Abstract

Structural modeling and systematic analysis are necessary in complex areas even before seismic interpretation. Seismic data in these zones usually show poor-quality images of the geologic elements. Therefore, a detailed analysis of the available information (e.g., seismic, previous wells, and surface geology) is needed to build a comprehensive structural model to constrain the seismic interpretation. Although a restorable structural cross section is not necessarily the unique solution, it is a valid interpretation to begin with, which can be tested against additional information. As an example, a structural profile interpretation in the Agrio fold and thrust belt of the Neuquén Basin, northeastern Argentina, is presented and described as invalid on the basis of several unrestorable geometric components. This led to the reevaluation of the structure to understand its possible exploratory potential. Integration of different data such as regional structural styles inferred fault trajectories from seismic reflection termination patterns, synorogenic deposit geometries in seismic, and surface geology, dipmeter data to identify the presence and location of fault position and vergence of the fold axis, and a kinematic forward model, resulted in a new restorable structural model. The new interpretation proposes a “broken triangle zone” framed by two opposite surface anticlines with the same detachment level, later faulted by a basement fault. The interpreted model suggests at least two phases of deformation (1) a thin-skinned phase with the two opposite anticlines sharing the same detachment level that is responsible for about 80% of the shortening and (2) a thick-skinned phase from an east-verging basement fault, transporting the western anticline and crosscutting the eastern anticline, that is responsible for 20% of the shortening and the synorogenic deposits at the frontal region. This new interpretation defined a new exploration prospect drilled by a wildcat well, which validated the interpretation and model predictions.

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