IS SEQUENTIAL GAUSSIAN SIMULATION (SGS) A CORRECT METHOD FOR ESTIMATING DISTRIBUTION OF PETROPHYSICAL PROPERTIES IN AN UNCONVENTIONAL RESERVOIR?

Modeling complex systems such as an unconventional gas reservoir can be very challenging task. A legitimate question for scientists and engineers is how accurately the petrophysical properties of a reservoir are modeled. Traditional reservoir modeling techniques such as Sequential Gaussian Simulation (SGS) or Truncated Gaussian Simulation are based on simplified two-point correlation statistics of spatial continuity inferred from the sample data solely. Since unconventional reservoirs have very complex geometric and geologic features, and sample data are typically sparse, identification of two-point statistics is not sufficient to reproduce curvilinear and large-scale connected reservoir structures. For that reason, this traditional approach cannot accurately represent a real distribution of petrophysical properties in the reservoir and produce geologically accurate models. Realistic representation of the reservoir structure requires characterization of spatial continuity at three or more locations at a time. Reproduction of multiple-point patterns of geologic continuity in the reservoir is critical to provide accurate numerical input for flow performance predictions. This paper investigates the drawbacks of Sequential Gaussian Simulation (SGS) used in static modeling of a reservoir. Simulation results are obtained using commercial software PETREL and ECLIPSE. Geologic interpretations of generated result will be used to single out major drawbacks of Sequential Gaussian Simulation (SGS). Using different geological interpretations for a given outcrop and comparing the simulation results, this study helps demonstrate that the SGS may not always assimilate the uncertainties of different geological features into the reservoir model.