Composition, Origin, and Accumulation Model of Coalbed Methane in the Panxie Coal Mining Area, Anhui Province, China.

To investigate the geochemical characteristic, genetic types, and accumulation model of coalbed methane (CBM), 16 samples from a burial depth of 621-1494 m were collected in the Panxie Coal Mining Area of Huainan Coalfield. The results indicate that the samples are dominated by methane, and the concentrations are distributed in the range of 73.11-95.42%. The dryness coefficient is 0.77-1.00 (average, 0.93), and the ratio of methane to the sum of ethane and propane (C1/(C2 + C3)) is 3.18-242.64 (average, 36.15). The δ13CCH4 values are distributed in the range of -65.44 to -32.38‰ (average, -45.22‰), the δDCH4 values are in the range of -226.84 to -156.82‰ (average, -182.93‰), and the δ13CCO2 values are in the range of -19.7 to -10.1‰ (average, -15.51‰). CBM samples in the study area are dominated by thermogenic gases, followed by secondary biogenic gases with CO2 reduction. For the percentages of different genetic gases, the distribution range of thermogenic gas is 70.11-97.86%, whereas that of biogenic gas is 58.65-77.86% for five samples from Zhangji, Panyi, Pansan, and Panbei Coalmines. Moreover, desorption-diffusion fractionation and the effect of groundwater dissolution occurred in the Panxie Coal Mining Area, and higher δ13CCH4 values mostly existed in the deeper coal seams. Furthermore, the biogenic gases are more likely to be secondary biogenic gases generated by CO2 reduction on the basis of data comparison, which is related to the flowing water underground. Accumulation models of different genetic types of CBM are correlated with the burial depth of coal seams, location, and type of faults and aquifers.

Effective Approach with Extra Desorption Time to Estimate the Gas Content of Deep-Buried Coalbed Methane Reservoirs: A Case Study from the Panji Deep Area in Huainan Coalfield, China.

In this study, 11 core coal samples were collected from deep-buried coalbed methane (CBM) reservoirs with burial depth intervals of 900-1500 m for gas estimation content by a direct method. In desorption experiments, the cumulative gas desorption data were recorded within 2 h in the field on the basis of the China National Standard method. For accuracy, two improved methods were proposed. The results show that the gas contents of deep-buried coal samples based on the China National Standard and mud methods are 3.58-9.89 m3/t (average of 6.03 m3/t) and 3.74-10.05 m3/t (average of 6.20 m3/t), respectively. The proposed Langmuir equation and logarithmic equation methods exhibited nonlinear relationships between the cumulative desorption volume and desorption time, which yield values of 6.33-13.34 m3/t (average of 9.36 m3/t) and 6.15-13.86 m3/t (average of 10.37 m3/t), respectively. In addition, the two proposed methods combine the raw data within 2 h by the China National Standard method and additional desorption points during extra time, which are helpful for the ability of the hypothetical methods to calculate the gas content. The Langmuir equation method is a relatively more accurate method to estimate the gas content in comparison with the proposed logarithmic method, which is based on the relative error and comparison plots of actual data and simulated results. From the perspective of numerical value, the Langmuir equation method gives values 1.06-3.39 times (average of 1.86 times) those of the China National Standard method. These analyses show that the proposed Langmuir equation method with extra desorption points is an effective method to determine the gas content of deep-buried CBM reservoirs.

Methodology for Lost Gas Determination from Exploratory Coal Cores and Comparative Evaluation of the Accuracy of the Direct Method.

In the coal exploration of China, the commonly used direct method within 120 min has potential errors in lost gas calculation of deep coal seam for its complex geological conditions. The exploration of deep coal resources by drilling holes in Huainan of Eastern China offered an opportunity to starting research into developing a new method. A developed method with error analysis was constructed to estimate the lost gas using the total desorption process obtained from exploratory coal cores. The accuracy of the direct method was also evaluated comparatively. The result shows that the desorption curve of tested coal samples matches the fitted curve equation. Desorption temperature and the tectonic coal with associated pore characteristics significantly affect the variation of the adsorption characteristics and the estimation of lost gas. The direct method obviously underestimates the lost gas, and methodology using a new lost gas estimation procedure with additional residual gas allows for achieving relatively accurate results of the determination of gas content in coal seams. The calculated result of the new method is about 1.00-1.41 times that of the direct method. The error analysis of desorption results allowed us to determine the dependence between the time (retrieval time and desorption time) and determination method. The time used for desorption in the tank is allowed to extend to less than 400 min or more than 1000 min, which is very potentially important to accurately get the coalbed gas content for coring samples, especially deep exploratory cores for field application.

Preliminary Assessment of the Resource and Exploitation Potential of Lower Permian Marine-Continent Transitional Facies Shale Gas in the Huainan Basin, Eastern China, Based on a Comprehensive Understanding of Geological Conditions.

The Huainan Basin in eastern China contains abundant shale gas resources; the Lower Permian is an exploration horizon with a high potential for shale gas in marine-continent transitional facies. However, few detailed analyses have investigated shale gas in this area. In this paper, a comprehensive investigation of the geochemical characteristics, physical properties, and gas-bearing capacities of shale reservoirs was conducted, and the resource and exploitation potential were evaluated. The results show that the cumulative thicknesses of the Shanxi Formation (P1s) and lower Shihezi Formation (P2xs) are mostly greater than 35 and 65 m, respectively. The TOC contents of the P1s and P2xs shale vary from 0.11 to 8.87% and from 0.22 to 14.63%, respectively; the kerogens predominantly belong to type II with minor amounts of type I or type III kerogens; average R o values range between 0.83 and 0.94% and between 0.82 and 1.02% in P1s and P2xs, respectively; the shale samples are primarily at a low maturity, while some shale samples have entered the high-maturity stage. The shale reservoirs have low permeability and porosity in P1s and P2xs, respectively. The pores of the P1s shale reservoir are characterized by well-developed micropores and transition pores and poorly developed mesopores, while the pores in the P2xs shale reservoir are all characterized by well-developed micropores and transition pores and some well-developed macropores; the different pore types in the shale reservoirs developed in the organic matter, clay minerals, and pyrite, while a few endogenous fractures developed in the organic matter and structural fractures developed in the minerals. The total shale gas contents in P1s and P2xs are 2.85 and 2.96 m3 t-1, respectively. The P2xs shale reservoir has a higher hydrocarbon generation potential than P1s and has a lower gas generation potential. The total shale gas amounts in P1s and P2xs are 3602.29-4083.04 × 108 and 2811.04-3450.77 × 108 m3, respectively. Further research on shale gas exploration and exploitation for these formations needs to be performed.

Ground surface settlement analysis of shield tunneling under spatial variability of multiple geotechnical parameters.

This paper presents an efficient method of shield tunneling reliability analysis using spatial random fields. We introduced two stochastic methods into numerical simulation. The first one computes the maximal ground surface settlement using classical statistics, in which the response surface method is utilized to calculate the failure probability by first-order second moment. Cohesion, internal friction angle, Young's modulus and mechanical model factor are considered as random variables. The second method is the spatial random fields of aforementioned three key geotechnical parameters. Using these two methods, similar multiple soil layers are converted into a stationary random field by local regression as the first step, and then the process is followed by the spatially conditional discretization of multivariate. Failure probability of maximal ground surface settlement is calculated by a subset Monte-Carlo Algorithm. This approach is applied into the four-overlapping shield tunnels of the 5th and 6th metro lines intersecting at Huanhu W Rd station, Tianjin China. The failure analysis results indicated that classical statistics of geotechnical parameters showing higher variability than spatial random fields, which substantially support the complex shield tunneling project.