Estimating volumes of reserves and resources to provide a “book value” (total assets of a company) is mandatory for any publicly listed oil and gas firm. The primary objective of this process is to arrive at a consistent volume and associated value assessment for companies, investors, lenders, and government agencies.

The book value of reserves and resources – i.e., the amount of hydrocarbons that can be economically recovered from the field – is the net capitalized costs associated with developing oil and gas properties. This calculation is critical, as accountants equate the book value of reserves and resources directly to reserves value which, together with the level of production and commodity price at the time of assessment, are the key metrics used to arrive at the book value of an oil and gas firm.

Book value, therefore, has a direct bearing on both the share price of an oil and gas firm and the approach it takes to portfolio management. Likewise, the forecast techniques employed to arrive at book value exert indirect but considerable influence on commercializations and how all stakeholders, potential investors, and lenders approach investment.

However, the complexity of reservoirs pushes at the boundaries of computational power, and limitations associated with handling uncertainty from geology up to fluid flow behavior continue to result in high risk in terms of the potential production associated with the volumes in place.

The global nature of an oil and gas firm and the increasingly diverse types of plays managed within its portfolio present major challenges to making the right investment decision with given financial resources and incorporating technical and nontechnical risk and uncertainty.

Ensuring compliance with the reporting requirements across multiple agencies and jurisdictions (Table 1) globally also presents a considerable challenge. Numerous rules are applied, and a great deal of latitude exists with their interpretation, which again results in uncertainty when booking reserves and resources.

Industry Pulse 1

TABLE 1. Reserve/resource classification systems.

Uncertainty analysis

There are many uncertainties in respect to calculating book value, which is greatly influenced by hydrocarbons in place and the recovery factor forecast. These are highly affected by the inherent uncertainty of the reservoir, the data gathered, and the interpretation analysis.

Subsurface characterization tools developed by oil and gas firms can be applied to determine and optimize hydrocarbon recovery. These are used to comprehensively assess the reservoir formation and its fluids and are the driving force behind effective reservoir management leading to reserve growth.

There are multiple models of subsurface characterization employed, and there continues to be evolution of both high-end numerical techniques that characterize fluid flow within the porous media and the techniques that model the most fundamental physical behavior of obtaining a geological understanding of the reservoir. Yet historically, reservoir engineering and geosciences have been treated in silos: Geology deals with the rock formations from a static perspective, whereas reservoir engineering focuses on evaluating the performance of a well or field through the understanding of the fluid flow behavior.

This has resulted in uncertainty in terms of accurately forecasting reserves and resources due to factors such as the seismic interpretation, geology of the reservoir between the wells, and fluid flow behavior within the wells. Similarly, there is a certain degree of uncertainty in terms of being able to assess actual production and injection rates and pressure in the multiple wells across a field and how these metrics ultimately impact the accuracy of the production volumes being forecasted.

Gaining an accurate understanding of a reservoir’s reserves and resources using subsurface characterization presents a key challenge in terms of portfolio management. And with the advent of so many different types of reservoirs produced in different ways, it is simply not possible to adopt the same approach across them all.

Disparate models

Today, there are several analysis techniques that are employed to a varying degree by oil and gas firms when researching and forecasting production:

Volumetric. This method is widely used in early stage developments and entails determining the size of the reservoir, pore volume, and fluid content. Recovery factor is later applied based on analogous cases;

Decline curve analysis. This shows how the oil and gas production rate decreases over time based on past performance but has the limitation that it does not incorporate any knowledge of the geology of the field;

Production analysis and well performance. Reserves estimates can be complemented with sophisticated pressure/rate analysis to determine formation and properties in the vicinity of wells;

Material balance. The analysis is of pressure behavior as reservoir fluids are produced and injected. These estimates may provide erroneous results in more complex situations, and the technique also assumes a unique set of properties across a reservoir;

Numerical simulation. This uses geological data and computer models to predict the oil and gas flow behavior of a reservoir. This is a good tool when used properly, but there is a risk of combining production data with erroneous geological information and ending up with optimistic or pessimistic forecasts; and

Integrated asset modeling. The model combines surface knowledge in terms of the restrictions of the facilities with subsurface characterization. This high-end technique is rarely used due to configuration complexity.

Oil and gas firms can use any of these models for developing and creating an understanding of the behavior of their assets. But when reporting to regulators, only decline curve analysis and material balance are widely accepted.

One of the major barriers today is that techniques such as numerical simulation and integrated asset modeling are more difficult to corroborate and audit. This is why companies need to focus on ensuring that internal procedures are both traceable and auditable. In addition, companies need to work more closely with industry bodies to ensure regulators understand why more sophisticated and high-end techniques are necessary – especially where unconventional plays such as shale gas are concerned.

Holistic approach

By definition, portfolio management encompasses having a good understanding of uncertainty. Since there is a risk of political uncertainty or tax regimes changing, these uncertainties have to be factored into investment decisions.

Yet uncertainty also is a key factor in the research and forecasting of reserves and resources. Analysis techniques aside, there is still a lot of work to be done both in terms of geoscience and reservoir engineering to understand the massive uncertainty of a reservoir, subsurface uncertainty, the range of capacity that surface facilities can handle, and the level of investment necessary to realize that capacity.

At C-level, the conventional approach to forecasting reserves and resources to arrive at book value is still deterministic and based largely on the production volume for the previous year. However forecasts – and therefore investment decisions – likely would change dramatically if these had a more probabilistic view of performance.

What is needed is a more probabilistic model for estimation to understand how uncertainty within the reservoir and recovery of the potential range of oil or gas in place affect a firm’s future performance – or indeed, what the future range of production is likely to be. Any model will need to incorporate all past data gleaned from data acquisition campaigns and previous technical analysis.

This is why the work of professional organizations such as the Society of Petroleum Engineers (SPE) is so important in realizing the overall vision of having “a set of reserves and resource definitions widely adopted by the oil industry, international financial organizations, and regulatory reporting bodies.”

Editor’s note: The views represented in this article are not necessarily those held by SPE.