Study on relevance between crude oil output and meteorological factors based on NCM-Apriori

Crude oil output is directly or indirectly associated with a number of factors such as reserves, geological structure, number of active wells, and production plan. Analysis of relationship between crude oil output and influencing factors plays a significant role in predicting crude oil output and planning reasonable productions. A method using NCM-Apriori algorithm to calculate the relevance between crude oil output and meteorological factors is proposed in this paper. With this method, data pre-processing based on K-Means algorithm is first conducted on daily production data of a certain oil production plant. Next, different meteorological factors are graded to achieve transaction datasets. An association analysis with NCM-Apriori algorithm is then performed on these datasets. Finally, the strong association rules related to crude oil output are selected based on settings for minimum support and minimum confidence. This method has been proven to be more simple and efficient than traditional Apriori algorithms in computation, thus providing a new reference for predicting crude oil output and developing reasonable crude oil production plans.