Changes

H4CH12FG12.JPG|{{figure number|12}}Exceedence probability curves for the oil yield over the last 15 m.y. for a selected drainage polygon for the two cases shown in [[:file:H4CH12FG11.JPG|Figure 11]].

H4CH12FG12.JPG|{{figure number|12}}Exceedence probability curves for the oil yield over the last 15 m.y. for a selected drainage polygon for the two cases shown in [[:file:H4CH12FG11.JPG|Figure 11]].

H4CH12FG13.JPG|{{figure number|13}}A probability map of net yield greater than 1 million stock tank barrels (MSTB)/km2. Map has the same areal extent as the map in [[:file:H4CH12FG2.JPG|Figure 2]].

H4CH12FG13.JPG|{{figure number|13}}A probability map of net yield greater than 1 million stock tank barrels (MSTB)/km2. Map has the same areal extent as the map in [[:file:H4CH12FG2.JPG|Figure 2]].

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The goal of this step is to translate the uncertainties in the key input parameters, as described by the probability distribution functions, to uncertainties in the output properties. In the Monte Carlo approach, this translation is accomplished in a brute force manner by calculating a large number of possibilities based on the possible distributions of input parameters. In the absence of calibration data, the results are saved and used to build distributions for the output properties; however, calibration data can be used to show that some realizations are more probable than others.

The goal of this step is to translate the uncertainties in the key input parameters, as described by the probability distribution functions, to uncertainties in the output properties. In the Monte Carlo approach, this translation is accomplished in a brute force manner by calculating a large number of possibilities based on the possible distributions of input parameters. In the absence of calibration data, the results are saved and used to build distributions for the output properties; however, calibration data can be used to show that some realizations are more probable than others.