The components of geostatistical simulation
- Nebraska Univ., Lincoln, NE (United States)
- Sandia National Labs., Albuquerque, NM (United States)
There are many approaches to geostatistical simulation that can be used to generate realizations of random fields. These approaches differ fundamentally in a number of ways. First, each approach is inherently different and will produce fields with different statistical and geostatistical properties. Second, the approaches differ with respect to the choice of the features of the region that are to be modeled, and how closely the generated realizations reproduce these features. Some fluctuation in the statistical and geostatistical properties of different realizations of the same random field are natural and desirable, but the proper amount of deviation is an open question. Finally the approaches differ in how the conditioning information is incorporated. Depending on the source of randomness and the uncertainty in the given data, direct conditioning of realizations is not always desirable. In this paper, we discuss and illustrate these differences in order to emphasize the importance of these components in geostatistical simulation.
- Research Organization:
- Sandia National Labs., Albuquerque, NM (United States)
- Sponsoring Organization:
- USDOE, Washington, DC (United States)
- DOE Contract Number:
- AC04-94AL85000
- OSTI ID:
- 228463
- Report Number(s):
- SAND--96-0690C; CONF-9605106--1; ON: DE96006983
- Country of Publication:
- United States
- Language:
- English
Similar Records
Reservoir property grids improve with geostatistics
Stochastic simulation for imaging spatial uncertainty: Comparison and evaluation of available algorithms