节点文献
提高地震反演中测井建模精度的方法与应用——自然伽马反演模型建模方法
Method for Improving the Modeling Precision of Seismic Inverstion——Method for Natural Gamma Ray Inversion Modeling
【摘要】 储层反演技术是利用地震和测井信息,在地质理论指导下对储层的空间展布和几何形态进行宏观描述。然而,某些储层反演模型重构方法由于对测井曲线录取时的影响因素、地层埋深对测井曲线的影响、复杂地质条件下不同岩性在测井曲线上响应的差异等问题缺乏深入分析,在一定程度上影响了利用储层反演结果区分地层岩性的能力,同时也制约了储层预测技术的广泛应用。研究以二连断陷盆地为例,在分析自然伽马曲线的各种不同影响因素的基础上,总结出一套自然伽马岩性反演模型的重构方法。认为由于地层受不同沉积时期等因素的影响,造成了自然伽马测井曲线上泥岩基线的差异和砂岩判别标准的不统一,同时由于钙质泥岩等特殊岩性的存在而影响了利用自然伽马测井曲线对砂岩和泥岩的识别,对这些影响因素做校正处理,可提高储层反演结果的岩性识别能力。
【Abstract】 Reservoir prediction was a technique which used seismic inversion and log data for macroscopic description of the reservoir distribution and geometric shapes under the guidance of geological theories.However,for some of the inversion methods,less analysis was conducted on the influential factors from the acquisition logging curves,the influence of buried depth on logging curves,the response difference of complex geologic condition on different lithologies,by which the ability for lithological division by using the inversion result were influenced at same extents and the application of reservoir predicting technique was constrained.By using Erlian Rift Basin for example,the model of natural gamma ray inversion was used based on influential factor analysis,a set of models were summarized for reconstructing the lithological inversion model.Study shows that because the reservoirs are influenced by different sedimentary stages,differences are induced on the baseline of natural gamma ray logging non-integraty of sandstone identification criterion,also impact is caused on the recognition of sandstone and mudstone by using natural gamma ray logging curves because of the speciality of calcite mudstone.The lithological recognizing ability on reservoir inversion result can be improved by correcting the influential factor.
【Key words】 reservoir prediction; natural gamma ray; logging curve; lithological recognition; influential factor; model reconstruction; reservoir inversion;
- 【文献出处】 石油天然气学报 ,Journal of Oil and Gas Technology , 编辑部邮箱 ,2008年05期
- 【分类号】P631.84
- 【被引频次】6
- 【下载频次】303