1 May, 2019

Prospect and Play Assessment: Volumetric Analysis

This technical series is designed to offer working professionals, their coworkers and management a thorough understanding of the fundamentals of assessing oil and gas resources. 

Assessment of prospects and plays requires two types of analysis:

1. How much hydrocarbons may be present = Volumetric Analysis

► Range of potential resources

► Most likely resource amount

2. What is the likelihood of an economic field being present = Risk Assessment

► What is the probability?

This article focuses on assessing hydrocarbons contained in individual prospects and leads through volumetric analysis. Volumetric analysis is a key part of assessment because it helps determine the amount of oil or gas that may be present and gives a range of expected resources. The techniques offered are compiled from reviews of techniques used around the world. The basic objective is to equip explorationists with the most modern and well-considered approaches to solving the business problems of finding new exploratory resources. Part two of the series will focus on the RISK ASSESSMENT.



The value and interpretation of any assessment is based on how success is defined in the analysis. It is important that all parties involved know the standards by which the assessment was conducted. Therefore, the key consideration is defining the meaning of success in the probability analysis.



The definition of “success” can differ across the industry but needs to be consistent within the corporation. The minimum economic approach is the method supported by many companies and is the basis of our Prospect and Play Assessment course; however, all methods are covered.

Others in the Industry recommend alternate methods, typically assessing “geologic success” first and subsequently completing the risk assessment of economic viability later in a second analysis.



How much oil and gas may be present? 
= Average expected amount
= Range of reserves expected



The recommended method for determining how much oil and gas may be present in a prospect is the combination of trap volumetrics and hydrocarbon charge. Ideally, we could map a single volume size, but this is typically unrealistic due to uncertainties for many of the volumetric factors. Uncertainty is a natural fact and normally a unique answer is not the favored solution. Typically, it is best to display the range of all potential sizes using an assessment curve and stochastic modeling.

STEP 1: Define Minimum Economic Size

► Define the minimum field size determined to be economic in play

► Interactive process in a company

► Factors to be considered

• Oil and gas prices expected  

• Development costs  

• Infrastructure costs

• Production costs  

• Production timing

• Corporate economic threshold

• Discount rate

STEP 2: Select Ranges for Individual Factors

The heart of exploration is gathering data that defines a prospect or play. Most of the time spent in exploration is expended data gathering, data interpretation and mapping. Assessment is most often the last step in the process before the decision to drill.  As stated previously, the expected size of an accumulation is one of the two key questions that we need to solve in assessing a prospect or play. The challenge is to determine the size distribution of all legitimate potential hydrocarbon accumulation sizes that could be associated with any given prospect. To achieve this, an evaluation of the prospect volume elements must be completed. It is the explorationists’ responsibility to evaluate, set ranges for and assess all of the prospect volume elements utilized in the calculation of prospect volumetrics. As a review, the prospect volume elements are listed below.


Prospect Volume Elements

► Trap volume

• Reservoir thickness

• Areal extent

► Reservoir properties

• Net/gross ratio

• Average porosity

• Average hydrocarbon saturation

• Percent of trap-filled (hydrocarbon fill)

• Shrinkage or volume factor

• Recovery factor

• Oil or gas fraction of hydrocarbon volume


Combining the prospect volume elements results in the following volumetric equations:

Hydrocarbons In Place = Gross bulk volume of trap  x  net/gross ratio x porosity  x  hydrocarbon saturation  x  hydrocarbon fill of trap volume 

Recoverable Hydrocarbons At Surface = Hydrocarbons in place x  shrinkage factor  x  recovery factor

Unconventional Reservoirs have similar but slightly different characteristics that must be taken into consideration. 


Measures of Uncertainty

Uncertainty is inherent in the interpretation of prospect volume element values and must be addressed or captured.

Typical workflow for explorationists is to map all of the critical geological factors. These factors may include but are not limited to trap type, type size, reservoir presence, porosity, source capability, drive mechanism, seal, and recoverability. Subsequently, a range of values should be selected for each factor. It is imperative that the measures reflect local conditions as closely as possible, incorporating both specific individual values and known variations around each.

Mapping of the prospect precedes the assessment and with modern 3D data sets, much of the inherent uncertainty has been reduced. PPA reviews more traditional assemblage of data so that the students can fully understand the principles behind the value prediction. Note that the approach to trap assessment is to predict total trap volume with no consideration of how much of the trap might be hydrocarbon filled. Hydrocarbon fill factor will be considered separately in a later calculation/prediction.

Figure 1 is an example of a triangular range of reservoir thickness values related to a specific prospect. Based on the data presented, the thickness is expected to range between 25 feet and 75 feet with a mean thickness of 50 feet. The data presented reflects the most likely value (mean) and the range of uncertainty based on local knowledge.


Figure 1. Effective reservoir thickness


Before considering all of the individual prospect elements, let’s review the basics of how uncertainty can be portrayed.

​A key is to remember that though we normally describe the elements by a range of values, in reality, there is only one single true value that we are attempting to model. The problem is that we will never know what that value is until after we drill. That is why care must be used when determining values in the assessments.

