Portfolio Management, Upstream Oil&Gas (part 2/2)
How to Optimize Your Oil & Gas Upstream Portfolio; Upstream Portfolio Management (part 2/2)
Portfolio management or optimization of the portfolio is being referred to by several leaders in energy sector. This article presents an introduction to the topic and intends to introduce how portfolio management is done in E&P sector.
Often what the oil and gas industry refers to as portfolio management is indeed portfolio rationalization. This process is nothing but ranking investment opportunities based on certain KPIs (IRR, NPV, FCF, PI, etc.), and allocating the short/mid-term Capex budget (say 1-3 years) from top to bottom. What is left at the bottom of the list would be deferred, or will be available for promotion. The process usually has a second phase where the strategic considerations are taken into account and few projects may exceptionally find their way up to the investment list. This process can be done for upstream, mid and downstream investment opportunities separately, or all combined in a big bucket. Doing the assessment in both ways would highlight the attractiveness of a segment versus the other. Usually the inter-relations of the projects are assessed when assessing the portfolio in segments i.e. in gas portfolio versus oil, or upstream versus, midstream.
Let’s look at an example, say we have 5 investment opportunities in your portfolio; could be 2 producing assets that require investment to expand their production, 2 greenfield projects (say one is gas and the other is oil field development), and one exploration project. Each of these projects has its unique constrains and a range of uncertainty. For example the exploration project could have a discovery but requires an expensive delineation well to be drilled next year. At this point of time the uncertainty range of the outcomes of the exploration project is from a sub-economic to plus $$$ on a NPV10 basis. There may be options such as early production facilities, or accelerated development scenarios to improve the economics of the project but the development concept cannot be concluded until the delineation well is drilled and tested. Usually the brownfield projects have less degree of uncertainty, however the above example illustrates that in real world when there are several investment opportunities all competing for certain amount of investment capital the optimization of the overall portfolio can be a complicated task. To portray a full picture, companies don’t want to dismiss the business development opportunities therefore let’s say there is an attractive farm-in opportunity which the BD team is pushing hard for investment dollars.
Portfolio management of the above 6 investment opportunities (4 development, 1 exploration, and 1 farm-in) starts with optimizing each case separately. Asset teams would make sure that the development scenarios are well defined, i.e. in terms of reservoir characterization, production profiles, capital investment, Opex, midstream solutions, technology benefits, execution cycle, and other aspect of the project development. Probabilistic distribution for the overall project economics will be developed for each of these optimized business cases. Programs such as Merak PEEP can be used to complete this stage. The result at this stage will be a distribution of the project economics and Tornado sensitivity charts which determine what parameter has the biggest impact (risk) to the project economics (say NPV or IRR).
Projects with more uncertainty (e.g. exploration) might need comprehensive decision tree analysis in order to define the decision options and their risked value at each stage. In such projects often a separate probabilistic analysis is needed for each stage. For example in a decision tree that starts with a wild-cat and moves on with another 3 stage exploration/development phase program (2nd and 3rd delineation wells followed by development phase), each delineation well would have its own probabilistic analysis for Capex and economic value (say NPV). Comprehensive subsurface work would support the POS assumption (risking factor) of each stage. The calculated values would be loaded into the decision tree, the NPV associated to each branch would be risked and finally the overall value of the project would be determined.
A similar decision tree can be built for development projects which are at concept selection phase. However, the focus on development project would be on probabilistic analysis of Capex, schedule and value.
At the end the base business cases and the uncertainty scenarios associated to each of the 6 investment opportunities will be loaded to the portfolio management engine for next round of the scenario analysis. The portfolio will be assessed for several optimization rounds (or constrains) including allowing slippage of the projects to respect certain budget constrain, allowing the application to shift oil assets versus gas assets to optimize for the commodity price uncertainty, give priority to investments with lower levels of uncertainty (smaller standard deviations), optimizing for a particular KPIs (NPV, F&D, EBITA, etc.), optimizing for certain RLI or RRR, and any combination of those factors.
There are several strategic considerations that common portfolio optimization tools may not be sophisticated enough to handle. There is a sustainability factor that in upstream world is measured by reserve-life-index (RLI), reserve-recycle-ration (RRR), liquid mix, political risk index, vertical integration, and other business factors that need to be considered to make sure that the portfolio is balanced from risk and opportunity point of view, and it is sustainable. Other strategic considerations such as renewable energies, corporate social responsibility, environmental goals and commitments (e.g. to the GHG reduction targets), project and per barrel carbon footprint, and so on just add to the complexity. Alignment with partner and commitments to the local governments are other factors create additional constrains and/or give priority to certain projects versus others in bigger portfolios (majors for instance).
The Bottom Line
The industry does the portfolio management in a different fashion than the investment community, and unlikely to the extent of implementing the efficient-frontier (EF). Many consulting firms and application developers are focusing to improve the best practices for oil and gas industry in regards to development and planning and portfolio analysis. Only few companies take the opportunities to optimize their portfolio routinely (more than once a year) as the projects’ life cycles in the oil and gas industry are usually much longer comparing to the investment sector. Nevertheless, emergence of the unconventional plays, higher capital-intensity, inflation of the services and raw material and finally the push from renewables have encouraged oil and gas companies to have a closer look at their portfolio.
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