期刊文献+

神经网络油气检测技术

NERVENET HYDROCARBON DETECTING TECHNIQUE
下载PDF
导出
摘要 多参数神经网络油气检测技术首先提取四大类26 个地震波特征参数,并定量描述这些参数,然后用神经网络技术对这些参数进行分析,预测油气分布,使油气识别工作定量化、计算机化。本次研究开发了一套神经网络油气识别软件,并利用其对东濮凹陷胡19 块进行油藏精细描述,预测沙三下砂组含油面积0-7 km2 ,石油地质储量70 ×104 吨。 Using nervenetwork technique with the full utilization of petroleum informations taken by seismic waves,hydrocarbon can be detected First, four types of 26 characteristic parameters were extracted from seismic waves and discribed quantitively Then these parameters were analyzed by nervenetwork to recognize and predict petroleum distribution with raising resolutions This method was quantified and realised by computer with the corresponding software As an application, the reserving in Hu 19 zone of Dongpu depression was fine described by this software The predicted oilbearing area of sand groups from 3 to 10 in lower Sha 3 member was 0 7 km 2, and the predicted petroleum geological reserve was 70×10 4 tons [
出处 《地球科学与环境学报》 CAS 1999年第S1期33-36,共4页 Journal of Earth Sciences and Environment
关键词 油气检测 神经网络 特征参数 地质储量 hydrocarbon detector nervenetwork characteristic parameter geological reserve
  • 相关文献

参考文献1

共引文献13

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部