Integrated Petrophysical Evaluation of Shale Gas Reservoirs for Wufeng-Longmaxi Formation in Southeast Chongqing

• Published in: IOP conference series. Earth and environmental science Vol. 804; no. 2; pp. 22019 - 22028
• Main Authors: Yan, Ping, Kou, Xiaopan, Hu, Gang, Yin, Qian, Zhang, Lina, Wang, Wei, Lai, Fuqiang
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.07.2021
• Subjects: Acoustic resonance; adsorbed gas; Carbon content; core analysis; Data logging; Design optimization; Evaluation; free gas; Gamma rays; integrated petrophysical evaluation; Kerogen; Mineralogy; Natural gas; Natural gas exploration; NMR; Nuclear magnetic resonance; Oil and gas exploration; Oil exploration; Organic carbon; Permeability; Porosity; Reservoirs; Rocks; Shale; Shale gas; Shales; Spectroscopy; TOC; Total organic carbon; X-ray diffraction
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/804/2/022019

Abstract Shale gas is an important unconventional natural gas resource. Different from conventional oil and gas exploration, gas shale is not only the source rock of natural gas, but also the cap rock and reservoir. This paper presents a logging interpretation method for comprehensive evaluation of shale gas. Taking well A in southeast Chongqing from Sichuan Basin as an example, the shale gas reservoir of Wufeng-Longmaxi formation is evaluated. This method makes full use of conventional logging data (gamma ray, array lateral resistivity, density, neutron, acoustic, spectral gamma ray), unconventional log data (NMR Nuclear Magnetic Resonance, ECS Elemental Capture Spectroscopy) and core experiment data (X-ray Diffraction, Tight Rock Analysis, Methane Adsorption Isotherm). This method of combining logging data with core measurement can provide mineralogy, porosity, permeability, saturation, kerogen volume, total organic carbon content, absorbed gas content and free gas content. The methods provide a means to understand the petrophysical properties and reservoir quality of Wufeng-Longmaxi shale. This information can help to determine the “sweet spot” along the vertical to land and design a selective completion strategy to optimize well productivity.