摘要
为了进一步弄清莺歌海盆地乐东底辟区中层超压气层的AVO类型及主控因素,探索适合本地区中层相应地质条件下的储层预测及烃类检测方法,进而提高中层勘探成效,从岩石物理统计特征出发,针对底辟区浅、中层2种典型气层在储层成因、物性与温压等方面的差异,以横波速度预测技术为基础,采用流体替代、变孔隙度模拟等手段对该区中层薄气层AVO特征进行了分析。与浅层常压气层的Ⅲ类AVO异常不同,该区中层超压气层主要为Ⅱ类AVO异常,储层孔隙度的变化是影响中层气层波阻抗变化及AVO特征的主控因素。由于该区中层储层物性差,超压薄气层顶界所产生的强振幅异常主要是由于该气层AVO效应和薄气层调谐效应所产生,此类振幅陷阱应在中深层勘探中予以足够重视。
In order to further examine the AVO types and their main controls in overpressured gas reservoirs with a middle depth in Ledong diapir area, Yinggehai basin, explore the methods of reservoir prediction and hydrocarbon detection suitable for the middle-deep intervals there, and finally improve the success rate of exploration in these intervals, the approaches such as fluid substitution and variable porosity simulation were used to analyze the AVO characteristics in thin gas reservoirs with a middle depth in this area,by starting from the statistical petrophysical characteristics, considering the differences in reservoir origin, petrophysics, temperature and pressure for two typical gas reservoirs with a shallow and middle depth respectively in the diapir area, and basing on the technique to predict shear- wave velocity. In contrast to the AVO anomaly of Type Ⅲ in shallow gas reservoirs with normal pres- sure, the overpressure gas reservoirs with a middle depth are predominated by the AVO anomaly of Type II , and the porosity change is the main control over impedance and AVO reservoirs. Owing to poor the reservoir rocks with a characteristics in these gas petrophysical properties of middle depth, the strong amplitude anomalies on the top of these overpressured thin gas reservoirs are primarily caused by their AVO effect and tuning. Such pitfall of amplitude should be given enough attention in gas exploration in these middle-deep intervals.
出处
《中国海上油气》
CAS
CSCD
北大核心
2014年第4期34-40,共7页
China Offshore Oil and Gas
基金
"十二五"国家科技重大专项"莺琼盆地高温高压天然气成藏主控因素及勘探方向(编号:2011ZX05023-004)"部分研究成果
关键词
莺歌海盆地
乐东区
中层薄气层
AVO响应
横波速度预测
正演模拟
调谐效应
Yinggehai basin
Ledong area
thin gasreservoirs with a middle depth
AVO response
shear-wave velocity prediction
forward modeling
tuning effect
