Acoustic Prediction and Risk Evaluation of Shallow Gas in Deep-Water Areas

被引:6
作者
Yang Jin [1 ]
Wu Shiguo [2 ]
Tong Gang [3 ]
Wang Huanhuan [1 ]
Guo Yongbin [4 ]
Zhang Weiguo [4 ]
Zhao Shaowei [5 ]
Song Yu [1 ]
Yin Qishuai [1 ]
Xu Fei [1 ]
机构
[1] China Univ Petr, Coll Safety & Ocean Engn, Beijing 102249, Peoples R China
[2] Chinese Acad Sci, Inst Deep Sea Sci & Engn, Sanya 572000, Peoples R China
[3] CNOOC Res Inst, Beijing 100028, Peoples R China
[4] CNOOC China Ltd, Shenzhen Branch, Shenzhen 518000, Peoples R China
[5] CNOOC China Ltd, Beijing 100010, Peoples R China
关键词
shallow gas; acoustic simulation experiment; sound wave speed; pressure coefficient; risk evaluation; POROSITY; VELOCITY;
D O I
10.1007/s11802-022-4790-z
中图分类号
P7 [海洋学];
学科分类号
0707 ;
摘要
Shallow gas is a potential risk in deep-water drilling that must not be ignored, as it may cause major safety problems, such as well kicks and blowouts. Thus, the pre-drilling prediction of shallow gas is important. For this reason, this paper conducted deep-water shallow gas acoustic simulation experiments based on the characteristics of deep-water shallow soil properties and the theory of sound wave speed propagation. The results indicate that the propagation speed of sound waves in shallow gas increases with an increase in pressure and decreases with increasing porosity. Pressure and sound wave speed are basically functions of the power exponent. Combined with the theory of sound wave propagation in a saturated medium, this paper establishes a multivariate functional relationship between sound wave speed and formation pressure and porosity. The numerical simulation method is adopted to simulate shallow gas eruptions under different pressure conditions. Shallow gas pressure coefficients that fall within the ranges of 1.0-1.1, 1.1-1.2, and exceeding 1.2 are defined as low-, medium-, and high-risk, respectively, based on actual operations. This risk assessment method has been successfully applied to more than 20 deep-water wells in the South China Sea, with a prediction accuracy of over 90%.
引用
收藏
页码:1147 / 1153
页数:7
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