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油层改造是低渗透复杂断块油气藏开发的主要增产措施，整体油层改造配套工艺的发展和完善，使得经济开发该类油田成为可能，获得较好的经济效益成为一切工艺措施优选的基本原则。神经网络专家系统能针对不同区块油气藏的压裂、酸化现状，总结分析出可能影响油层改造效果的主要因素，根据相似原理以实例作为样本学习模型，自动生成专家知识库。只要输入拟改造油气井的参数，根据专家知识库推理机便能正确实施单井与区块整体油层改造的选井、选层以及施工效果的预测等综合评价工作。 Ｗ Ｎ 油田 Ｗ２６９ 块的实例应用表明，该专家系统能较好地解决区块油层改造的选井选层及其效果评价问题，为实施科学、高效开发油田提供了可靠的评价方法和论证手段。
Reformation of oil layers is the main stimulation measure for the development of low permeability and complex fault block reservoirs. The development and perfection of the integrated process of overall reservoir reconstruction make it possible to develop such oilfields economically, and obtaining good economic benefits has become the basic principle of selecting all process measures. The neural network expert system can analyze the main factors that may influence the effect of oil layer reforming according to the fracturing and acidizing status of different block reservoirs. Based on the similarity principle, an example is used as a sample learning model to automatically generate an expert knowledge base. As long as the parameters of the well to be retrofitted are input, comprehensive evaluation work such as well selection, layer selection and prediction of the construction effect of the single well and the whole block reconstruction of the block can be correctly implemented according to the expert knowledge base reasoning machine. The application of W269 block in WN field shows that the expert system can well solve the well selection and effect evaluation in the reconstruction of block reservoirs and provides a reliable evaluation method and demonstration method for the scientific and efficient development of oilfields.