Characterization of gas hydrate distribution using conventional 3D seismic data in the Pearl River Mouth Basin, South China Sea

2016 ◽  
Vol 4 (1) ◽  
pp. SA25-SA37 ◽  
Author(s):  
Xiujuan Wang ◽  
Jin Qian ◽  
Timothy S. Collett ◽  
Hesheng Shi ◽  
Shengxiong Yang ◽  
...  

A new 3D seismic reflection data volume acquired in 2012 has allowed for the detailed mapping and characterization of gas hydrate distribution in the Pearl River Mouth Basin in the South China Sea. Previous studies of core and logging data showed that gas hydrate occurrence at high concentrations is controlled by the presence of relatively coarse-grained sediment and the upward migration of thermogenic gas from the deeper sediment section into the overlying gas hydrate stability zone (BGHSZ); however, the spatial distribution of the gas hydrate remains poorly defined. We used a constrained sparse spike inversion technique to generate acoustic-impedance images of the hydrate-bearing sedimentary section from the newly acquired 3D seismic data volume. High-amplitude reflections just above the bottom-simulating reflectors (BSRs) were interpreted to be associated with the accumulation of gas hydrate with elevated saturations. Enhanced seismic reflections below the BSRs were interpreted to indicate the presence of free gas. The base of the BGHSZ was established using the occurrence of BSRs. In areas absent of well-developed BSRs, the BGHSZ was calculated from a model using the inverted P-wave velocity and subsurface temperature data. Seismic attributes were also extracted along the BGHSZ that indicate variations reservoir properties and inferred hydrocarbon accumulations at each site. Gas hydrate saturations estimated from the inversion of acoustic impedance of conventional 3D seismic data, along with well-log-derived rock-physics models were also used to estimate gas hydrate saturations. Our analysis determined that the gas hydrate petroleum system varies significantly across the Pearl River Mouth Basin and that variability in sedimentary properties as a product of depositional processes and the upward migration of gas from deeper thermogenic sources control the distribution of gas hydrates in this basin.

2020 ◽  
Vol 39 (3) ◽  
pp. 176-181
Author(s):  
Jun Liu ◽  
Donghai Liang ◽  
Guangrong Peng ◽  
Xiaomin Ruan ◽  
Yingwei Li ◽  
...  

In the Enping 17 sag within the Pearl River Mouth Basin in the South China Sea, one wildcat well has been drilled to the Lower Paleogene Enping Formation (FM EP) and partially into the Wenchang Formation (FM WC) for deep formation hydrocarbon exploration. However, no commercial play was discovered. The reasons for this are clear if the petroleum systems modeling is examined. In FM EP, the main reason for failure is due to poor sealing. In FM WC, the failure is due to the lack of a good reservoir for hydrocarbon accumulation. Encountering a 9 m thick reservoir at a depth of 4650 m indicates that braided fluvial delta and lowstand turbidite sandstone may develop in FM WC. With the objective of establishing cap rock in FM EP and reservoir rock in FM WC, and in the absence of sufficient well data, an integrated framework for 3D seismic reservoir characterization of offshore deep and thin layers was developed. The workflow includes seismic data reprocessing, well-log-based rock-physics analysis, seismic structure interpretation, simultaneous amplitude variation with offset (AVO) inversion, 3D lithology prediction, and geologic integrated analysis. We present four key solutions to address four specific challenges in this case study: (1) the application of adaptive deghosting techniques to remove the source and streamer depth-related ghost notches in the seismic data bandwidth and the relative amplitude-preserved bandwidth extension technique to improve the seismic data resolution; (2) a practical rock-physics modeling approach to consider the formation overpressure for pseudoshear sonic log prediction; (3) interactive and synchronized workflow between prestack 3D AVO inversion and seismic processing to predict a 9 m thick layer in FM WC through more than 60 rounds of cyclic tests; and (4) cross validation between seismic qualitative attributes and quantitative inversion results to verify the lithology prediction result under the condition of insufficient well data.


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