More aspects of E&P asset and portfolio risk analysis

Oct. 6, 2003
Two other factors that should be considered when assessing the commercial risks to specific E&P projects are influenced by the project's maturity.

E&P RISK ANALYSIS—2

Two other factors that should be considered when assessing the commercial risks to specific E&P projects are influenced by the project's maturity. These are:

1. The uncertainty associated with commercial parameters (e.g., product prices, costs, well deliverability, etc.).

2. The exposure of the project to the fiscal, political, and business environment.

Click here to enlarge image

Fig. 9 illustrates these issues and demonstrates how uncertainty is reduced as projects mature at different stages for different parameters.

The lower part of Fig. 9 qualitatively shows that a company is most exposed to loss, and therefore most vulnerable to changes in the fiscal, political, or business landscape, around the time an oil or gas field comes onstream. That is when most of the development capital is spent but little or no revenue has yet been generated by the project. Project maturity should therefore have an influence on the fiscal, political, and business risks.

Quantitative scoring schemes

The 12-point risk assessment matrices (Figs. 3 to 8) can be used to provide a quantitative assessment in a variety of ways.

One way is to score categories against an index of 100. To do this, the analyst assesses each of the 12 attributes on a scale of 0 (most risky) to 10 (least risky), adds the 12 scores, and multiplies by 0.833 (100 divided by120). The result is a single score for the category out of 100. A score of 100 means no risk or a certain positive outcome. A score of zero means certain failure.

Other scoring schemes can be applied with similar effect. An alternative is to assign a score of 0 to 8 (0 means certain failure or negative impact; 8 means risk-free) to each of the 12 components identified on each matrix. Each score is then added to give a possible total of 96.

In order to focus the commercial analysis specifically to the oil and gas industry, a key 13th factor accounts for the final 4 points. Low scores of 1 and 2 for this key factor place a ceiling on the overall possible scores of 50 and 75, respectively, for that category.

The key factor is a country or region's track record with respect to the oil and gas industry with scores of:

1 = very poor track record

2 = poor track record

3 = moderate track record

4 = good track record

Both scoring schemes described generate a category score with 100 as the maximum. This score can be manipulated in three ways to give useful related scoring systems:

1.Expressed as a percentage, it indicates the percentage chance of "success" or "positive outcome."

2.As a probability scale of 0 to 1 by dividing the 1 to 100 score by 100. The probability scale can be considered as a probability of success and used as one component in an overall risk adjustment scheme (e.g., Table 1).

3.Inverted to a 0 to 5 risk rating scale (0 = risk-free; 5 = very high risk) in order to compare with some of the political risk assessment systems commonly adopted by industry analysts. This scale is derived by subtracting the score of between 0 and 100 from 100 and dividing the result by 20.

Integrated assessment scheme

A probabilistic risk assessment scheme that integrates all 12 of the subsurface and operational categories, outlined in Table 1 and discussed above, is proposed for a systematic approach to E&P assets or projects.

The first six components are related to the subsurface quality of the pros- pect or field (reservoir, trap, source rock, etc.). The second six components are operationally focused. It is here that the political, business, and fiscal assessments are combined with project location, technological, and timing assessments.

The 12 components can be equally weighted (as shown here) or skewed with independent weightings to suit a company's portfolio or preferences. For example, a portfolio consisting primarily of producing assets may wish to replace or place much lower weight on the subsurface categories associated with source rock and migration as these will always score 1).

Each of the 12 components contributes equally (i.e. 8.333%, see Table 1) to the overall chance of success factor. Weightings could be applied to increase the influence of some factors.

A 12-component system, with each component deemed to be independent and therefore multiplied together to provide an overall success factor, requires several high scores and very few low scores to achieve meaningful chances of success. Even if all 12 factors score 0.95 on the scale 0 to 1, the overall success factor only reaches 54%.

