Application of multi-attribute analysis technology based on FCM algorithm in fine characterization of sedimentary microfacies： take T Gas Field in Xihu Sag as an example
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摘要:
西湖凹陷T气田经过十多年的勘探与开发，亟需在主力层花港组内寻找潜力目标。该区为浅水三角洲沉积体系，岩性组合在空间上变化快，为了精确识别河道砂体及其边界，在海上少井条件下利用三维地震资料识别并刻画河道砂体。在等时地层划分的基础上，对目的层段进行岩石物理性质分析，通过地震沉积学的技术方法结合岩芯及测井等资料，对沉积微相做出初步判断，在此基础上提取6类48种地震属性，与砂厚及各属性之间进行相关性分析，对地震属性进行优选，将优选出的3种反映地质体边界、岩性较好的地震属性采用基于模糊C-均值（FCM）算法的多属性聚类分析，以达到数据降维、减少冗余的效果，研究分流河道沉积体系的整体展布规律。再进行多属性RGB融合显示，增强河道砂体边界的刻画，结合构造特征以及预测的砂体厚度综合分析，提出有利目标区，为后续油田滚动开发及井位部署提供依据。
Abstract:After 10+ years of exploration and development of the T Gas Field in the Xihu Sag in East China Sea, it is urgent to find potential targets in the Oligocene Huagang Formation. To identify channel sand body and its boundary accurately, 3D seismic data were used based on data of several offshore wells. The petrophysical properties of the target stratum were analyzed based on isochronous stratigraphic division, and the sedimentary microfacies were preliminarily specified by seismic sedimentology and logging data. In total, 48 seismic attributes were extracted in six categories. Correlation analysis was conducted on sand thickness and each attribute, from which three most meaningful seismic attributes were determined and selected. The three seismic attributes could well reflect the geological body boundaries and ideal lithology. In addition, multi-attribute clustering analysis based on the FCM (Fuzzy C-Means clustering) algorithm was performed, by which the effect of data dimension and redundancy were reduced. In addition, the distribution of distributary channel depositional system was studied, and RGB fusion display was carried out to highlight channel sand body boundaries. By combining the comprehensive analysis on geological structure and predicted sand body thickness, the favorable target area was proposed, which provides a basis for the subsequent rolling development of oilfield and the well location deployment.
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表 1 地震属性及砂厚相关系数矩阵
Table 1. Correlation coefficient matrix of seismic attribute and sand thickness
砂厚 RMS ATA AE AIF ARS EB IF IFB MIN EHT RAI SWEET 砂厚 1 RMS 0.591 1 ATA 0.516 0.623 1 AE 0.321 0.687 0.827 1 AIF 0.477 0.258 0.757 0.795 1 ARS 0.542 0.347 0.732 0.825 0.914 1 EB 0.254 0.024 0.335 0.452 0.426 0.387 1 IF 0.376 0.276 0.712 0.458 0.654 0.468 0.745 1 IFB 0.421 0.127 0.665 0.521 0.698 0.498 0.719 0.932 1 MIN 0.612 0.489 0.587 0.529 0.455 0.325 0.689 0.552 0.548 1 EHT 0.201 0.287 0.473 0.492 0.512 0.585 0.552 0.367 0.419 0.652 1 RAI 0.378 0.128 0.269 0.325 0.186 0.392 0.655 0.425 0.691 0.225 0.362 1 SWEET 0.318 0.165 0.285 0.487 0.287 0.348 0.318 0.189 0.254 0.347 0.395 0.516 1 注：RMS_Amplitude-均方根振幅，ATA-平均波谷振幅，AE-平均能量，AIF-平均反射频率，ARS-平均反射强度，EB-有效带宽，IF-瞬时频率，IFB-瞬时频宽，MIN-最小振幅值，EHT-能量半衰时，SWEET-甜点，RAI-相对声波阻抗。 
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