Characteristics Of Shale Petrology And Its Effect On Adsorbed Gas

The exploitation of shale-gas is of great significance to improve the environment and energy security, and ease the contradiction between supply and demand of domestic energy. Shale petrological analysis is the foundation of the shale reservoir research, like shale gas reservoir evaluation and selection of fracturing technology. Adsorption of shale gas adsorbed on the pore surface of organic matter, or on the surface of clay minerals, so the shale components controls the adsorption volume to some extent. Therefore, establishing the relationship between components of shale content and adsorbed gas content is of great significance to the objective evaluation and prediction of shale gas reservoir adsorption capacity.Silurian Longmaxi shale of Fuling Jiaoshiba district in Sichuan Basin is the research object. Using X-ray diffraction analyzer, X-ray fluorescence analyzer, carbon sulfur analyzer and optical microscope analyzed44pieces of shale sample, containing the mineral composition, the main micro elements, organic carbon content and maturity of kerogen. Combining with field emission scanning electron microscopy (SEM) and energy spectrum analysis, a deep understanding was obtained about the petrological characteristics of the shale in the study area. Using methane adsorption/desorption experiments of shale, this paper discussed the influence of temperature, pressure, TOC and clay minerals content on the adsorption capacity of influence, through the calculation of the shale isosteric heat of adsorption the adsorption heat of limit reveals the adsorption characteristics of methane in shale surface. On the basis of low-temperature nitrogen adsorption and high-pressure mercury injection results, the effect of components on the pore structure of shale was explored. Multivariate statistical analysis method was used to build the adsorption volume prediction equation based on shale composition content.Fuling Jiaoshiba shale is in the bottom of Silurian Longmaxi formed in the deep-water shelf facies with high organic matter content (average3.82%) and developed pyrite (average3.23%), etc. Shale minerals are mainly composed of quartz and clay. Illite, illite/smectite interlayer mineral and chlorite are the main clay types. Biogenic silica minerals enrichment is the main reason for the higher quartz content in Longmaxi formation at the bottom than tha t of the middle. Under the scanning electron microscopy (SEM), mineral grains closely packed, diversified, and sorted with size small and good roundness.Methane adsorption/desorption of shale experimental results can be used to fit the Langmuir model well, and show that the methane is single molecule layer adsorption in shale pore wall. The limit of the shale adsorption heat is less than chemical reaction heat, which means that methane adsorption belongs to physical adsorption phenomenon. With the increasing of the adsorption quantity, the isosteric heat of adsorption is reduced with a nonlinear decreasing, which indicates that pore wall surface energy differs on the pore wall and related properties like pore size.Pore structure analysis that based on low-temperature nitrogen adsorption method and high pressure mercury injection method showed that there were three main peak of pore radius, which is the main peak of2～5nm,100～200nm peak time, and1-10microns peak times. The organic matter content and maturity controls the micropores smaller than2nm, while TOC and clay minerals affect the2～50nm mesoporous pore development. Quartz, feldspar and clay minerals had a greater influence on pores bigger than50nm.The adsorption capacity was affected by the content of organic matter and clay mineral content. The adsorption capacity was highly correlated with TOC, and showed a moderate correlation with illite/smectite interlayer mineral and chlorite, and a weak correlation with illite. Using multivariate statistical method, based on shale components, a linear prediction model of shale adsorbed gas content was constructed, and the test results of the model showed that the variable residuals obey normal distribution, since the samples’point data was taken from normal population which can represent the overall characteristics of the statistical significance.