Ninth International Geostatistics Congress, Oslo, Norway
June 11 – 15, 2012



Abstract No.:



Facies Simulation in Practice: Lithotype Proportion Mapping and Plurigaussian Simulation, a Powerful Combination


J. M. Yarus, Landmark Graphics Corp (US)
R.L. Chambers, Halliburton/Landmark (US)
M. Maucec, Halliburton/Landmark (US)


The geostatistical simulation of facies and petrophysical properties has become a mainstream technology for building stochastic geocellular models. However, modelers are presented with a plethora of challenges when attempting to produce models based on real data, including honoring depositional facies boundary conditions and proportions, honoring data in the presence of numerous or closely spaced wells, capturing post depositional overprinting, and accounting for non-stationarity. Commonly used algorithms tend to satisfy some, but not all, of these issues, falling short on many more.

For example, Sequential Indicator Simulation lacks the ability to control facies boundary conditions, Truncated Gaussian Simulation provides for only simple facies with transitional boundaries, and although Object Simulation can manage most non-overprinted complex facies sets, it is unstable in the presence of high density, closely spaced wells. Non-stationairity compounds the problem, and the introduction of simple trends to ?detrend" the data often provide insufficient solutions.

One powerful combination of methodologies is the use of a multiple lithotype proportion curve matrix (LPM) with Plurigaussian Simulation (PGS). PGS provides numerous advantages over other methods. The LPM consists of hundreds of high resolution trend maps that account for vertical and lateral non-stationarity. Trends for each facies within each layer and every reservoir interval in the model are calculated. The PGS methodology captures most inter- and intra-facies relationships, including post-depositional overprinting, such as diagenesis. As a pixel-based method, PGS works appropriately with both closely spaced and sparse well control. Although it is possible to overcome some of the challenges presented by traditional algorithms through the intervention by experts, the implementation of a LPM with PGS workflow can be presented simply and intuitively, making it available to both experts and non-experts. Results demonstrate successful modeling of complex depositional settings difficult to construct using other methods including mixed carbonate systems with diagenesis and multi-sequenced clastic environments.




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