摘要
泥页岩油气产能与异常高压存在一定的正比关系,通常异常压力越大油气产量越高,因此地层孔隙压力预测的准确性对于"甜点"区优选有重要意义。以松辽盆地北部某区块青山口组为例,首先以单井测井资料为基础,用实测压力数据作为质控条件,优选出适合该区块目的层孔隙压力的计算模型及相应参数,然后基于叠前地质统计学反演得到的高分辨率地震速度体,利用优选出的压力模型进行井震结合孔隙压力体和压力系数体预测。研究结果表明,Bowers法适用于松辽盆地青山口组泥页岩储层孔隙压力预测,且预测结果精度高。研究成果可为泥页岩油有利钻探目标优选提供技术支撑。
There is a certain relationship between the hydrocarbon productivity the mud shale reservoir, in general, the higher the abnormal pressure is, the and the abnormal high pressure for greater the hydrocarbon production will be, therefore, the accuracy of the pore pressure prediction is of great significance for the optimization of "the sweet point" area. Taking Qingshankou Formation of one block in North Songliao Basin as an example, on the basis of the individual well log data, regarding the measured pressure data as the quality control condition, the calculating model and its corresponding parameters of the pore pressure were optimized for the target layer in the block, and then with the help of the high-resolution seismic velocity body gained by the pre-stack geo-statistics inversion, and moreover by means of the optimized pressure model, the pore pressure body and pressure coefficient body of the well-seismic integration were predicted. The study results show that Bowers Method is suitable for the pore pressure prediction of the mud-shale reservoir in Qingshankou Formation of Songliao Basin and furthermore the predicted precision is pretty higher, so the results can provide the technical support for the optimization of the favorable drilling target in the mud-shale oil reservoirs.
作者
李奎周
陈树民
赵海波
王团
霍秋立
LI Kuizhou;CHEN Shumin;ZHAO Haibo;WANG Tuan;HUO Qiuli(College of Geosciences,Northeast Petroleum University,Daqing 163318,China;Exploration and Development Research Institute of Daqing Oilfield Co Ltd.,Daqing 163712,China)
出处
《大庆石油地质与开发》
CAS
CSCD
北大核心
2018年第6期7-12,共6页
Petroleum Geology & Oilfield Development in Daqing
基金
中国石油天然气股份有限公司重大科技专项"大庆油气持续有效发展关键技术研究与应用"(2016E-0211)
关键词
孔隙压力预测
泥页岩
地震速度
叠前地质统计学反演
青山口组
松辽盆地
pore pressure prediction
mud shale
seismic velocity
pre-stack geo-statistics inversion
Qingshankou Formation
Songliao Basin