A workflow for multimineralogic carbonate rock physics modelling in a Bayesian framework: Brazilian pre‐salt reservoir case study

Abstract

We develop a workflow to estimate elastic attributes (Vp and Vs) of Pre‐Salt carbonate reservoirs using the Xu and Payne rock physics model in a depth‐variant multimineralogic fashion and apply it to one calibration and four extrapolation wells in a field in the Brazilian Santos Basin. Some of the parameters were stochastically simulated in a Bayesian framework to handle the model non‐uniqueness. Nuclear magnetic resonance porosity and mineralogic logs and x‐ray powder diffraction data from the studied wells and literature reference values were used for elastic solid media and dual‐porosity network modelling, bringing geological reasoning to the proposed workflow. Using rock physics templates, we improved our understanding of the reservoir petroelastic trends and devised alternative model parameterizations. Since the model was parameterized in a multimineralogic fashion with depth‐variant mineralogic information (e.g. volumes of carbonate, quartz and clay) as input, we improved elastic attribute estimations within the reservoir, increasing the model predictive power, compared to the common practice of allowing only porosity to vary with depth and representing the matrix properties by a depth‐invariant homogeneous or mixed mineral. We also investigated the workflow robustness and non‐uniqueness by studying its dependence on the choice of calibration well.

Depth-variant pore type modeling in a pre-salt carbonate field offshore Brazil

“…Also, as porosity increases, the impact of mineralogy matrix in the rock elastic behavior decays in importance in relation to pore aspect ratio and volume, as expected. This behavior was also observed by Dias et al (2021).…”

“…Mirkamali et al (2020) provided a seismic petrophysics workflow to improve well tie with poor or missing seismic data from the modeling pore types and their volumes using P-and S-wave velocities. Finally, Dias et al (2021) coupled an inclusion rockphysics model with Bayesian framework parameterization in a depth-variant multimineral fashion to estimate the elastic attributes Vp and Vs. One of the main conclusions is that the Bayesian parametrization helped provide prior knowledge through probability density functions (PDFs) of the Barra Velha Formation (BVF) in the Santos Basin.…”

Erratum

“…In Dias et al . (2021), the following errors were published on pages 672, 673, 674, 675 and 676.…”

Reactive Flow in Carbonate Rocks From Lacustrine Environments: The Effects of Pressure and Fluid Salinity

“…Those rocks are characterized by being highly heterogeneous and presenting a complex pore network. (Lima et al, 2020;Dias et al, 2021;Boyd et al, 2015).…”