基于五维地震数据的火山机构刻画及岩相识别——以准噶尔盆地石炭系火山岩为例

Characterization of volcano structure and identification of lithofacies based on 5D seismic data:a case study on Carboniferous volcanic rocks in Junggar Basin

五维地震数据可以更好地分析地震波在各向异性介质中传播的旅行时间、速度、振幅、频率和相位等属性随方位角的变化,而且炮检距信息与目标地质体的尺度、地层岩性和流体成分等存在相关性,方位角信息则与地层中的断裂、裂缝等的发育特征相关。为此,提出了基于五维地震资料的火山机构刻画和岩相识别技术。考虑到地下构造在垂直于走向方向的响应更明显的特点,通过构建方位分析窗提取优势方位信息,利用倾角成像增强处理的地震资料预测火山机构,利用倾角及方位角的变化计算相邻道的相似性,提高了地震资料的横向信噪比,明确了火山机构宏观分布范围;通过定义方位时窗,结合地震道反距离加权算法,提取每个方位对断裂最敏感的信息,提高了火山机构刻画精度,得到的火山形态更清晰;再结合核主成分分析(KPCA)融合优势属性预测火山岩有利岩相,精细预测了准噶尔盆地KM1井区的三期火山岩有利区带,为高效勘探、开发该区的火山岩储层奠定了基础。

Five⁃dimensional(5D)seismic data can better analyze the changes in attributes such as travel time,speed,amplitude,frequency,and phase of seismic waves propagating in anisotropic media with azimuth angle.Moreover,the offset information is related to the scale,stratigraphic lithology,and fluid composition of the tar⁃get geological body,while the azimuth angle information is related to the development characteristics of strati⁃graphic faults and fractures.Therefore,this paper proposes a technique for volcanic structure characterization and lithofacies identification based on 5D seismic data.By considering that the underground structure responds more obviously in the direction perpendicular to the strike direction,the paper constructs an azimuth analysis window to extract the dominant azimuth information and uses dip imaging to enhance the processed seismic data,so as to predict the volcanic structure.By using changes in dip and azimuth angles,the paper calculates the similarity of adjacent channels,improves the lateral signal⁃to⁃noise ratio of seismic data,and clarifies the macroscopic distribution range of volcanic structures.By defining the azimuth time window and combining the seismic trace inverse distance weighting algorithm,the paper extracts the most sensitive information about faults at each azimuth angle,improves the accuracy of volcanic structure characterization,and obtains a clearer volcanic morphology.Combined with kernel principal component analysis(KPCA),the dominant attributes are fused to predict the favorable lithofacies of volcanic rocks.The proposed method accurately predicts the fa⁃vorable zones of the third phase of volcanic rocks in the KM1 well area of the Junggar Basin,laying the founda⁃tion for the exploration and development of volcanic rock reservoirs in this area.