A workbook of spreadsheets included in the executive report that accompanies this article includes alternative scoring schemes that allow different weights to be applied (using the addition rule of probability rather than the multiplication rule of probability applied here) by assuming that the risk components are not independently interacting.

Whatever scheme is adopted should be applied consistently.

For the multiplication scheme presented here, the reality is that for high quality assets and projects several of the components should have scores close to 1. Exploration projects scoring, on a fully integrated basis, in the range 1 to 50% chance of success and production-development projects scoring in the range 50% to 90% are consistent with the actual project outcomes recorded by many oil and gas companies.

The fiscal terms risk-assessment category is primarily associated with such conditions as the stability, complexity, difficulty of administration and interpretation rather than toughness of terms on a project economic basis. Tough terms will be addressed in the cash flow models and the profit share earned under the fiscal contract.

Some schemes incorrectly assess the economic aspects of the fiscal terms in such risk assessment (effectively double-accounting or adjusting for it). In this integrated risk scheme, fiscal risk is only allocated a weight of 1/12 (i.e. 8.33% weighting, in line with all the other 11 categories assessed).

Other risk analysis schemes place a much higher emphasis on fiscal terms and their economic performance. In the IHS scheme, for example, fiscal risk accounts for 35% of the overall risk-assessment scheme (with political risk 15% and technical risks 50%). If used to adjust a cash-flow model that already incorporates the fiscal terms, the assessment will penalize tough fiscal terms twice over.

Another aspect of an integrated risk assessment scheme is that the credibility of ongoing risk analysis can be undermined if repeated forecasts lead to severe risk adjustments for projects, but the forecast risks fail to materialize, or if they do happen, their consequences are less severe than forecasted for whatever reason.

It is sometimes argued that political risk analysis is invalidated by the fact that certain forecast events did not transpire but the perception that they might have led to overly cautious business decisions. In probabilistic systems, eventualities with chances of occurrence significantly less than certainty (1) may never occur, but this does not mean that they could and will never occur and should not be factored into risk assessment and business decisions.

Generic oil-gas projects

Click here to enlarge image

Table 2 shows risk analysis applying the proposed scheme for an indicative E&P project in a hypothetical country as it evolves through the exploration, development, and production stages.

In this example, the subsurface risks decrease as one would expect from exploration (21% chance of success) through development (75% chance of success) to production (90% chance of success).

In contrast, the operational risks are highest during the development phase because it is at this stage that the company is most exposed to technological timing and political risks (i.e., it is outlaying large capital sums for little or no short-term cash flow). Hence the operational risks are often moderate in the exploration phase (49% chance of success), high in the development phase (36% chance of success), and moderate to low in the production phase (69% chance of success).

In the production phase, particularly after payback is achieved and only limited infill drilling is planned, technological and timing risks often diminish or disappear unless aging plant and large decommissioning liabilities loom.

The fully integrated risk assessment (multiplying subsurface and operational risk factors) suggests very high risk for the exploration phase (10% chance of success), high risk during the development phase (27% chance of success), and a moderate risk during the production phase (62% chance of success). This integrated assessment is closer to reality than either of the subsurface or operational assessments considered in isolation.

As already mentioned, the probabilistic approach is simplistic and provides only an approximation to an integrated project success factor. Another drawback to probabilistic methods in general is the subjective way in which probabilities are often assigned to the component attributes. This provides scope for the unscrupulous to manipulate the results.

The use of a transparent multi-attribute system, with information coming from several departments and individuals and applied in a rigorous and systematic way for each project, provides the best safeguard against subjective manipulation.

At the present time, probabilistic assessments of risk combined with simulation analysis to integrate parameter uncertainties offers one effective way of achieving an integrated assessment and risked valuation at the asset level. However, many of the commercial facets of risk are fuzzy and nonrandom and can also be dealt with using possibility theory and fuzzy logic.

There is potential to develop future models that integrate probability and possibility theory to produce more accurate methods to calculate integrated project success factors.

