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In order to promote the discovery of new shale gas exploration areas in Guangxi, based on the latest drilling data, through detailed observation and description of logging data and cores, this paper selects high-quality shale samples of the target layer for X-ray diffraction analysis and testing of clay minerals and whole rock, major and trace elements (including rare-earth elements), TOC, and other related analysis and testing. The study shows that the total amount of rare-earth elements in the first member of Lower Carboniferous Luzhai Formation in Rongshui area, Guangxi, is low; δEU and δCE show negative abnormality. The average value of wV/V+Ni, Th / U ratio, and Mo-TOC covariant model diagram of the first member of Luzhai Formation show that it was the condition of anoxic reduction at that time. At the same time, Ba-Sr diagram, Sr/Cu ratio, and total rare-earth elements reflect that the area was in an arid, hot, and marine salt water paleoenvironment during the sedimentary period. Most of the sample parent rocks of the first member of Luzhai Formation are in shale area, and some samples are close to felsic igneous rock area, which is of mixed origin. The tectonic background of the source area is mainly continental island arc and active continental margin, indicating that the sedimentary environment was unstable and highly active under the background of extensional rifting at that time.

Geofluid discrimination plays an important role in reservoir characterization and prospect identification. Compared with other fluid indicators, the effective pore-fluid bulk modulus is more sensitive to the property of fluid contained in reservoirs. We combine the empirical relations with deterministic models to form a new kind of linearized relationship between the mixed fluid/rock term and the fluid modulus. On the one hand, the linearized relationship can decouple the fluid bulk modulus from the mixed fluid/rock term; on the other hand, the decoupled terms are more stable especially in low-porosity situations compared with previous approaches. In terms of the new linearized equation of the fluid modulus, we derive a novel linearized amplitude variation with offset (AVO) approximation to avoid the complicated nonlinear relationship between the fluid modulus and the reflectivity series. Convoluting this linearized AVO approximation with seismic wavelets, the forward modeling is constructed to combine the prestack seismic records with the fluid modulus. Meanwhile, we introduce the Bayesian inference with multivariable Cauchy prior to the fluid modulus inversion for a stable and high-resolution solution. Model examples demonstrate the accuracy of the proposed linearized AVO approximation compared with the exact Zoeppritz equation and Aki-Richards approximate equation. The synthetic and field data tests illustrate the accuracy and feasibility of the proposed fluid modulus inversion approach for geofluid discrimination.