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石油裂缝定位系统(OFPS)的研究
尹学诚
Subtype工学硕士
Thesis Advisor陈振民
1997-06-01
Degree Grantor中国科学院自动化研究所
Place of Conferral中国科学院自动化研究所
Degree Discipline模式识别与智能系统
KeywordOfps 主从式 无线控制数据采集 P波 S波 Lms自适应滤波模式识别 Bp神经网络 Ofps Wireless Controlled Data Acquisition p Wave s Wave Adaptive Filter Pattern Recognition Neural Network
Abstract地球物理信号的处理与解释是一件很复杂的事件。通常勘探者对地球物理信 息的解释不仅仅依靠包含在地球物理数据中的信息,还要依赖于一‘些相关的地理 信息知识。专家知识起很大的作用。尽管在目前的条件下建立一自动的地球物理 数据解释系统是件很困难的事情,但作者基于-简化的相对比较简单的模型,运 用模式识别、专家系统和神经网络等技术来研究石油裂缝地理信息,并为此开发 了-暂时使用的0FPS(石油裂缝定位系统),它包含从前期的数据采集到后续的 数据处理以及石油裂缝的机器解释。 这个系统包含四个部分: (1)使用主从式无线控制的数据采集硬设备系统; (2)对采集数据的自适应滤波处理; (3)P波s波的机器识别与解释; (4)BP神经网络的P波s波识别应用研究。 OFPS的部分已在河南中原油田使用达半年。从实验结果我们可以得出结 论:0FPS的硬件系统及其原理都经受了实践检验是可行的。其软件系统中应用 的模式识别与神经网络等技术也为减轻勘探者的劳动强度与提高解释质量起到 了一定的作用。
Other AbstractThe task of geophysical signal processing and interpretation is very complicated in its nature. Usually, the explorationists explain geophysical data not only based on information contained in the geophysical data, but also on other related geological knowledge. Knowledge and expertise play very important roles. Altough it is extremly difficult to extablish an automatic geophysical data intepretation system, much effort has been made to introduce the technology of pattern recognition, neural network and expert system to geophsical signal processing and interpretation in the oil-well fissure position for the relatively simple model we use. In order to expose the possibility and effectiveness of exploiting pattern recognition techniques in the field of exploration ofoil field and the oil-well fisuure geophysical information, a tentative geophysical signal interpretation OFPS (Oil-well Fissure Position System) has been developed by author, which contains from the beginning of oil-well geophysical data acqusition hardware to the late software to deal with the data and gives the interpretation This system consists of four parts, for the following purposes: (1) Hardware of oil-well fissure geophysical data acquisition using wireless communication ; (2) LMS adaptive filter apply to the OFPS data ; (3) Pattern recognition of the P wave and S wave and interpretation; (4) Research on the BP neural netwok application in the Pattern recognition of the P wave and S wave. Parts of the OFPS has been put in use in the Zhongyuan Oil field, puyang, Henan province for about half year. From the experimental results we may conclude that the pattern recognition technique and neural network will provide explorationists with some effective means in reducing their labor intensities and improving the quality of interpretation.
shelfnumXWLW443
Other Identifier443
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/7205
Collection毕业生_硕士学位论文
Recommended Citation
GB/T 7714
尹学诚. 石油裂缝定位系统(OFPS)的研究[D]. 中国科学院自动化研究所. 中国科学院自动化研究所,1997.
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