The physical and chemical texture of tectonically deformed coals produced by various formational mechanisms are different from those of primary coals, thus resulting in major differences among the physical properties of the reservoirs of these coals. We have studied the adsorption/desorption behavior of tectonically deformed coals by the use of isothermal adsorption/desorption experiments under equilibrium moisture condition. Experiments of isothermal adsorption/desorption of methane or multi-component gases have indicated that, the adsorption curves of coals with a low degree of tectonic deformation conform to the type of isothermal adsorption curve described by the Langmuir equation; the methane adsorption curves of coals with strong tectonic deformation cannot be described by the Langmuir equation. The adsorption/desorption process of methane and multi-component gases in the deformed coals is not consistent with primary coals, which form an effect of hysteresis in different kinds of tectonically deformed coals. With the change of pore structure of tectonically deformed coals at reservoir condition, the added adsorbed CH 4 in the experiments is desorbed on the pore surface of coals during the pressure reduction process. Thus, the result shows that the adsorption volume in the process of desorbing is greater than that in adsorbing. Because of the deformation, structural change, and transformation of the adsorption potential field of coals, it is essential to form a new kind of isothermal adsorption curve and the hysteresis effect of the desorption process.tectonically deformed coal, adsorption/desorption behavior, methane, multi-component gases, hysteresis effectThe physical and chemical texture of coals and their properties have been comprehensively investigated and discussed by scientists throughout the world [1][2][3][4] . Further, scientists have intensively studied the coal and gas outbursts experienced in nearly all the major coal-producing countries [5,6] . Of the extensive research on coal and gas outbursts, the study of tectonically deformed coals is of vital importance [7][8][9] . Within these deformed coals, the adsorption/desorption behavior and higher gas content are the major scientific problems. In fact, tectonically deformed coal is a type of coals in which, under mono-or multi-phases tectonic stress fields, the primary texture and structure were deformed, broken or destroyed, even the chemical composition was changed. Tectonically deformed coals formed by different deformational mechanisms are divided into three series of deformation and ten classes: the series of brittle deformation include cataclastic structure coal, mortar structure coal, granulitic structure coal, mealy structure coal, schistose structure coal, and thin-layer structure coal; the series of ductile deformation include wrinkle structure coal, mylonitic structure coal and ductile structure coal; the series of brittle-ductile include scale structure coal [9] .

The serious geological hazards occurred frequently in the last few years. They have inflicted heavy casualties and property losses. Hence, it is necessary to design a geological information service system to analyze and evaluate geological hazards. With the development of computer and Internet service model, it is now possible to obtain rich data and process the data with some advanced computing techniques under network environment. Then, some technologies, including cyber-physical system, Internet of Things, and cloud computing, have been used in geological information management. Furthermore, the concept of cyber-physical-social-thinking as a broader vision of the Internet of Things was presented through the fusion of those advanced computing technologies. Motivated by it, in this article, a novel modeling and computing method for geological information service system is developed in consideration of the complex data processing requirement of geological service under dynamic environment. Specifically, some key techniques of modeling the information service system and computing geological data via cyber-physical system and Internet of Things are analyzed. Moreover, to show the efficiency of proposed method, two application cases are provided during the cyber-physical-social-thinking modeling and computing for geological information service system.

Knowledge graph (KG) as a popular semantic network has been widely used. It provides an effective way to describe semantic entities and their relationships by extending ontology in the entity level. This article focuses on the application of KG in the traditional geological field and proposes a novel method to construct KG. On the basis of natural language processing (NLP) and data mining (DM) algorithms, we analyze those key technologies for designing a KG towards geological data, including geological knowledge extraction and semantic association. Through this typical geological ontology extracting on a large number of geological documents and open linked data, the semantic interconnection is achieved, KG framework for geological data is designed, application system of KG towards geological data is constructed, and dynamic updating of the geological information is completed accordingly. Specifically, unsupervised intelligent learning method using linked open data is incorporated into the geological document preprocessing, which generates a geological domain vocabulary ultimately. Furthermore, some application cases in the KG system are provided to show the effectiveness and efficiency of our proposed intelligent learning approach for KG.