CSimMDMV: A parallel program for stochastic characterization of multi-dimensional, multi-variant, and multi-scale distribution of heterogeneous reservoir rock properties from well log data

  • Authors:

  • Jun-Wei Huang;Gilles Bellefleur;Bernd Milkereit

  • Affiliations:

  • University of Toronto, 60 St. George Street, Toronto, ON, Canada, M5S1A7;Geological Survey of Canada, 615 Booth Street, Ottawa, ON, Canada, K1A 0E9;University of Toronto, 60 St. George Street, Toronto, ON, Canada, M5S1A7

  • Venue:
  • Computers & Geosciences
  • Year:
  • 2011

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Abstract

We present CSimMDMV, a software package to simulate two- and three-dimensional, multi-variant heterogeneous reservoir models from well logs at different characteristic scales. Based on multi-variant conditional stochastic simulation, this software is able to parameterize multi-dimensional heterogeneities and to construct heterogeneous reservoir models with multiple rock properties. The models match the well logs at borehole locations, simulate heterogeneities at the level of detail provided by well logging data elsewhere in the model space, and simultaneously honor the correlations present in various rock properties. It provides a versatile environment in which a variety of geophysical experiments can be performed. This includes the estimation of petrophysical properties and the study of geophysical response to the heterogeneities. This paper describes the theoretical basis of the approach and provides the details of the parallel implementation on a Linux cluster. A case study on the assessment of natural gas hydrate amount in Northwest Territories, Canada is provided. We show that the combination of rock physics theory with multiple realizations of three-dimensional and three-variant (3D-3V) gas hydrate reservoir petrophysical models enable us to estimate the average amount of gas hydrate and associated uncertainties using Monte Carlo method.