Handling uncertainty - issues

• Evaluators historically missed the range for 2/3 of the time

• No difference for P30 and P90 ranges

• People are prouder of their answers than data would indicate

• Uncertainty ranges in are not expanded even when data indicates it should be so


Handling uncertainty – solutions

• Understanding the objectives of the assessment

• Better knowledge – better ranges

• Training in predictions

• Lognormal or normal distribution for specific elements

• Geostatistical refinement by single models or multiple simulations (probabilistic)

• Assessing the Quantity of data vs the Quality of data


Representative Data

It is critical in the assessment that proper specific and range of values are used in the analysis. Following is a quick overview of porosity and permeability and will be jointly considered since there are many dependencies between the two.


Figure 2. Multiple realizations of permeability


This analogue is much better data than we frequently have available in exploration – especially frontier exploration. Given the data, what permeability or range of permeability should be used in modeling?

Answer: P90 or Minimum is not the lowest seen value (4.72) but the value where 90% of the values are equal or greater to that value (6.0). The Mean is given as 10.32 and the Maximum as well should be where 10% of the values are equal or greater (not 24.12) but a bit lower (~19.0). This still gives a log normal distribution for permeability which is what is expected.


Figure 3


The illustration in Figure 3 offers ranges for porosity in several facies in an exploration play. Note the wide range in porosity for some facies compared to the narrow range for others. Compare the data presented here with that of Figure 2. Obviously, the strategy to represent porosity using these data will vary by the facies.


Figure 4 is another depositional system in which the same point can be made as in the last illustration.


Figure 4


The following table offers statistical measures from the data in Figure 4. This data would be very useful in modeling anticipated reservoir properties for an exploration play.


Table 1



Figure 5. Uthmaniyah field, Saudi Arabia


The data in Figure 5 is from the Ghawar area in Saudi Arabia, the world’s largest field. The left panels portray the porosity value ranges by facies and the right panels have permeability values.


Figure 6


The illustration in Figure 6 above, from Ghawar, categorizes porosity and permeability data on a zone-by-zone basis demonstrating another way to illustrate reservoir properties.



Volumetric data is combined to create stochastic volumetric curves (an exceedance curve is shown below) which gives the range of possible volumes (Resource Volumes) on the X axis) and the Probability of those volumes on the Y axis.


Figure 7. Assessment Curve


Play Assessment by Fields

The preferred methodology to estimate the hydrocarbon potential of a play is doing an assessment by fields or potential fields. To estimate play assessment by this approach, it is best to locate perceived areas of success first and then extend the analysis to the area of interest. This method is applied by explorationists who use past discovery-process data as guides but focus on future opportunities.



This is the first assessment question for a play. To answer the question a prediction must be made for the number of and size distribution of the potential fields.


Field Size Distributions

It is important to tie the distribution to the largest anticipated field. Frequently we assess the largest prospect and use that as the anchor for the prediction. A caution here is to be confident that the field used is actually a part of the distribution and not an anomaly. 

The data set should also be truncated on the small side.  This allows the consideration of a manageable amount of data and focus on the most important part of the distribution; where most of the reserves are located. This also focuses efforts onto the economic portion of the size distribution with less distraction toward the small, uneconomic portion.

Field sizes are distributed log-normally as indicated intuitively and based on data from study of fields in trends around the world. This will be very useful in the construction of field size distribution predictions. It should be intuitive that there are many more small fields than there are large ones (Figure 8).


Figure 8. Distribution of oil fields


Baker et al (1986) demonstrate the field size distributions quite conclusively.  Only 440, or 3% of the 13,985 fields in the United States are larger than 50 million barrels. Though these 440 fields represent only 3% of the fields, they comprise 80% of the reserves (Figure 9 and 10). It should be obvious from this data that the large fields are few, but very important in resource assessment.


Figure 9. Plotting representative prospect assessments


Figure 10


In the Baker et al paper, it was also shown that different plays have unique distributions (Figures 11 and 12).  It is imperative that in any volumetric analysis that the proper distribution is employed.  If an inappropriate data set is utilized the results could be disastrous.

As a further demonstration of the lognormal distribution, fields in several plays have been plotted. Even though the shape of the distribution is unique to a play, each of these trends is lognormal.


Figure 11


Figure 12



Correct volumetric assessment of both plays and of prospects involves the collection and analysis of large amounts of detailed information.  For the prospect it means collecting and analyzing data on the source rocks, traps, seals, reservoirs, hydrocarbons and geologic history.  In order to create prospects, the geoscientists must be able to extract detailed information from multiple sources and then extrapolate and creatively predict unseen and undrilled traps.  Thus, in the area of new prospects, the data will be sparse and lacking in many respects and it requires special skills to accurately predict the range the potential hydrocarbon volumes that may be present and the most likely volume to be found.  In play analysis, the geoscientists must gather information from all the existing fields and the existing prospects within the play fairway to accurately predict, on a portfolio basis, how many prospects are likely to be commercial, what is the range of sizes of the remaining prospects and where do the better prospect lie?

Assessment of plays and prospects is an important tool in managing financial and human resources. To learn more about volumetric analysis and more we recommend enrolling in the upcoming session of Prospect and Play Assessment (PPA).

Written by: Jeff Aldrich

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