. Rather, the assumptions used for Woodside’s internal business planning, such as for investment decisions and asset valuation, require a broader range of inputs. These inputs include consideration of climate-related factors, including both Paris-aligned and non Paris-aligned outcomes. They must also include other factors such as economic growth, inflation, exchange rates, interest rates and geopolitics. They consider the specific role of LNG (as opposed to aggregate gas use) and regional differentiations (as opposed to globalised data). Together these factors can inform a broad based consideration of risks, opportunities, competitiveness and resilience. They contribute to understanding the potential impact of climate-related risks alongside other risks to our strategy, business and financial planning.
For the 2024 assessment, we have continued to utilise pricing assumptions derived from the three main scenarios in the IEA’s World Energy Outlook, updated for its latest edition. These span a range of temperature outcomes: STEPS (2.4ºC), IEA Announced Pledges Scenario (APS) (1.7ºC) and Net Zero Emissions by 2050 (NZE) (1.5ºC).5 It is important to note that the assumptions which underpin these scenarios do not constitute the only potential pathway to achieving those outcomes.
Our 2024 analysis, depicted in the chart, concludes that:
- The Woodside portfolio is Free Cash Flow (FCF) positive for all periods, highlighting resilience of the business, including in the Net Zero Emissions Scenario (NZE) and the IEA Announced Pledges Scenario (APS), that are aligned with the Paris Agreement temperature goals.
- FCF from 2025-2029 is lower than 2030-2034 (under all three scenarios) due to high capital expenditure during this period on Scarborough, Pluto Train 2, and the Trion development.
- FCF peaks under all three scenarios in 2030-2034 as Scarborough and Trion are operating and then declines consistent with the natural field decline of older assets within our portfolio.
Scenario analysis has limitations and is based on a wide range of assumptions. It involves interpreting each scenario to generate average price points (these assumed price points are provided in the chart below).