Complex Traps: A Method for Calculating the Chance-Weighted Value Outcomes for a Prospect with Multiple Trap Styles*

By

Raymond Young ¹, Steven McIntyre ¹, Mark A. McLane ¹, David M. Cook ¹, James A. MacKay ¹, and James Gouveia ¹

Search and Discovery Article #40168 (2005)

Posted September 6, 2005

*Oral presentation at AAPG Annual Convention, Calgary, Alberta, June 19-22, 2005.

Click to view presentation in PDF format.

¹Rose & Associates, LLP, Houston, TX ([email protected])

Abstract 

Exploration prospects require an assessment of both chance and size to quantify value. For most prospects, especially smaller sized ones, it can usually be assumed that the geological chance factors are constant through the entire resource distribution. In larger, more complex traps, however, chance factors often do vary across the prospect. For example, lateral facies changes can result in variable reservoir thickness and quality across the prospect, and multiple trap styles in the same prospect may result in a variable ability to seal.

A common way to estimate the chance of economic success (Pe) is to multiply the Pg (the chance of finding a minimum volume of producible hydrocarbons) by the Pmefs (the chance of finding or exceeding the minimum economic field size). However, because of this focus on finding a minimum accumulation (Pg), the variability of chance factors across the resource distribution is often ignored and can lead to a profoundly optimistic bias.

To illustrate this point, a closure is described for which the potential resource distribution spans an element of updip four-way closure and an element of down-dip, three-way faulted closure. The four-way closure requires only top-seal but the three-way closure requires both top-seal and lateral fault-seal to be effective. In other words, there is an increased chance of leakage associated with the higher resource outcomes. A method for calculating the resource distribution and the chance-weighted value outcomes that result from this trap complexity is described.

Click to view examples of complex traps.

Conclusions 

1. A complex trap is any trap where the Pg varies across the prospect and hence the resource distribution.

2. Using the higher Pg will overestimate the chance of success in a complex trap. Using the lower Pg will underestimate the chance of success. Using the Pg at the P50 area will reduce the error.

3. The correct way to analyze a complex trap is to combine the chance – weighted distribution of each of the trapping styles. Failure to do this could have a profound effect on the estimated prospect value.