利用地震多属性分析技术预测“暗点”型含气储层
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摘要
充分利用能够反映储层及其含气特征的多种地震属性,结合已知钻井的测井、地质资料进行综合分析,以神经网络技术和属性降维处理为技术手段,估算储层参数及预测储层含气性的方法就是地震多属性分析技术.该技术的关键是储层的精细标定、层位准确追踪,以及沿层提取属性所开时窗的合理性.对孝泉-新场地区须家河组二段气藏的应用实例证实,该技术是运用叠后地震数据对“暗点”型气藏进行储层及其含气性预测的又一有效手段.
Taking use of multiple seismic attributes which reflect the characteristics of reservoirs, combining with the present logging and geologic data, by means of neural network and attributation dimension reduction management, seismic multiple-attributes analysis technology can estimate the reservoir paramenters and predict the gas-bearing reservoirs. The key parts of the technology include fine calibration of reservoirs, bed tracing and the rationality of windows opening for attributes picking-up. As an applying example in the prediction of Xiaoquan-Xinchang Gas-bearing reservoirs, Member 2 of Xujiahe Formation, this technology has been proved effective when predicting Dim-spot gas-bearing reservoirs using post-stack seismic data.
引文
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