Rock-physics-based estimation of quartz content in the Shenhu area, South China Sea

Acta Geophysica

article

Deng, Wei¹  Liang, Jinqiang²  He, Yulin¹  Kuang, Zenggui²  Meng, Miaomiao³ 

[1] Guangzhou Marine Geological Survey, China Geological Survey;Natural Gas Hydrate Engineering Technology Center;Southern Marine Science and Engineering Guangdong Laboratory

关键词: Gas hydrate;    Quartz content;    Gas saturation;    Rock physics;    Seismic inversion;    Shenhu;   

DOI  :  10.1007/s11600-020-00489-y

学科分类：地球科学(综合)

来源: Polska Akademia Nauk * Instytut Geofizyki

【 摘 要 】

Estimation of quartz content (QC) is important for gas hydrate production. However, the existing methods pay more attention to estimate saturations of hydrate or free gas instead of QC. QC is difficult to be estimated because of its limited and unclear influences on velocities in the hydrate-bearing sediments. A workflow was proposed to estimate QC from core to logging to seismic inversion whose core technologies were an unconsolidated anisotropic model (UAM) and an inverse modeling approach. We used the UAM to construct the quantitative relationships between physical properties including QC and velocity. Then, the velocities of the reservoirs were obtained by logging-constrained seismic inversion. Finally, QC can be scaled by the inverse modeling of the UAM. To build the UAM, we analyzed the physical properties of hydrate reservoirs based on the cores and logging while drilling (LWD) data in the Shenhu area, South China Sea, and characterized unconsolidated sediments with horizontally layered hydrates and gas occurrences. The calculated P-velocities and S-velocities from the UAM agreed with the LWD data when the input variables were QC, porosity, hydrate saturation, and gas saturation. Conversely, for a group of P-velocity and S-velocity from seismic inversion, the corresponding QC can be scaled out as well as the other parameters based on the UAM, which was defined as an inverse modeling. Because the significant parameters such as hydrate saturation have been considered as independent variables in the model, we can effectively avoid the correlation between QC and the others. Prediction multiplicity can be reduced. The estimated QC was consistent with the drilling and geological understanding in the field application, indicating that the method proposed is effective and practical.

【 授权许可】

Unknown