by Juliet Irvin, Guest Contributor

As an experienced assurance professional, I have seen many different approaches to assurance over the years, some more successful than others. The first part of this article explores when and how assurance can be most effective, the role of the outsider, the importance of putting things into context and testing assumptions.

Early Engagement

Early engagement between the assurance team and the technical team is absolutely key. For example, if the assurance team sees the prospect for the first time in the technical reviews (when usually a large proportion of the work has already been completed), it may be too late to steer the analysis and correct any errors, thus exposing a business decision to an incomplete or flawed evaluation.

Imagine an alternative approach, where a member of the assurance team is involved from the beginning of the prospect characterisation and can assist the technical team throughout. Together they can frame the business questions which must be addressed and design an evaluation that is fit for purpose and adds value. For example, there is little value to be had from a very detailed prospect assessment, separating out every fault and reservoir segment, when the business decision at hand is whether to bid a 2D seismic survey to secure a block in a frontier area. This would be a significant waste of time and resources that could have been easily avoided.

The Role of the Outsider

There have been many discussions about project teams conducting their own assurance process while evaluating prospects, vs. the need for external assurance. Which method works best? Having been involved with several hundred prospect assessments, I’m convinced that assurance works most effectively when an impartial and independent person is involved, and that person can contribute by:

  • Being independent and ideally objective
  • supporting the technical team
  • avoiding linkage to rewards and motivations with the decision given their independence
  • providing fit-for-purpose assurance, tailored to the project requirements, organisation size, and skills mix of the prospecting teams
  • having strong facilitation skills
  • testing risk & uncertainty inputs for bias and suggesting mitigations as needed
  • testing assumptions inherent in evaluation
  • benchmarking prospect metrics against others in the portfolio
  • bringing relevant analogues for consideration of reality checks
  • facilitation of the above to converge upon agreed prospect parameters

Putting the Assessment in Context / More than the Numbers

Any prospect assessment is only as good as the inputs (“garbage in, garbage out”), so another key aspect of assurance is understanding what is behind the numbers.  For example:

  • What geological model is being risked?
  • What assumptions form the basis of the parameter ranges?
  • Which parameters have the greatest impact on the volumetrics?

We will now take a closer look at each of these components to explore how impartial assurance, and hence an outsider view, can be an integrated and valuable part of project evaluation.

What is the Geologic Concept for the Prospect?

This may sound like an obvious question, but when this is not clearly understood, it can cause significant problems. To avoid different assumptions, it is important to describe explicitly the geologic model of the prospect being assessed. For example, are we assessing the chance of sand or the chance of a specific environment of deposition? These are not necessarily the same thing. Are there additional geologic models / scenarios, which could yield a success case? Do they need to be characterised at this stage, to maximise understanding of the value of the prospect? Drawing out this clear description up front ensures a common understanding for the technical, management, and assurance teams, and helps to mitigate erroneous assumptions.

When considering analogues, it is vital to consider how likely those scenarios are to occur. For example, if they are highly optimistic cases, management need to be aware of that for subsequent valuation and decision purposes.

Testing Assumptions – What is the Basis of Parameter Ranges?

When conducting a prospect assessment, the technical team will provide a range of values for each of the input parameters, e.g. porosity, net-to-gross (NTG), saturation, etc. Understanding the basis of these ranges is an important part of the assurance process. 

For example: when characterising the NTG, we are usually looking to describe the full range it can average across the prospect, given success. Often the ranges in the assessment do not honour this concept – for example, we may get a maximum NTG value from a single well, or a minimum NTG value seen in a core sample, without considering if those values could represent the minimum to maximum average for the prospect as a whole.

In my experience, a useful way of testing for plausible ranges is to ask geoscientists to draw minimum and maximum NTG maps depicting the environment of deposition (Figure 1). This requires the interpreter to explicitly describe the geologic scenarios which would give rise to those extremes and consider if they are appropriate, and then modify their assessments if needed.

Figure 1. Reservoir geologic scenarios for a prospect (dashed outline) in the SE quadrant of the map

Which parameters have the greatest impact on the output volumes?

“Assess early and assess often” was a mantra often heard from one of my mentors, and it ties in directly with another one: “what business question are we trying to answer?”

Most technical evaluations have both a divergent ideas stage and a convergent stage. Initially the teams are using their creativity, seeking all available information and coming up with ideas of which areas and reservoirs may be prospective. When concepts start to converge, this is a useful stage to engage with the assurance team, to conduct an early prospect assessment, and explore which aspects of the evaluation have the biggest impact on the results.  Figure 2, for example, shows that GRV has the greatest impact on the estimated resources with Recovery Factors influence being minimal.

  • Porosity, net-to-gross
  • GRV
  • Hydrocarbon column height
  • Fluid properties
  • Recovery Factors

Figure 2. Resource parameters and their influence on the resource assessment.

This can ensure the remaining work effort is focused on the most impactful inputs (in this case, GRV), thus avoiding spending time and resources on work that will make little difference to the business decision.

Conclusions

It is very easy to plug numbers into a volumetric software package and calculate a range of outcomes. But are the outcomes meaningful? Do they address the relevant business questions? This is where assurance can help, contributing with early and active engagement, an outside facilitator, an open listening mindset, and some techniques to practically engage with the technical team.

In my view, a key sign of success is when there are no major surprises at the final project reviews, because all relevant aspects of the assessment have already been tested, documented, and addressed along the way with an analysis that has directly addressed the business questions in order to support timely and appropriate decision making.

Management decisions are more informed when the assurance team participates as an advisor, participating in discussions to understand any concerns and provide an independent view of the technical inputs into the analysis and the associated justifications, identify any biases that may have been in play, and communicate the critical risks and uncertainties with the prospect. This can help ensure the conversation is focused on the geologic concepts underlying the analysis, rather than just the numbers coming out. If management concerns are still valid, the assurance team can work with the technical team to address and revise the evaluation if appropriate.

At the end of the day, all technical assessments should help the decision makers make better business decisions by having the right information and analysis available.

About the Author

Juliet is an advanced Risk and Uncertainty Specialist and Geoscientist. She has 22 years’ experience with ExxonMobil (1998-2021) spanning Oil & Gas Exploration, Development, Production, Research and IT, and has been an Assessment and Assurance advisor / specialist for over 10 years. She also has more than 14 years’ experience running professional training classes including Risk & Uncertainty and Prospect and Play Assessment.