Abstract

We have developed a stochastic multifault method for analysis of the impact of stratigraphic uncertainty on cross-fault leakage at sand-sand juxtapositions. This method assumes that all sand-sand juxtapositions leak across the fault. Stratigraphic uncertainty is modeled by stochastic variation of stratigraphic stacking. Structural uncertainty is addressed through variation of the input. Our objectives were to quantitatively predict the impact of uncertainties in stratigraphic and structural input and to simulate the complex system of structural spills and juxtaposition leak points that control hydrocarbon contact levels in traps with stacked reservoir systems and many faults.

Three examples demonstrate how this stochastic multifault method has helped us evaluate uncertainty and understand complex leak fill-and-spill controls. The Ling Gu prospect demonstrates that widespread cross-fault leakage on two crestal faults with throw changes that exceed seal thickness causes only a single hydrocarbon column to accumulate in multiple-stacked reservoirs. This column is controlled by a juxtaposition leak point on a third, deeper fault. We have learned from examples like Ling Gu that the relative size of throw change and seal thickness is a fundamental control on the probability of cross-fault juxtapositions. An example at prospect A demonstrates the sensitivity of hydrocarbon entrapment to small faults in a sand-prone interval with thin seals. The prospect A analysis shows that if seals are thin, faults or channel incisions below seismic resolution can leak hydrocarbons out of stacked reservoirs that are interpreted as unfaulted on seismic data. This introduced significant predrill uncertainty and risk. Guntong field demonstrates that a thin sand in a juxtaposed seal interval can introduce large uncertainty in the prediction of hydrocarbon columns.

These examples and many other analyses using the method demonstrate how small changes in stratigraphic and structural input to a fault-seal analysis can introduce significant uncertainty in the predicted range of hydrocarbon volumes. Such uncertainties need to be directly and systematically accounted for in a fault-seal analysis.

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