The State-of-the-Art Techniques of Hydrocarbon Detection and Its Application in Ultra-Deep Carbonate Reservoir Characterization in the Sichuan Basin, China

Abstract

The Sichuan Basin is one of the most important gas-bearing basins in China, and its production accounts for more than a quarter of the country. In the past 10 years, major natural gas exploration discoveries in the basin were in ultra-deep ancient carbonate formations. The discovery of large marine gas fields has gone through a long period of exploration. For example, the Anyue gas field was discovered after more than 40 years of exploration. The main difficulty stems from deep burial, old age, and the complex geological evolution history of the carbonate rock and the resulting difficulty in identifying gas-bearing reservoirs. Although state-of-the-art reservoir prediction techniques have been used, the success rate of the exploration wells is relatively low. At present, the success rate of the ultra-deep exploration wells is about 30%. To enhance the reliability of the hydrocarbon detection of the ultra-deep carbonate reservoirs, we have developed a few novel methods in the last 10 years, including seismic-print analysis (SPA), depth-domain seismic dispersion analysis (DDSDA), and deep learning seismic analysis Applications to field data show that the results obtained by the new methods are in better agreement with the drilling results. This article presents the methods and their applications in the identification of the ultra-deep carbonate gas-bearing reservoirs in the Sichuan Basin, China. Key issues in hydrocarbon detection of ultra-deep carbonate reservoirs, which have not been solved well, are also discussed.