Integrated success factor

A useful adjustment to make using the success factor is to convert discounted cash flow estimates (net present values, or NPVs) for each oil and gas asset into expected monetary values (EMVs).

These can then be used to derive risk-weighted corporate asset portfolio values providing input to portfolio models,2 3 which will evaluate additional portfolio risks (i.e., risks of failing to achieve corporate strategic targets).

Care should be taken when applying sophisticated portfolio and project risk analysis software that identify specific portfolio and project risks without taking into account the risks inherent in the component assets. Some users are fooled into thinking that the risks derived from such models automatically encompass all the risks that impact the underlying assets. They do not, unless such asset risks are specifically assessed and incorporated into the models.

It is possible to take the reserves or production contribution (or forecast contribution) from each project in the portfolio and weight the success factor to derive an overall success factor for the portfolio. The portfolio success factor can also be used to benchmark and compare the risk exposure of the E&P portfolios of a peer group of companies (e.g., for risked valuations, merger and acquisition purposes, and assessment of ability to deliver their stated strategic targets), assuming that subsurface risks can be estimated with meaningful accuracy for competitors without access to their subsurface data.

It is also appropriate to adjust companies' growth and return on investment forecasts by use of the portfolio success factor. Such adjustments are how quoted unrisked targets which overstate true performance potential are moved towards those returns and growth rates that have been historically achieved on a long-term basis by the industry as a whole.

Click here to enlarge image

Fig. 10 shows how such adjustments are made with the risk assessment data.

Other quantitative schemes

The scheme described here is by no means the only holistic method that can provide useful quantitative E&P risk analysis results.

For example, the scheme proposed by Sandrea 4 involves assessing uncertainty in upstream projects with the objective of ranking them as potential equity or debt investments for financial institutions.

That scheme includes three components (i.e., reserve potential, finding and development costs, and company performance) that commendably attempt to provide opportunity offsets to three downside risk components. However, it relies on averages and ranges taken from data base benchmarking studies to provide scales for the different components.

By their nature benchmarked data bases rely on historical, and in some cases out-of-date, data and, as others have noted, frequently do not have the accurate and detailed information needed to compare different projects on the same basis (e.g., Avidan and Hernandez5).

Comparing different projects using only a few criteria and incomplete data can be deceptively simple, but often does not take into account key differences between specific projects. The averages and ranges derived from Sandrea's approach and the methodology are clearly useful for general conclusions regarding country potential, but the author believes that these are less reliable for detailed and integrated risk analysis of specific projects than the more project-focused approach presented here.

Another holistic approach that has gained some favor amongst some risk analysts and project managers attempts to place absolute expected monetary value distributions on a myriad of potential outcomes for identified risked events, based upon expert panel assessment ranges of the likelihood (probability) of occurrence of each outcome multiplied by the cost of impact if an outcome should occur (e.g. Bowden et al.6).

The project is then valued using simulation techniques, including the expected risk cost distributions. Some sensitivity or simulation cases also incorporate estimated costs and benefits of various risk mitigation strategies devised as part of a structured and systematic risk analysis process (e.g., cost-benefit analysis).

This approach can work well for several of the operational risk categories where cost outcomes of risk events that might materialize can be either directly or indirectly estimated within acceptable levels of accuracy. It is also useful for profiling and ranking the significance of specific potential events.

However, it is much more difficult to apply this approach to the full spectrum of less tangible subsurface and political risks required for a fully integrated analysis.

The author supports this absolute, expected cost approach during the valuation process to build in well-defined value estimates of downside risks and upside opportunities (e.g., for field development cases) into cash flow distributions where the estimates can be made to acceptable levels of uncertainty. However, pushing this approach too far to try to quantify cost outcome distributions for extremely "difficult to quantify" events, with wide reaching and subtle impacts (e.g., political instability, inefficient bureaucracy etc.), is likely to generate highly subjective and imprecise valuation models which themselves risk losing credibility and become difficult to justify or verify.

