1887

Abstract

Reservoir heterogeneity in this study is the term describing the spatial distribution of dissimilar rock properties in the earth medium. Reservoirs contain multiple petrophysical properties, each having different degrees of statistical correlations with others. For example, compressional wave velocity is usually positively and strongly correlated with shear wave velocity, whereas the correlation of density to resistivity or porosity to permeability is often not straightforward. In this paper, we describe a new method to model three dimensional heterogeneous rock properties at different correlation lengths. This algorithm is able to honor different degrees of correlation among multiple reservoir petrophysical properties, match borehole logs and simultaneously mimic the statistical features observed in the data. It provides a heterogeneous 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. In addition, our approach can be easily implemented on current parallel architectures to construct large three dimensional reservoir models without loss of accuracy. We apply the modeling approach to the gas hydrate reservoir located in Northwest Territory of Canada, where in situ gas hydrate volume is estimated. We show that by using rock physics theory, statistical parameters estimated from well logs, and the horizontal correlation length estimated from acoustic impedance inversion, the amount of gas hydrate is nearly an order of magnitude lower than earlier estimates which did not include effect of small-scale heterogeneities. Monte Carlo simulations show that the estimated amount and uncertainty of gas hydrate will decrease if the stochastic models are conditioned by well logs. The synthetic cross borehole seismic data illustrate that strong scattering due to the multi-scale heterogeneities can have a severe impact on seismic imaging of the reservoir.

Loading

Article metrics loading...

/content/papers/10.3997/2214-4609.20145025
2010-09-06
2024-03-29
Loading full text...

Full text loading...

http://instance.metastore.ingenta.com/content/papers/10.3997/2214-4609.20145025
Loading
This is a required field
Please enter a valid email address
Approval was a Success
Invalid data
An Error Occurred
Approval was partially successful, following selected items could not be processed due to error