Integrated Petrophysical Evaluation Applied to the Characterization of Shaly-Sand Reservoirs in the Santonian Gas Field, Santos Basin, Brasil; #50503 (2011)

The integration between new technologies (Natural Gamma-ray Spectrometry log tool, magnetic resonance, etc.), characterization methodologies (probabilistic evaluation, crossplots analysis) and core data (petrophysical and petrological data and sedimentologic description) is very important to identify diagenetic constraints for reservoir quality in shaly-sand reservoirs in order to build a more robust petrophysical model. This work presents a formation evaluation for two main Santonian sequences of an important gas field composed of siliciclastic reservoirs in Santos Basin, eastern Brazilian margin. In these reservoirs the dispersed clay (mainly chlorite) and the sand composition (rich in feldspar) may complicate the petrophysical analyses when using conventional tools to identify the different reservoir zones, to evaluate the permeability and the saturation model. The basic analyses are not enough for the full comprehension of the constraints on these shaly-sand reservoirs. This work proposes an integrated workflow using the core-log approach to improve the characterization of rocks and fluids. This method will allow the understanding of the factors which affect petrophysical properties, as well as identify using log curves the main petrofacies described, applying all available information, the core data and spectral gamma ray tools in order to build a multi-mineral model. The NGS logs and crossplots element ratios have been highly important to the identification and evaluation of these reservoirs. The probabilistic approach has shown significant results for the mineralogical model which was supported by core and plug data. The saturation model has been fitted to the resonance saturation curve calibrated in laboratory (T2 cutoff) and the porosity and permeability models were adjusted with plug data. Finally, the crossplot NGS ratio has proved to be a useful tool assisting in the identification of petrofacies through clusters analysis. The adopted approach has indicates that chlorite was one of the factors that affected the quality of the reservoir (mainly permeability), but did not affect resistivity curves. Moreover, this approach has also proved that those dispersed clays can be identified using the NGS logs and that their volume can be safely calculated with the probabilistic (multi-mineral) model. All these analyses have provided a more predictive model to be applied in a field in the early developmental stage. Copyright © AAPG. Serial rights given by author. For all other rights contact author directly.