Logging Reservoir Evaluation Based on Spark

Abstract

In the past, most traditional logging reservoir evaluation methods rely on expertise. However, as data size grow rapidly, the efficiency of manual analysis is low. With the big data technology becoming more and more mature, we can use big data platform to evaluate logging reservoir. In this paper, we proposed a Spark based logging reservoir evaluation method. By constructing a 3 nodes IBM BigInsights big data platform, using the decision tree algorithm of Spark, we accomplished the evaluation of logging reservoir. We tested our proposed algorithm on a dataset in an oil-field in Northwest China, the proposed algorithm can accomplish the evaluation of logging reservoir. This approach doesn't rely much on expertise and can achieve a better efficiency than traditional evaluation. The proposed method can provide a reference to using big data platform to evaluate the logging reservoir.