基于NNFR神经模糊推理的储层参数识别与评价  

Fuzzy Inference Reservoir Parameter Identification and Evaluation Based on NNFR

作　　者：张方舟[1] 张媛媛[1] 金宗泽 邱露露[1] 宋经纬[1] 

机构地区：[1]东北石油大学计算机与信息技术学院,黑龙江大庆163318

出　　处：《计算机技术与发展》2015年第6期211-215,共5页Computer Technology and Development

基　　金：黑龙江省科技攻关项目(F2004-01);黑龙江省教育重大科研项目(10051z0001);黑龙江省教育科学技术研究项目(11551016)

摘　　要：随着勘探技术的不断发展,研究的不断深入,对油气层预测的精度越来越高。为了提高参数识别的精度,同时,为了应用地化数据实现储层的参数识别与评价,文中通过引入数据归一化算法来克服各方面因素对预测结果的干扰,并借助基于NNFR的神经模糊推理来帮助实现参数的识别与评价。通过建立参数预测的分析步骤方法最终完成对储层参数的识别。并为验证理论模型的正确性,通过对7口井12个试油井的井段数据井进行测试与验证,证实了该方法的可行性。With the continuous development of exploration technology and research is studied deeply,the hydrocarbon reservoir prediction accuracy is higher and higher. In order to improve the precision of parameter identification,at the same time,apply geochemical data to achieve the parameters identification and evaluation of reservoir,by the introduction of data normalization algorithm,overcome the various interferences on the prediction results,and by means of NNFR to identify and evaluate the parameters. By establishing the procedure of analyzing method,it recognizes the reservoir parameters. In order to verify the correctness of the theory and model,it tests the data units of 12 test wells in 7 wells,which proves the feasibility of the method.

关 键 词：数据归一化 神经网络 模糊推理 储层预测 

分 类 号：TP389.1[自动化与计算机技术—计算机系统结构]