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Basin modeling is an increasingly important element of exploration, development, and production workflows. Problems addressed with basin models typically include questions regarding burial history, source maturation, hydrocarbon yields (timing and volume), hydrocarbon migration, hydrocarbon type and quality, reservoir quality, and reservoir pressure and temperature prediction for pre–drill analysis. As computing power and software capabilities increase, the size and complexity of basin models also increase. These larger, more complex models address multiple scales (well to basin) and problems of variable intricacy, making it more important than ever to understand how the uncertainties in input parameters affect model results.

Basin modeling is an increasingly important element of exploration, development, and production workflows. Problems addressed with basin models typically include questions regarding burial history, source maturation, hydrocarbon yields (timing and volume), hydrocarbon migration, hydrocarbon type and quality, reservoir quality, and reservoir pressure and temperature prediction for pre–drill analysis. As computing power and software capabilities increase, the size and complexity of basin models also increase. These larger, more complex models address multiple scales (well to basin) and problems of variable intricacy, making it more important than ever to understand how the uncertainties in input parameters affect model results.

Step 6: Propagate the uncertainty in key input parameters through to the output properties of interest via Monte Carlo or similar analysis.

Step 6: Propagate the uncertainty in key input parameters through to the output properties of interest via Monte Carlo or similar analysis.

* The final step is a Monte Carlo simulation where values for the input parameters identified in step 4 are randomly selected from the distributions assigned in step 5. The key results from each realization are saved for subsequent evaluation.

* The final step is a Monte Carlo simulation where values for the input parameters identified in step 4 are randomly selected from the distributions assigned in step 5. The key results from each realization are saved for subsequent evaluation.

Step 7: Iterate as needed to fine tune the input parameters and dependencies between input parameters, to fine tune error bars and weights for calibration data, and to improve the base-case scenario.

Step 7: Iterate as needed to fine tune the input parameters and dependencies between input parameters, to fine tune error bars and weights for calibration data, and to improve the base-case scenario.

* Although several approaches could be used to quantify uncertainty in models, the approach presented uses Monte Carlo simulation. Monte Carlo simulation has the advantage of being (1) able to handle any probability distribution function, (2) able to account for dependencies between variables, and (3) straightforward to implement. It is also typically straightforward to analyze the results of the Monte Carlo simulation. The disadvantages include that it may require a large number of realizations to adequately sample the possible solution space, and it may be difficult to adequately develop probability distribution functions or the required realizations, particularly for maps and volumes.

* Although several approaches could be used to quantify uncertainty in models, the approach presented uses Monte Carlo simulation. Monte Carlo simulation has the advantage of being (1) able to handle any probability distribution function, (2) able to account for dependencies between variables, and (3) straightforward to implement. It is also typically straightforward to analyze the results of the Monte Carlo simulation. The disadvantages include that it may require a large number of realizations to adequately sample the possible solution space, and it may be difficult to adequately develop probability distribution functions or the required realizations, particularly for maps and volumes.

[[File:H4CH12FG2.JPG|thumb|300px|{{figure number|2}}Present-day depth structure map (meters) of the key migration surface. The outlines of the drainage polygons are shown in black, the closures are outlined in red, and the escape paths are shown in green. The scale bar in the legend represents 12,500 m (41,010 ft).]]

[[file:H4CH12FG3.JPG|thumb|300px|{{figure number|3}}Cross section through the model along the line AA' shown in [[:file:H4CH12FG2.JPG|Figure 2]].]]

==Hypothetical example==

==Hypothetical example==

A hypothetical example is presented to illustrate the approach described. Although the geology is synthetic, it was constructed with realistic basin modeling issues in mind. In this example, the traps of interest formed about 15 Ma. The primary question addressed by the model is, “What is the volume of oil charge to each of the traps during the last 15 m.y.?”

A hypothetical example is presented to illustrate the approach described. Although the geology is synthetic, it was constructed with realistic basin modeling issues in mind. In this example, the traps of interest formed about 15 Ma. The primary question addressed by the model is, “What is the volume of oil charge to each of the traps during the last 15 m.y.?”

[[file:H4CH12FG3.JPG|thumb|300px|{{figure number|3}}Cross section through the model along the line AA' shown in [[:file:H4CH12FG2.JPG|Figure 2]].]]

[[File:H4CH12FG4.JPG|thumb|300px|{{figure number|4}}Burial history curve for location X represented by the dot in [[:file:H4CH12FG2.JPG|Figure 2]]. [[Source rock]]s are in the middle of each indicated isopachs.]]

For the purposes of this illustration, the migration analysis has been simplified, and it has been assumed that a present-day map-based drainage analysis is sufficient. A map view of the key surface for the map-based drainage analysis is shown in [[:file:H4CH12FG2.JPG|Figure 2]], and a cross section through the model is shown in [[:file:H4CH12FG3.JPG|Figure 3]]. A burial history curve at location X in [[:file:H4CH12FG2.JPG|Figure 2]] is shown in [[:file:H4CH12FG4.JPG|Figure 4]]. Also shown in [[:file:H4CH12FG4.JPG|Figure 4]] are three potential hydrocarbon source rocks, Upper [[Jurassic]], Lower [[Cretaceous]], and lower [[Miocene]]. The sources are modeled as uniformly distributed [[marine]] [[source rock]]s with some terrigenous input.

For the purposes of this illustration, the migration analysis has been simplified, and it has been assumed that a present-day map-based drainage analysis is sufficient. A map view of the key surface for the map-based drainage analysis is shown in [[:file:H4CH12FG2.JPG|Figure 2]], and a cross section through the model is shown in [[:file:H4CH12FG3.JPG|Figure 3]]. A burial history curve at location X in [[:file:H4CH12FG2.JPG|Figure 2]] is shown in [[:file:H4CH12FG4.JPG|Figure 4]]. Also shown in [[:file:H4CH12FG4.JPG|Figure 4]] are three potential hydrocarbon source rocks, Upper [[Jurassic]], Lower [[Cretaceous]], and lower [[Miocene]]. The sources are modeled as uniformly distributed [[marine]] [[source rock]]s with some terrigenous input.

===Step 1: identify the purpose of the model===

===Step 1: identify the purpose of the model===

As previously stated, the purpose of this model is to estimate the volume of oil charge to individual traps during the last 15 m.y.

As previously stated, the purpose of this model is to estimate the volume of oil charge to individual traps during the last 15 m.y.

===Step 2: develop a base-case scenario===

===Step 2: develop a base-case scenario===

The next step is to develop and calibrate a base-case scenario. Values for the selected parameters used in this example are listed in the "Most Likely" column of Table 2. In this hypothetical model, only one calibration point is present, so a match to the data is relatively straightforward, but is also nonunique (Figure 5). The uncertainty around the single temperature measurement (±15°C) is indicated by the error bars.

The next step is to develop and calibrate a base-case scenario. Values for the selected parameters used in this example are listed in the "Most Likely" column of Table 2. In this hypothetical model, only one calibration point is present, so a match to the data is relatively straightforward, but is also nonunique ([[:file:H4CH12FG5.JPG|Figure 5]]). The uncertainty around the single temperature measurement (±15°C) is indicated by the error bars.

 

 

==References==

==References==