Comparison of box counting and correlation dimension methods in well logging data analysis associate with the texture of volcanic rocks release_ebhkde6llbfmvap46su6vz4qqm

Abstract

We have developed a fractal analysis method to estimate the dimension of well logging curves in Liaohe oil field, China. The box counting and correlation dimension are methods that can be applied to predict the texture of volcanic rocks with calculation the fractal dimension of well logging curves. The well logging curves are composed of gamma ray (GR), compensated neutron logs (CNL), acoustic (AC), density (DEN), Resistivity lateral log deep (<i>R</i><sub>LLD</sub>), every curve contains a total of 6000 logging data. The dimension of well logging curves are calculated using box counting and correlation algorithms respectively. It is shown that two types of dimension of CNL, DEN and AC have the same average value. The box counting dimension of volcanic lava is lower than the pyroclastic rock obviously. The majority of correlation dimension of volcanic lava is lower than the pyroclastic rock, but a small amount of correlation dimension of volcanic lava is equal to the pyroclastic rock. It is demonstrated that the box counting dimension is more suitable for predicting the texture of volcanic rocks. Applications to logging data, A well show the relationship between the fractal dimension and the texture of volcanic rock in certain depth.
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