摘要
通过对特定元素的含量与储层质量之间的潜在关系进行发掘,筛选出铝和钒作为能够对储层质量进行衡量的特征元素,并对该统计规律进行了成因分析。为使该方法转为具备实用价值的新技术,主要从地震反演手段与该方法原理的有效结合上,以多种主流地震反演手段进行了多轮试验性研究,最终建立以岩屑分析化验数据为基础的储层质量评价方法。该技术首次以岩屑分析化验数据为基础,利用分频反演方法,以独特的视角描述有利储层的空间展布特征,丰富了钻前研究成果,同时该技术受放射性元素影响小,亦能应用于老井复查工作,在探井数量较少的勘探初期,具有较高的实用价值。文章同时对该方法的分辨率及数据筛选等实际应用问题进行了讨论。该技术在莺歌海盆地某高温高压气田储层预测工作中获得成功应用,6口定向井、1口水平井优质储层的垂深预测误差总体控制在6m(4ms)以内,基本达到ODP随钻调整的精度要求,从而实现了录井、实验、地质与地球物理多学科的有机结合。
The statistical relationship between element contents and reservoir quality suggests that aluminum and vanadium can be used to measure reservoir quality, and the mechanism was analyzed. To make it a valuable reservoir prediction tool, following the principle that combines the mechanism with seismic inversion methods, several experimental researches were conducted on primary seismic inversion methods, and finally a reservoir quality evaluation method was developed based on cuttings analysis data. Specifically, frequency-divided inversion was employed to map the spatial variation of favorable reservoirs based on cuttings analysis data. The method is of great importance to pre-drilling research. In addition, hardly affected by radioactive elements, it is useful for re-examination on old well data, especially in early exploration without enough drilled wells. For field application of this method, the resolution and how to filter data are discussed in this paper. This technology has been applied in a HPHT gas field in the Yinggehai basin and achieved a great success：the TVD prediction error of high quality reservoirs in 6 directional wells and 1 horizontal well is less than 6m（4ms）, which meets the ODP adjustment precision while drilling, and realizes multi-disciplinary dynamic integration of mud logging, experiment, geology and geophysics.
出处
《中国石油勘探》
CAS
北大核心
2017年第6期101-111,共11页
China Petroleum Exploration
基金
中海油能源发展股份有限公司科研项目"高温高压复杂气田中CO2流体对储层影响及元素示踪储层预测技术研究"(HFKJ-CJF1306)
"南海西部海域复杂油气藏ODP实施随钻分析技术研究"(HFKJ-GJF2015012)
关键词
元素含量反演
铝钒元素图版
储层预测
分频反演
莺歌海盆地
element content inversion, AI-V characteristic elementchart, reservoir prediction, frequency-divided inversion,Yinggehai Basin
