Why we should NOT use percentages for migration losses

Migration loss is one of the least constrained parameters in petroleum system analysis and modeling. When you ask a geologist how much of the expelled hydrocarbon volumes could have been lost before reaching the traps, the answer typically is a wide range of percentages. I have heard of numbers as low as 20% or as high as 98%. Here I want to argue that is not a very useful way to look at migration loss, and perhaps even the wrong way.

In the follow hypothetical case we have 4 prospects in an area, each having the exact same geology (fetch area, geometry, migration distance, and complexity of the carrier beds, …), with the only exception the estimated expulsion volumes in each of the fetch areas are different as shown below because source variability.

Say we just drilled b and found 500 mmbls of oil in-place, and we estimate 1 billion barrels were expelled in its fetch area. Therefore 500 mmbls (or percentage wise 50 %) were lost in the rock volume between the source and reservoir. What would you then predict the volume of oil charge to be at prospect c, where 500 mmbls were expelled? Is it going to be 250 mmbls, since we would lose 50%, or zero since we would lose 500 mmbls as the two have the same geology?

I ask this question in my training class, while most my mostly explorer students agree it should be zero charge at c, but a few of them may take a bit more to be convinced. If the volume of the rock hydrocarbons migrated through are exactly the same, the lost volume (as residual saturation, and what is trapped in micro or macro traps along the way), required before hydrocarbons reach the trap, should be the same - ie 500 mmbls. For those who still insist on a percentage, I then ask them what would happen if the source rock expels only one barrel.

The implication is really important: In this case, half the number (2) of the traps would not receive charge if we assume the same migration loss volume. But if we used a percentage for efficiency, we would have predicted all traps would have oil. Using percentages would make prospects associated with poor source strength look better, and vise versa, other things being equal.

Since it is very difficult, or impossible, to estimate migration losses, we tend to spend very little time considering it. Based on the above analysis, I recommend running scenarios with different migration losses per unit fetch area to compare prospects. For a given loss volume, a certain number of prospects would not receive charge. More prospects would not receive charge when the assumed loss volume is increased. Prospects with high tolerances to migration loss scenarios tests are safer than those that are too sensitive. This may be an effective way to include migration loss in prospect ranking, even if we cannot accurately quantify this huge uncertainty.