A fast complex domain-matching pursuit algorithm and its application to deep-water gas reservoir detection. (25th September 2017)

• Record Type: Journal Article
• Authors: Zeng, Jing; Huang, Handong; Li, Huijie; Miao, Yuxin; Wen, Junxiang; Zhou, Fei
• Is Part Of: Journal of geophysics and engineering. Volume 14:Number 6(2017:Dec.)
• Page Start: 1335
• Page End: 1348
• Publication Date: 2017-09-25
• Subjects: spectral decomposition -- complex domain-matching pursuit -- reservoir fluid mobility -- deep-water gas reservoir; Geophysics -- Periodicals; Prospecting -- Geophysical methods -- Periodicals; Engineering -- Periodicals; 622.1505
• DOI: 10.1088/1742-2140/aa7bd8
• Languages: English
• ISSNs: 1742-2132

Abstract

Abstract: The main emphasis of exploration and development is shifting from simple structural reservoirs to complex reservoirs, which all have the characteristics of complex structure, thin reservoir thickness and large buried depth. Faced with these complex geological features, hydrocarbon detection technology is a direct indication of changes in hydrocarbon reservoirs and a good approach for delimiting the distribution of underground reservoirs. It is common to utilize the time–frequency (TF) features of seismic data in detecting hydrocarbon reservoirs. Therefore, we research the complex domain-matching pursuit (CDMP) method and propose some improvements. First is the introduction of a scale parameter, which corrects the defect that atomic waveforms only change with the frequency parameter. Its introduction not only decomposes seismic signal with high accuracy and high efficiency but also reduces iterations. We also integrate jumping search with ergodic search to improve computational efficiency while maintaining the reasonable accuracy. Then we combine the improved CDMP with the Wigner–Ville distribution to obtain a high-resolution TF spectrum. A one-dimensional modeling experiment has proved the validity of our method. Basing on the low-frequency domain reflection coefficient in fluid-saturated porous media, we finally get an approximation formula for the mobility attributes of reservoir fluid. This approximation formula is used as a hydrocarbon identification factor to predict deep-water gas-bearing sand of the M oil field in the South China Sea. The results are consistent with the actual well test results and our method can help inform the future exploration of deep-water gas reservoirs.