Hydrocarbon column height is a crucial parameter in predicting prospect volumes. A difference of a few meters may significantly alter a prospect's estimated success-case volumes. Such sensitivity renders accurate prediction of column height critically important when evaluating prospects for drilling and acreage-capture decisions. In the absence of direct hydrocarbon indicators (DHIs) or known fill controls, column-height modeling must rely on a synthesis of empirical observations from existing discoveries. An extensive compilation of global column-height data demonstrates how trap geometry, genetic history and geologic setting influence the relative roles exacted by various hydrocarbon exit mechanisms (i.e. synclinal spill, fault juxtaposition, erosional leak, capillary leak, and mechanical seal failure). The results also highlight the interplay among trap closure height, seal capacity, and fluid type, as postulated by Sales (1997). Analysis of column-height data for traps containing both oil and gas enable estimation of the capillary entry pressure controlling fluid-contact elevations and provide a proxy for regional seal capacity. Globally, 40% of structures shorter than 250m fill to synclinal spill point. The data suggests combining a uniform column-height distribution with a filled-to-spill distribution, weighted between zero and 0.4, for modeling prospects between 250 and 800m tall. However, the use of global benchmarks for column-height prediction is discouraged without careful consideration of trap-specific geology. Fill patterns for broad, low relief traps contradict the hypothesis that the probability of encountering a cryptic leak, i.e. an unresolved fault juxtaposition or erosional leak, increasing exponentially in probability from trap crest down structure. Characterization of effective seal area for various top-seal lithologies provides an estimate of cryptic leak distribution. The use of a shallow leak contact model, versus a uniform distribution, is suggested when prospect area is much larger than the effective seal area. These results provide a framework to determine two critical inputs for prospect evaluation: (1) the probability functions most appropriate for modeling column height and (2) the weighting of these functions to best reflect the relative likelihood of various fill-control scenarios. This approach is more objective than other methods, which can fail to accurately capture the range and probability of column-height uncertainty.
AAPG Datapages/Search and Discovery Article #90216 ©2015 AAPG Annual Convention and Exhibition, Denver, CO., May 31 - June 3, 2015