“IMAGEAMENTO GEOELÉTRICO DA BACIA DO PARNAÍBA POR MEIO DA INVERSÃO MAGNETOTELÚRICA DETERMINÍSTICA E BAYESIANA”

Abstract

The objective of this thesis is to improve the understanding of the internal structure and tectonic framework of the Parnaíba Basin by applying the magnetotelluric (MT) method, within the framework of the Parnaíba Basin Analysis Project (PBAP). The Parnaíba Basin is located in northeastern Brazil, where a thick Phanerozoic sedimentary sequence covers most of the basin, and the presence of magmatic intrusions represents a key element in the geodynamic evolution of the basin.

The MT dataset used in this research consists of 218 broadband magnetotelluric (BBMT) stations and 37 long-period magnetotelluric (LMT) stations, distributed along a profile crossing the basin in an E–W direction. The data were analyzed and processed using robust techniques, ensuring the quality and reliability of the resulting magnetotelluric responses. Subsequently, the data were modeled and inverted using both deterministic and probabilistic inversion methodologies. In this context, this thesis is organized into two main parts, each focusing on the characterization of the deep structure of the Parnaíba Basin at different scales of analysis.

The first part consists of obtaining crustal-scale resistivity models through 3D deterministic inversion strategies. The inversion results reveal the presence of three contiguous lithospheric blocks that constitute the Parnaíba Basin. From west to east, these correspond to the Amazonian Craton, the Parnaíba Block, and the Borborema Province, separated by lithospheric-scale resistive discontinuities. Within each block, the models display distinct geoelectrical characteristics. The Amazonian Craton exhibits a conductive domain, possibly associated with the replacement or modification of a previously delaminated lithosphere. The Parnaíba Block, in turn, is composed of two distinct tectonic domains: the highly resistive Grajaú Block and the more conductive Teresina Block. This resistivity contrast is primarily related to magmatic activity, which is more pronounced in the Teresina domain, although it may also be influenced by Cretaceous extensional events associated with the opening of the South Atlantic Ocean. In the Borborema Province, resistive and conductive signatures observed at lower crustal depths provide evidence of collisional processes associated with its Neoproterozoic formation. Overall, these deep resistivity models provide new insights into the crustal amalgamation of the Parnaíba Basin and contribute to a better understanding of the tectonic processes that shaped Western Gondwana.

The second part of this research focuses on the characterization of the shallow structure of the basin (~ 3–4 km depth) through the application of 1D Bayesian trans-dimensional inversion approach based on Markov chain Monte Carlo (MCMC), which allow uncertainties associated with non-1D effects in the data to be properly accounted for. Furthermore, by integrating magnetotelluric data with structural information and well data, and through the application of the Bayesian Estimate Fusion (BEF) approach, it was possible to construct a robust model of basement geometry.

This approach also enabled the identification of the sedimentary cover-basement interface, as well as highly conductive anomalies within the sedimentary sequence, particularly associated with the Poti and Cabeças formations, which are linked to hydrocarbon reservoirs in the Parnaíba Basin. These results provide a more detailed view of the shallow architecture of the basin and its economic potential.

Overall, the results obtained in this thesis significantly contribute to the understanding of both the deep and shallow structure of the Parnaíba Basin, providing key insights into its tectonic evolution as well as valuable information for future hydrocarbon exploration.

Keywords: Parnaíba Basin, Magnetotellurics, 3D inversion, 1D Probabilistic inversion, Markov Chanin Monte Carlo (MCMC), Bayesian Estimate Fusion, West Gondwana Formation, Hydrocarbon Exploration