Conclusions

The E&P sector, in order to reconcile its poor organic growth performance results with its forecasts for production and earnings growth resulting from activity with the bit rather than the merchant bank, in general needs to apply risk assessment in a broader, more rigorous and integrated manner.

There is currently no accepted standard, and many companies seem content to mislead their shareholders by issuing forecasts (or remaining silent while analysts do so on their behalf) that are adjusted inadequately (if at all) for risk and make no attempt to be transparent about the exposure of the assets in their portfolio to the various facets of risk.

Frequently analysts' risk assessments of an oil company's performance and forecasts are based on last year's financial statement numbers, some broad-brush speculation on growth potential, and limited assessments of political, fiscal, and business risks of countries, making no attempt to address the not inconsiderable asset-specific, subsurface, and project risks.

The integrated E&P risk assessment system outlined here provides one scheme that ensures that a broad range of subsurface and operational risks are systematically addressed asset by asset, while avoiding some of the subjectivity and data base approximation pitfalls of other methods.

The combined scoring system is tough but if applied rigorously and systematically to all assets within a portfolio should yield more meaningful and project-specific calculated risk and success factors that are in line with the historical performance of the industry.

No scheme will provide exactly the "right" numerical answer, but an integrated probabilistic approach offers at least to provide insight to the many facets of risk to which E&P projects are exposed by applying a transparent and simply displayed system.

The number of dry holes drilled and field development projects and pipelines delayed by political disputes testifies to the fact that the industry is exposed to both subsurface and operational risks and cannot easily avoid taking quite high risks if it is to succeed. Far better to evaluate risk more comprehensively and build it into forecasts more openly, thereby providing shareholders and management with fewer unpleasant surprises.

The recent and sudden downward adjustments of the long-term growth forecasts by several companies based on their own portfolio performance reviews (e.g., Shell, BP, and others during 2002) suggest that the industry still has a long way to go to successfully assess risk and in disclosing internal assessment techniques and risked valuations.

References

1.Wood, D.A., "Probabilistic Methods with Simulation Help Predict Timing, Costs of Projects," OGJ, Nov. 12, 2001, pp. 79-83.

2.Wood, D.A., "Three-Stage Approach Proposed For Managing Risk In E&P Portfolios," OGJ, Oct. 23, 2000, pp. 69-72.

3.Wood, D.A., "Portfolio Optimization Benefits from Integrating Analysis of Risk, Strategy, and Valuation," OGJ, July 8, 2002, pp. 26-33.

4.Sandrea, R., "Upstream opportunity index assesses E&P investments," OGJ, May 19, 2003, pp. 18-22.

5.Avidan, A., and Hernandez, R., "Benchmarking study" (letter), OGJ, June 30, 2003, pp. 11-12.

6.Bowden, A.R., Lane, M.R., and Martin, J.H., "Triple Bottom Line Risk Management: Enhancing Profit, Environmental Performance and Community Benefit," John Wiley & Sons, 2001, 314 p.

Click here to enlarge image

The author
David A. Wood (woodda@ compuserve.com) is an international exploration and production consultant specializing in the integration of technical and economic evaluation with management and acquisitions strategy. He also provides an extensive range of training on upstream economics, international fiscal terms, strategic portfolio and risk analysis, both as an independent trainer and on behalf of several training organizations. After receiving a PhD in geochemistry from Imperial College in London, Wood conducted deep sea drilling research and in the early 1980s worked with Phillips Petroleum Co. and Amoco Corp. on E&P projects in Africa and Europe. During 1987-93, he managed several independent Canadian E&P companies (Lundin Group), working in South America, the Middle East, and the Far East. During 1993-98, he acquired and managed a portfolio of onshore UK and North Sea companies and assets before becoming a consultant. Wood is the author of four Oil & Gas Journal Executive Reports on risk analysis and related subjects (for information, contact Linda Barzar at 713-963-6229; email: [email protected]).