Abstract
This study investigates whether pixel-based geostatistical modelling methods can be used to generate high net:gross ratio models with low connectivity of the net facies, a common combination in many natural geological systems. Connectivity as a function of net:gross is systematically measured in stationary, representative, horizontally isotropic three-dimensional models generated using three different pixel-based geostatistical methods: sequential indicator simulation, truncated Gaussian simulation and multiple-point statistics modelling. All methods are found to have percolation thresholds similar to, or substantially lower than, that of a random object-based model in which the net facies becomes macroscopically connected at a critical net:gross ratio of 0.27. A geometrical transformation previously defined for object-based models known as the compression method has been adapted to deal also with pixel-based models. Application of the method, calibrated using the newly established percolation thresholds, allows construction of geologically realistic facies models using a range of pixel-based methods. The resultant models contain quantifiable levels of connectivity that are defined independently of the model net:gross ratio.
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This publication has emanated from research supported in part by a research grant from Science Foundation Ireland (SFI) under Grant Number 13/RC/2092 and is co-funded under the European Regional Development Fund and by PIPCO RSG and its member companies. Schlumberger are thanked for their provision of an academic Petrel license.
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Walsh, D.A., Manzocchi, T. Connectivity in Pixel-Based Facies Models. Math Geosci 53, 415–435 (2021). https://doi.org/10.1007/s11004-021-09931-3
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DOI: https://doi.org/10.1007/s11004-021-09931-3