CAJ | 학술논문

通过已知测井资料对油藏储量进行预测，是目前石油行业一个重要的研究课题。文章介绍了一种基于贝叶斯正规化算法的BP神经网络，并把网络应用到油藏参数拟合过程中的具体方法，该方法对提高石油生产效率、降低成本具有很大的作用。
통과이지측정자료대유장저량진행예측，시목전석유행업일개중요적연구과제。문장개소료일충기우패협사정규화산법적BP신경망락，병파망락응용도유장삼수의합과정중적구체방법，해방법대제고석유생산효솔、강저성본구유흔대적작용。
The known logging data to predict reservoir reserves is an important research topic in the oil industry. In this paper, the algorithm based on Bayesian regularization BP neural network is introduced and the applications to specific methods in the reservoir parameter fitting process is also described. This method plays a significant role in improving the oil production efficiency and reducing the costs.