Oil & Gas Sensitivity Analysis
Executive Summary
Key Takeaways
- ✓ Sensitivity analysis in oil and gas modelling applies the general technique to sector-specific variables, commodity price, production decline rate, capital and operating cost, and fiscal regime terms.
- ✓ Decline rate sensitivity is distinct from price sensitivity, since a steeper-than-modelled decline reduces both revenue and reserve life independently of any price movement, and should be tested as its own variable.
- ✓ Fiscal regime terms should be tested in combination with price, not in isolation, since mechanisms such as a production sharing contract's R-factor mean price movements affect both gross revenue and the government-operator split simultaneously.
- ✓ Combined stress scenarios, testing multiple adverse variables together rather than one at a time, reveal compounding effects that individual single-variable sensitivities do not capture.
Objective¶
This guide sets out how the general sensitivity analysis technique applies to the specific variables that matter most in oil and gas financial modelling, within Oil & Gas Financial Modelling.
The Core Variable Set¶
An oil and gas sensitivity analysis should flex, at minimum: commodity price, addressed in Oil Price Scenario Analysis and Gas Price Scenario Analysis; production decline rate; capital cost; operating cost; and fiscal regime terms.
Decline Rate as Its Own Variable¶
A steeper-than-modelled production decline reduces both revenue and total reserve life independently of any price movement, a distinct failure mode from a price decline. Decline rate sensitivity should therefore be tested as its own explicit variable, not assumed to move in lockstep with price, since the two can diverge, a price recovery does not offset a genuinely underperforming reservoir.
Fiscal Terms Tested Alongside Price¶
Where the fiscal regime includes a mechanism such as a production sharing contract's R-factor, addressed in Production Sharing Contract Models, a price movement affects both gross revenue and the government-operator profit split simultaneously. Testing price sensitivity in isolation, without flowing the same price scenario through the fiscal terms, understates the full combined effect on contractor economics, and the two should be tested together.
Combined Stress Scenarios¶
Beyond single-variable sensitivities, a combined adverse scenario, a price decline together with a steeper decline rate and elevated operating cost, for example, reveals compounding effects that no individual sensitivity captures on its own. This combined view provides a more realistic basis for assessing tail-risk outcomes than a set of isolated single-variable tests, complementing the probabilistic approach addressed in Oil & Gas Monte Carlo Risk Analysis.
Common Structuring Pitfalls¶
- Testing price sensitivity without also testing decline rate sensitivity as its own distinct variable.
- Flexing price without flowing the same scenario through fiscal terms tied to an R-factor or similar mechanism.
- Relying solely on single-variable sensitivities without a combined, multi-variable stress scenario.
Continue Reading¶
Related Pillars¶
Related Technical Guides¶
Related Glossary¶
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Frequently Asked Questions
What variables should an oil and gas sensitivity analysis flex?
Commodity price, production decline rate, capital cost, operating cost, and fiscal regime terms, the variables with the most material effect on oil and gas project economics, tested both individually and in combination.
Why is decline rate sensitivity distinct from price sensitivity?
Because a steeper-than-modelled production decline reduces both revenue and total reserve life independently of any price movement, a different failure mode from a price decline, and should therefore be tested as its own explicit sensitivity variable rather than assumed to move together with price.
Why should fiscal terms be tested together with price rather than in isolation?
Because mechanisms such as a production sharing contract's R-factor, addressed in Production Sharing Contract Models, mean that a price movement affects both gross revenue and the government's profit share simultaneously, so testing price alone without flowing it through fiscal terms understates the full combined effect on contractor economics.
Why test combined stress scenarios rather than only single-variable sensitivities?
Because a combined adverse scenario, for example a price decline together with a steeper decline rate and higher operating cost, can compound in ways that no single-variable sensitivity reveals on its own, providing a more realistic view of tail-risk outcomes.
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Oil Price Scenario Analysis
Oil price is one of the single most influential variables in any oil and gas financial model, and should be tested through a defined set of scenarios, a forward curve or bank price deck base case, and explicit upside and downside stress cases, rather than a single flat assumed price held constant across the model's full life. This guide sets out how oil price scenarios are constructed, the difference between forward curve pricing and a flat long-term assumption, and how scenario results should be presented alongside the base case rather than replacing it.
Gas Price Scenario Analysis
Natural gas price scenario analysis differs from oil price scenario analysis in one key respect: gas trades at materially different prices across regional hubs, and long-term contracts, particularly in LNG, are frequently priced against a specific indexation formula rather than a single global benchmark. This guide sets out how gas price scenarios should reflect the relevant regional hub or contract indexation basis, and why applying an oil-style single global benchmark misrepresents gas price exposure.
Oil & Gas Monte Carlo Risk Analysis
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Production Sharing Contract Models
Building a production sharing contract (PSC) into a financial model requires a specific waterfall structure: a cost recovery ceiling limiting how much cost oil or cost gas can be claimed in a period, a carry-forward mechanism for unrecovered cost, and a profit oil or profit gas split that frequently varies with production rate or a cumulative revenue-to-cost ratio known as an R-factor. This guide sets out how to construct that waterfall as a modelling exercise, extending the conceptual definition covered in the Production Sharing Contract glossary entry.