AUTHOR=Zhang Guanyu , Huang Xuri , Xu Yungui , Tang Shuhang , Chen Kang , Peng Da 

TITLE=Deep carbonate gas reservoir sweet spot identification with seismic data based on dual-factor control of sedimentary facies and fault system

JOURNAL=Frontiers in Earth Science

VOLUME=Volume 12 - 2024

YEAR=2024

URL=https://www.frontiersin.org/journals/earth-science/articles/10.3389/feart.2024.1427426

DOI=10.3389/feart.2024.1427426

ISSN=2296-6463

ABSTRACT=The deep carbonate reservoir of the Dengying Formation in the Sichuan Basin is one of the main production zones for natural gas development. The reservoirs are deeply buried with strong heterogeneity and poor seismic data quality which makes the prediction of sweet spots a challenge. Furthermore, the reservoir properties are largely determined by sedimentary facies and fault system, which shares similar seismic responses and increasing the difficulty of sweet spot identification. To solve this problem, we propose a dual-factor controlled sweet spot prediction method with two steps. We first identify sedimentary facies and faults separately at different seismic scales using different attributes by steerable pyramid (SP) method. SP method decomposes the original seismic data into high-frequency and low-frequency data. The amplitude attributes from high-frequency data are used to identify mound-shoal facies, while coherence attributes based on low-frequency data are used to characterize the fault systems. After separately identifying sedimentary facies and faults, we merge these two attribute volumes together to predict reservoir sweet spot. The prediction accuracy is verified with the well production data. The field study indicates that the deep carbonate reservoir quality of the Dengying Formation is controlled by both sedimentary facies and fault systems. Sedimentary facies generally control the type and distribution of reservoirs, while strike-slip fault systems control the migration and accumulation of gas. Additionally, the fault systems serve as karst channels to further improve the reservoir properties. The prediction based on the dual-factor controlled sweet spot prediction method can effectively locate reservoir sweet spots, providing favorable technical support for efficient development.