Abstract
Heat and mass transfer in a natural gas hydrate reservoir is strongly affected by the hydrate pore habit. Some present simplified models used in numerical simulation of a hydrate-bearing sediment are difficult to catch features of the hydrate distribution in sediments precisely. Using an improved multiple-point geostatistics simulation method, this study generates a series of images of porous media that reproduce the hydrate distribution information on a training image. The improved algorithm completely solves the problem that the hydrate blocks the boundary and makes the variogram and visual properties similar to the training image. Some typical phenomena of hydrate formation appear in the results, such as Ostwald ripening and the shift of hydrate pore habit from grain coating toward pore filling. The feasibility of predicting the pore habit of a hydrate with time using this novel method is proven by the verification case. This study offers a new approach to predict the distribution behavior of a hydrate, and this algorithm may be applied widely by scanning training images from different reservoirs.
Published Version
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