孟大江, 文鹏飞, 张宝金, 张如伟, 李延, 赵斌, 沈尚峰. 天然气水合物储层反演及饱和度预测[J]. 海洋地质前沿, 2019, 35(11): 43-51. DOI: 10.16028/j.1009-2722.2019.11007
    引用本文: 孟大江, 文鹏飞, 张宝金, 张如伟, 李延, 赵斌, 沈尚峰. 天然气水合物储层反演及饱和度预测[J]. 海洋地质前沿, 2019, 35(11): 43-51. DOI: 10.16028/j.1009-2722.2019.11007
    MENG Dajiang, WEN Pengfei, ZHANG Baojin, ZHANG Ruwei, LI Yan, ZHAO Bin, SHEN Shangfeng. GAS HYDRATE RESERVOIR INVERSION AND SATURATION PREDICTION[J]. Marine Geology Frontiers, 2019, 35(11): 43-51. DOI: 10.16028/j.1009-2722.2019.11007
    Citation: MENG Dajiang, WEN Pengfei, ZHANG Baojin, ZHANG Ruwei, LI Yan, ZHAO Bin, SHEN Shangfeng. GAS HYDRATE RESERVOIR INVERSION AND SATURATION PREDICTION[J]. Marine Geology Frontiers, 2019, 35(11): 43-51. DOI: 10.16028/j.1009-2722.2019.11007

    天然气水合物储层反演及饱和度预测

    GAS HYDRATE RESERVOIR INVERSION AND SATURATION PREDICTION

    • 摘要: 沉积物含天然气水合物后通常会引起速度的增加,与周围地层形成较大的波阻抗差异,利用地震波阻抗反演技术可识别出这种差异,从而预测天然气水合物的分布。测井资料具有较高的纵向分辨率,而地震资料横向分辨率较高,通过井震联合反演可获得天然气水合物准确的空间展布形态。利用井震联合反演技术对南海北部神狐海域天然气水合物储层进行了精细刻画,研究表明,该矿区天然气水合物储层表现为高波阻抗特征,其值域范围为3 450~4 500 m/s·g/cm3,同时根据有效介质模型建立了岩石物理量版,预测了天然气水合物储层的孔隙度和饱和度数据,预测结果与测井解释结果吻合度较高,为天然气水合物的资源评价提供了比较准确的物性数据。

       

      Abstract: Seismic velocity in sediment will increase when gas hydrate occurs, and the impedance of the sediment is greatly different form surrounding sediments. Therefore, seismic impedance inversion technology, which may identify the difference between the sediments with and without gas hydrate, is used to predict the distribution of natural gas hydrate. Since logging data have high vertical resolution and seismic data have high lateral resolution, accurate spatial distribution of gas hydrate can be obtained by joint inversion of well data and seismic data. The gas hydrate reservoir in Shenhu sea area, northern South China Sea, was characterized by such well-seismic inversion technology. The study shows that the gas hydrate reservoir in the area is characterized by high impedance, ranging between 3450-4500m/s*g/cm3. At the same time, the petrophysical templates for porosity and saturation prediction was established according to the effective medium model. The predicted porosity and saturation data of gas hydrate reservoir are in good agreement with the log interpretation results, which provides more accurate physical property data for calculation of gas hydrate reserves.

       

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