Electrofacies Definition and Zonation of the Lower Cretaceous Barra Velha Formation Carbonate Reservoir in the Pre‐salt Sequence of the Santos Basin, Se Brazil

Abstract

Lower Cretaceous carbonates in the pre‐salt succession in the Santos Basin, eastern Brazil, are highly heterogeneous in terms of their reservoir characteristics as a result of depositional and diagenetic factors. Electrofacies have widely been used for reservoir zonation and, when allied with computer‐based methods such as neural networks, may help with the study of such complex reservoir rocks and with the identification of high‐quality reservoir zones. In this work, an unsupervised artificial neural network known as a self‐organizing map (SOM) was used to carry out a zonation of the pre‐salt carbonates in the Aptian Barra Velha Formation, the main reservoir unit in the Santos Basin. Available data included gramma‐ray, neutron porosity, resistivity deep, sonic, density, photoelectric factor, total porosity and effective porosity profiles from 21 wells together with mineralogical models. Core descriptions and thin section images were used as additional data for the lithological characterization of the electrofacies and consequently for reservoir zonation. A total of four electrofacies were defined from the SOM application, and five reservoir zones were identified.The characterization of the reservoir zones also considered the structural locations of the wells based on the relative depth to top‐ Barra Velha Formation; well locations were classified as structurally high, intermediate or low. Based on the reservoir zone characteristics, the results could be correlated with zonations in previous studies. A general tendency was noted for there to be an increase of finer‐grained sediments in the formation in wells located in structural lows; packstone and mudstone facies were prevalent in these wells and were in general characterized as poor‐quality reservoir rocks. By contrast, the shrubstones and grainstones which were more frequent in structurally high wells comprised higher quality reservoir rocks.The basal reservoir zone showed wide lithological variation compared to the overlying reservoir zones. Grainstone‐dominated facies were identified in the middle of the formation, and the uppermost reservoir zones were characterized by an upward increase in shrubstones and reworked grainstones which in general pointed to better quality reservoirs.

Carbonate reservoir characterization with integrated rock, special well logs, and machine learning methods

“…In the last decade, applications in reservoir characterization are on the rise, with solutions being deployed on several fronts of machine learning (e. g. regression, classification, clustering, anomaly detection). Some selected works in the Brazilian Pre-Salt include automatic facies classification (Bize-Forest et al, 2018;Ferreira et al, 2019;Valentin et al, 2019, Camargo et al, 2022, reservoir property estimation Valentin;Ferreira et al, 2021;Babasafari et al, 2022), synthetic well-log generation , and support to drilling operations (Duarte et al, 2018). Some of these methods are further expanded in the next section.…”

“…Valentin et al (2019) used core and Borehole Image Logs to predict depositional facies with deep residual convolutional networks (Valentin et al, 2019). Camargo et al (2022) segmented the Barra Velha reservoir in different zones using selforganizing maps, by taking as input Nuclear Magnetic Resonance and other conventional wells logs. Moreover, data-driven facies prediction can also be applied as an aid to seismic interpretation.…”