Application Of Comprehensive Evaluation Method In Oil Well Classification

Abstract

China’s oil resources are very rich, but the effect of oil exploitation is not good. Precise prediction of oil production plays an extremely important role in formulating a reasonable oil planning plan and determining the direction of investment. In order to improve the accuracy of oil well exploitation, it is necessary to establish a scientific oil production forecasting system. First, pre-treatment research on the data of Baikouquan Oilfield to ensure the quality of oilfield data. Secondly, the main controlling factors affecting the production of oil wells are analyzed, and the single evaluation is carried out by the coefficient of variation method, the entropy method and the mean square error method. Then, the pre-examination test of the consistency test is performed on the single evaluation result, and the combination of the evaluation methods is selected. The combined evaluation method is the average method, and the fuzzy Borda method. It is again tested whether the combined evaluation result has passed the consistency test. After the consistency test, the sum of the squares of the errors of the three combined evaluations is calculated, and the optimal one is optimized. The combined evaluation method was used for the second combination evaluation, and the results of all the evaluation methods were compared to observe whether the combined evaluation results were effective, and 8 main control factors were analyzed and screened. Finally, the main control factor data analyzed by comprehensive evaluation is used for discriminant analysis, and the fitting effect is compared. It is found that the fitting results are basically consistent with the data of the oilfield site, indicating that the results of the main control factors analyzed by the comprehensive evaluation are better. The prediction accuracy meets the engineering requirements and is of great significance for the prediction of on-site oilfield production.