Volumetric Uncertainty

Part 13, Chapter 13: Net Pay, Cutoffs, and Volumetrics

Learning objectives

  • Treat each volumetric input as a distribution, not a number
  • Run a Monte Carlo to get the STOIIP distribution
  • Read P90, P50, and P10 and the P10/P90 ratio
  • Explain why the volume distribution skews to the high side

A Number Becomes a Distribution

Every term in the volumetric equation is an estimate with a range. The area comes from a contour map, the net thickness from a cutoff, the porosity and saturation from logs with their own error bars. Feed each as a distribution and the STOIIP is no longer a number but a distribution of its own, found by Monte Carlo: draw one value from each input, compute the oil in place, and repeat thousands of times.

Volumetric uncertainty202530354045STOIIP (MMstb)P9025P5030P1037One Monte Carlo over the input ranges gives P90/P50/P10; the spread skews to the high side.

P90, P50, P10

The result is reported as three numbers, the percentiles of one distribution rather than three hand-picked scenarios. The P90 is the low case, the value the true volume exceeds nine times in ten; the P50 is the middle; the P10 is the high case. An asset is booked against these, with the P90 the conservative number a lender will trust and the P10 the upside the explorationist dreams of.

Why It Skews

Because the equation multiplies its inputs, their uncertainties compound and the distribution skews, with a long tail to the high side. The single honest measure of how well the prospect is known is the ratio of the P10 to the P90: near one, the volume is pinned down and the appraisal is mature; three or more, it is a wildcat whose value will not be known until it is drilled. Widening the input uncertainty fans the whole spread out.

References

  • Capen, E. C. (1976). The difficulty of assessing uncertainty. Journal of Petroleum Technology, 28(8).
  • Society of Petroleum Engineers (2018). Petroleum Resources Management System (PRMS).

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