Abstract
Petrophysical rock typing is a very important problem in flow unit interpretation and reservoir characterization. Unlike the sandstone, the presence of numerous nanopores in tight sandstone can cause strong gas and liquid non-linear flow. And this makes the traditional rock typing indexes derived from Darcy'law unsuitable for tight sandstone. In this paper, new rock typing indexes, including the Darcy index (Fi), the gas non-Darcy index (Kc) and the liquid non-Darcy index (Sr), have been proposed to describe the non-linear flow characteristics in tight sandstone. In addition, the limit pore ranges for gas and liquid non-Darcy flow have been determined based on these indexes. Then the weighted fuzzy kNN algorithm, which can consider the weight differences between different rock typing indexes, is combined with three indexes to improve the accuracy of rock typing. In order to test the rock typing indexes and the weighted fuzzy kNN algorithm, the tight sandstone dataset in Upper Triassic Yanchang Formation, Ordos Basin, NW China has been constructed with RES (representative element surface) random pore network and experiment data. The results show that the new rock typing indexes and the weighted fuzzy kNN algorithm have better performance in typing tight sandstone than the traditional methods. Moreover, 30 mercury injection capillary pressure (MICP) curves measured on highly inhomogeneous tight sandstone samples from the research area have also been used to validate our method. All the results have proved that the proposed new rock typing indexes and weighted fuzzy kNN algorithm can type the tight sandstone very well, and they play a significant role in permeability prediction, reservoir modeling and simulation.
NSTL
Elsevier