Thomas T. Tran

FLUVSIM: a program for object-based stochastic modeling of fluvial depositional systems

This paper presents a FORTRAN program for hierarchical object-based modeling of complex fluvial facies. Unique features of this program include (1) a simple approach to place channel, levee, and crevasse sands within a matrix of floodplain shales, (2) templates for fast rastering of fluvial facies objects, leading to fast CPU times, and (3) the use of simulated annealing and non-random perturbation rules for conditioning to extensive soft facies-proportion data and local well data. Object-based modeling techniques are widely applicable to modeling fluvial depositional systems. Public domain software for such modeling is rare and inflexible with respect to the variety of conditioning data that can be handled. Commercial software is costly and also of limited flexibility. The fluvsim program overcomes many of these limitations with an accessible research code.

Incorporating Seismic Attribute Maps in 3D Reservoir Models

We introduce a new geostatistical method to incorporate seismic attribute maps into a 3D reservoir model. The method explicitly honors the difference in vertical resolution between seismic and well log data. The method, called Sequential Gaussian Simulation with Block Kriging (SGSBK), treats the seismic map as a soft estimate of the average reservoir property. Using this method, the average of the cell values in any one vertical column of grid cells is constrained by the value of the seismic map over that column. The result is a model that contains vertical variability driven by well logs and the vertical variogram model and spatial variability driven by the seismic map and the areal variogram model.

Production Data Integration in Sand/Shale Reservoirs Using Sequential Self-Calibration and GeoMorphing: A Comparison

The stochastic inversion of spatial distribution of lithofacies from multiphase production data is a difficult problem. This is true even for the simplest case, addressed here, of a sand/shale distribution and under the assumption that reservoir properties are constant within each lithofacies. Two geostatistically based inverse techniques, sequential self-calibration (SSC) and GeoMorphing (GM), are extended for such purposes and then compared with synthetic reference fields. The extension of both techniques is based on the one-to-one relationship existing between lithofacies and Gaussian deviates in truncated Gaussian simulation. Both techniques attempt to modify the field of Gaussian deviates while maintaining the truncation threshold field through an optimization procedure. Maintaining a fixed threshold field, which has been computed previously on the basis of prior lithofacies proportion data, well data, and other static soft data, guarantees preservation of the initial geostatistical structure. Comparisons of the two techniques using 2D and 3D synthetic data show that the SSC is very efficient in producing sand/shale realizations matching production data and reproducing the large-scale patterns displayed in the reference fields, although it has difficulty in reproducing small-scale features. GM is a simpler algorithm than SSC, but it is computationally more intensive and has difficulty in matching complex production data. Better results could be obtained with a combination of the two techniques in which SSC is used to generate realizations identifying large-scale features; then, these realizations could be used as input to GM for a final update to match small-scale details.