摘要
石油水压裂是在石油开采过程中增加产能的重要措施,但由于种种条件的限制,传统的建模方法无法建立起精确的仿真模型.研究分析了石油水力压裂工艺流程各个部分的不同特点,分别采用不同种类的神经网络建立仿真模型来替代原有的模型,并以RBF网络建模求取综合滤失系数来验证方案的可行性.
Hydraulic fracturing treatment play an important role in improving the productions of petroleum, but traditional modeling methods have many limitations to build a precise simulization model of hydraulic fracturing treat. The author analyses the characteristics of various parts in the hydraulic fracturing process, building simulation models by different types of neural network to replace the old models, and try to certificated the feasibility of this network to get filtration coefficient. program by building the model through RBF neural
出处
《北京工商大学学报（自然科学版）》
CAS
2007年第4期30-33,共4页
Journal of Beijing Technology and Business University:Natural Science Edition
关键词
石油水力压裂
神经网络
建模
仿真
hydraulic fracfuring treatment
artificial neural network
model building
simulization
