--> Evolving Genetic Concepts and Their Influence on Hydrocarbon Systems Predictions, an Example from the SubAndean Foldbelt of Argentina

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Evolving Genetic Concepts and Their Influence on Hydrocarbon Systems Predictions, an Example from the SubAndean Foldbelt of Argentina

Abstract

Convergent orogenic systems pose challenges for the prospector seeking to predict oil and gas occurrences, as these regions are often data-poor. Explorationists, therefore, must often rely on conceptual models to choose the most favorable exploration areas. This talk examines how different conceptual models of hinterland evolution can influence predictions of hydrocarbon systems in an adjacent foreland. A 1D method was developed for assessing incremental hydrocarbon yield during progressive foldbelt deformation and source rock burial/maturation, and employed to evaluate how hydrocarbon yield was affected by two different scenarios for the timing of uplift an adjacent mountain belt. The study uses the example of the Puna plateau and adjacent Metán foreland region of northern Argentina, although the concepts are globally applicable. In the first scenario, plateau growth and burial of the Metán region begins in the early Miocene and progresses to the present day. In the second scenario, plateau growth and basin formation occur predominantly in the Eocene, with minor deformation from Middle Miocene to Present. The later load timing decreases the relative volume of liquid hydrocarbons available to fill structural traps. The differences in charge volume and timing between the two scenarios are enhanced in this region as a result of thinned crust and relatively high heat flow that linger from a Cretaceous rifting event. The results of the study provide an example of how boundary conditions obtained from studies of an orogenic hinterland can be used to risk a potential play within a basin where data is incomplete or inconclusive. They also yield general insights on the use of regional genetic concepts to predict thermal history and source rock maturation/yield in data-poor areas.