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Session:

Petroleum 5

Abstract No.:

O-077

Title:

Linking geostatistics with basin and petroleum system modeling: Assessment of spatial uncertainties

Author(s):

B. Jia, Stanford University (US)
T. Mukerji, Stanford University (US)
A. Hosford Scheirer, Stanford University (US)

Abstract:

Basin and Petroleum System Modeling process covers a large spatial and temporal interval. Many of the input parameters are highly uncertain. While probabilistic approaches based on Monte Carlo simulations have been used to address parameter uncertainty, the impact of spatial uncertainty on basin modeling remains unexplored. Facies is one of the key modeling inputs since the rock properties are wrapped into facies definition. Geostatistical techniques developed for facies modeling in reservoir characterization can be applied in basin modeling. In particular Multi-point Geostatistical Method had been proven effective in facies modeling given sound training images. In this work using a synthetic 3-D example we first show the traditional uncertainty analysis in basin modeling. Then the impacts of different facies distributions are studied and the corresponding uncertainty in oil accumulations and oil distribution are assessed. We show that spatial uncertainty of facies distributions is an important factor in the overall uncertainty in the oil accumulations, and different geological interpretation gives quite different results. In principle one could get the output distributions of hydrocarbon accumulations by running basin models with multiple facies realizations. However, 3-D basin modeling can be quite time consuming. To alleviate this, we use distance and kernel methods to select a few models for simulation. Using multi-dimensional scaling (MDS), with an appropriate distance metric, multiple models are mapped to a low-dimensional space. Kernel clustering method is then used in the low-dimensional space to select a small subset of realizations that are representative for the uncertainty space. Results show that the variation of oil accumulation from facies uncertainties is greater than traditional parameter such as total organic carbon (TOC) and hydrogen index (HI). Spatial uncertainty should be considered as important if not more important than typical basin modeling inputs. Geostatistics can help basin modelers in assessing impacts of spatial uncertainty.