摘要
沉积相研究是油气勘探开发中一项十分重要的任务。在桩241块初次利用神经网络模式识别法进行测井微相识别,将识别后的结果与岩心微相划分结果相对比,测井相的识别完全满足研究的需要,为密井网条件下沉积微相划分提供了一种新的思路和方法。采用神经网络判识沉积微相技术,可以提高沉积微相的分析和解释精度。
Study on sedimentary facies is a main subject of the oil-gas exploration.Neural net discrimination of micro-sedimentary facies is first applied to block Z241.The neural net-discriminated results can be correlated with the well-logged micro-sedimentary facies and meet completely the need of the study thus provides a new thought and a technique for micro-sedimentary facies division under close exploration well net condition.The technique is playing an important role in improving efficiency and accuracy of analysis and interpretation of the micro-sedimentary facies.
出处
《地质找矿论丛》
CAS
CSCD
2009年第4期317-321,共5页
Contributions to Geology and Mineral Resources Research
关键词
神经网络
沉积微相
neural net
micro-sedimentary facies
