Clastic-reservoir characterisation of the Malay basin poses numerous challenges resulting from the silty and clayey nature of its reservoirs. To date, different practitioners use shale volume (Vsh) and clay volume (Vcl) in an exchangeable fashion, where the former is rock and the latter is defined as either size or mineral content. Inaccurate quantification of Vcl magnifies the errors inbound in the calculation of porosity and saturation because of the impact of clay density and conductivity in relevant equations.
Different models were developed to evaluate sand, silt, and clay reservoirs, which may be applicable in some local areas and not applicable in others. One of the more common caveats in some of the available models is the mix between the silt volume, Vsilt, and the volume of dispersed clay, Vcl_disp, which has an impact on the effective porosity and water saturation calculations, Sw, especially when evaluating lowresistivity/low-contrast (LRLC) zones using the Thomas-Stieber model.
In the presented study, the same data set was treated with three different deterministic models to solve for sand, silt, and clay volumes. These models include: 1) the sand-silt-clay-water model, also known as the Malay or SSC model; 2) a model that uses maximum porosity to calculate the silt volume; and 3) a technique that uses nuclear magnetic resonance (NMR) clay-bound and capillary-bound volumes from the NMR porosity model.
To select the most accurate and reliable petrophysical approach, the results were compared with X-ray diffraction (XRD) analysis results in the area of the study, and a comparison of grain-size distributions of actual data with grain-size distributions obtained from NMR T2 measurements by a recently developed model was made.
The proposed technique helps in selecting maximum sand and shale porosities as one of the essential parameters in the Thomas-Stieber model for typifying and quantifying the shale and for deciding whether the laminated-dispersed or laminated-structural shale model should be used.
The refined sand, silt, and clay volumes and porosities along with tensor resistivity data were then input into the tensor model for a petrophysical evaluation across anisotropic sand intervals.
The proposed model will help to minimise the uncertainty as a fit-for-purpose approach by improving the accuracy in the calculated mineralogy, porosity, saturation, and consequently, reserve estimations.