Thin Beds and Cutoffs: Improved Assessment and Modeling of Net Porous Volume

Abstract

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 166045, ’Thin Beds and Cutoffs: A Probabilistic Approach for an Improved Assessment and Modeling of the Net Porous Volume,’ by J. Clavel and P. Ruelland, Total, prepared for the 2013 SPE Reservoir Characterisation and Simulation Conference and Exhibition, Abu Dhabi, 16-18 September. The paper has not been peer reviewed. Applying a cutoff consists of defining a threshold value on one or more logs to separate the reservoir intervals in which hydrocarbons are mobile from the gross rock thickness. In a thin-bed context, this deterministic approach is insufficient because of the resolution of the logs and a limited number of data. The probabilistic approach proposed in this paper considers that the relationship between the cutoff value on the selected log and hydrocarbon mobility in the sandy laminae is a statistical function. Introduction Cutoffs in petrophysics are frequently applied in the oil and gas industry. Previous work has shown the benefits that result from their use, in particular the decrease in the biases related to the upscaling of petrophysical properties, as well as the usual disadvantages of using cutoffs (i.e., the possible decrease of volume-in-place calculations and connectivity). The overall increase in computer power and cellsize reduction in cellular models, as well as the improvement in upscaling methodologies, render the use of cutoffs less crucial for massive sandstone facies. The objective of this paper is to propose a probabilistic approach to cutoffs in order to improve the coherency and quality of 3D cellular models. Thin Beds and Cutoffs Thin beds are a common occurrence in turbiditic, deltaic, and tidal series. They consist of alternating sand and clay layers that have a thickness of less than 50 cm. Outside these layer thickness, sand and clay are well-distinguished on classic logs and are not considered to be thin beds. Thin-bed facies are heterogeneous, and sampling by wells is insufficient to obtain a representative set of calibration and data; thin beds are undersampled. At the scale of the core, the variability of sand proportion and of lamina thickness in thin beds is clearly observed. The usual work flow to carry information from core to log and then to gridcell size includes two scale jumps. The synthesis of sedimentological core characterization and image logs into a high-resolution petrophysical log is used to calibrate the quantitative interpretation of wireline/logging-while-drilling logs. Petrophysical data that result from this interpretation then need to be upscaled per facies (or rock type) to the cell size of the 3D reservoir model. Applying a cutoff consists of defining a threshold value on permeability or other logs that will define reservoir intervals in which hydrocarbons are mobile. Byproducts of a cutoff include net height and net-to-gross (NTG) ratio, the ratio of net height to total height. The examples in this paper are all extracted from turbidite environments with a shallow burial where cutoffs on the log of volume of clay (VCL) are the best indicator. Cutoffs are applied at log scale on one or more petrophysical parameters in order to take a phenomenon into account: fluid mobility at the scale of the lamination. The relationship between VCL and fluid mobility is statistical. The cutoff is then consolidated at the scale of one or more fields, taking into account fluid types and production mechanism; this operation also relies on statistics. Well sampling in the laminated facies is often insufficient to capture heterogeneity at these different scales. Net height, computed through cutoffs, is very sensitive to small variations in parameters such as cutoff value and VCL-log and lithology variations at small scale. This explains the limitations of a deterministic cutoff in thin beds. When considering a cellular model and the way the log information is upscaled to the cell size, the limitations of a deterministic cutoff are even greater.