--> 4-D Analogue Modeling of Transpressional Structures Growing in a Rheologically Heterogeneous Medium: Methodology, Main Results and Reference Models

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4-D Analogue Modeling of Transpressional Structures Growing in a Rheologically Heterogeneous Medium: Methodology, Main Results and Reference Models

 

Marchal, Denis1, Jean-Marc Daniel2, Misael Alvear1 (1) Petrobras Energia Venezuela, Caracas, Venezuela (2) Institut Français du Pétrole, Rueil Malmaison, France

 

The study of the evolution of complex geological structures, such as the transpressive one of La Concepción field in Maracaibo basin, is a challenging task due the time and space scale involved in geological processes. One powerful method used to handle this difficulty is scaled analogue modeling. At IFP this modeling methodology is completed by the use of non-destructive techniques of acquisition with CT-scanner (4D imaging), allowing the geol­ogist to follow, in space and time, the deformation of the structures growing in the experi­ments.

During this project, twenty-two experiments have been performed to describe the tec­tonic evolution of a rheologically contrasted sedimentary cover lying over a stepover formed by two overlapping basement faults, reactivated by transpressional tectonics. Thirty-three 3D blocks of selected experiments have been interpreted (horizons and faults). These 3D models illustrate the main geometrical characteristics of the different fault networks gener­ated and their evolution through time (4D approach). The analysis of these experiments has highlighted the main tectonic phenomena occurring in this tectonic setting and the principal parameters that control them.

The study shows that the La Concepción field structure best matches with a tectonic model involving transpression with a moderate amount of shortening, including a partial decoupling between the lower and the upper part of the structure. Moreover, all the models might be used as references (database) for the geologist interpreting seismic data in prob­lematic zones (structural complexity, scarce or noisy data) and to constantly test the struc­tural model elaborated with the field data.