Application research of data mining on reservoir characterization

Most Chinese oil-gas fields are almost approaching production tail, and an increasing number of non-traditional oil-gas reservoirs are encountered during the process of exploratory development, which leads to a urgent requirement for advanced methods in conventional methods such as cross plot and multiple linear regression, which can not precisely describe complex oil-gas reservoirs. Thus, the main purpose of this paper is to come up with method of Decision Tree as final model for identification of reservoir fluid based on the comparison of advantage and disadvantage of four methods, including Decision Tree, Support Vector Machines, Artificial Neural Network and Bayesian Network. Moreover, nonlinear regression is performed by using Support Vector Machines to calculate reservoir parameter, which is testified to be good compared with observed data. In sum, data mining is a prospective applied method in oil geology.