摘要
克拉玛依油田一西区测井资料分为标准测井和综合测井两大类。大多数井均为标准测井,其资料品质差,所建立的孔、渗模型解释精度不高。针对此问题,提出对于没有综合测井曲线的井,采用神经网络的方法用标准测井曲线反演出其综合测井曲线,据以分岩性建立孔隙度、渗透率模型。用这种方法建立的模型要比直接用标准测井曲线反演的孔隙度、渗透率模型精度高,而且可以满足测井解释的要求。在此基础上,对一西区克拉玛依下亚组油藏进行了储集层质量评价。
The type logs from west District No.1 in Karamay oilfield are classified as the normal logs and composite logs.The normal logs from most wells are poor in quality,so the porosity and permeability models developed by them are lower in interpretation accuracy.For this reason,this paper proposes that for wells without the composite logs,the normal logs can be inverted to composite logs by means of neural network method,by which the porosity and permeability models are developed on litholgy,thus satisfying the requirement of logging interpretation.On the basis of these,the reservoir quality evaluation the Lower Karamay formation in west District No.1 in Karamay oilfield is conducted.
出处
《新疆石油地质》
CAS
CSCD
北大核心
2011年第2期176-178,共3页
Xinjiang Petroleum Geology
