The use of alternating conditional expectation to predict methane sorption capacity on coal

Feng, Qihong; Zhang, Jiyuan; Zhang, Xianmin; Shu, Chenglong; Wen, Shengjun; Wang, Shuhua; Li, Jiaxiang

doi:10.1016/j.coal.2013.11.011

Cited by 19 publications

(16 citation statements)

References 51 publications

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“…However, the discrepancies of results of experimental studies show that using the coal rank as the only factor evaluating the sorption capacity of coal is a controversial approach [9,19]. Additionally, the petrographic composition of coal [20][21][22], the porous structure [23], or the tectonic disturbances affecting the structural and textural features of the coal seam [24] disturb the clear picture of the relationships described in the literature. It is also known that various petrophysical parameters of coal may have different influences on the sorption properties of coal, and the impact of one of the parameters may limit the influence of another [25].…”

Section: Introductionmentioning

confidence: 99%

Synergy of Parameters Determining the Optimal Properties of Coal as a Natural Sorbent

et al. 2020

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Selection of the optimal properties of coal as a natural sorbent, both as a sample collected from a seam or of the coal seam itself, requires various parameters to be determined and may not be based on the knowledge of metamorphism degree only. In order to improve the predictions of sorption capacity and the kinetics, analyses of correlation and multiple regression based on the results of laboratory studies were performed for 15 coal samples with various coal rank. The maximum vitrinite reflectance (R0) for low-rank coals was 0.78%–0.85%, and 0.98%–1.15% and 1.85%–2.03% for medium- and high-rank coals, respectively. Coal samples were subjected to technical and petrographic analysis. The gravimetric method was used to perform sorption tests using methane, in order to determine the sorption capacity and the effective diffusion coefficient for each of the coals. Pycnometric methods were used to determine the textural parameters of coals, such as the percentage porosity and specific pore volume. The studies were further supplemented with an evaluation of the mechanical properties of the coals, Vickers micro-hardness, and elastic modulus. This work shows that the statistical multiple regression method enables a computational model including the selected petrophysical parameters displaying synergy with the specific sorption property—capacity or kinetics—to be created. The results showed the usefulness of this analysis in providing improved predictions of the optimal sorption properties of coal as a natural sorbent.

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Section: Introductionmentioning

confidence: 99%

Synergy of Parameters Determining the Optimal Properties of Coal as a Natural Sorbent

et al. 2020

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“…To further test the robustness of an estimation model, the normality and homoscedasticity of the estimation results should be analyzed in addition to performing the error evaluation [40]. In this study, the normality and homoscedasticity of the results were assessed by the T-test and F-test, respectively.…”

Section: Evaluation Matricesmentioning

confidence: 99%

Estimation of CO2–brine interfacial tension using an artificial neural network

Zhang

Feng

Wang

et al. 2016

The Journal of Supercritical Fluids

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“…Both average absolute error (AAE) and average absolute relative error (AARE) are used to estimate the accuracy of the calculated results, which are defined as (Feng et al, 2014;Fan et al, 2018b):…”

Section: Permeability Determinationmentioning

confidence: 99%

Radial Permeability Measurements for Shale Using Variable Pressure Gradients

Fan

Sun²,

Elsworth

et al. 2020

Acta Geologica Sinica (Eng)

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Shale gas is becoming an important component of the global energy supply, with permeability a critical controlling factor for long‐term gas production. Obvious deviation may exist between helium permeability determined using small pressure gradient (SPG) methods and methane permeability obtained under actual field production with variable pressure gradients (VPG). In order to more accurately evaluate the matrix permeability of shale, a VPG method using real gas (rather than He) is established to render permeability measurements that are more representative of reservoir conditions and hence response. Dynamic methane production experiments were performed to measure permeability using the annular space in the shale cores. For each production stage, boundary pressure is maintained at a constant and the gas production with time is measured on the basis of volume change history in the measuring pump. A mathematical model explicitly accommodating gas desorption uses pseudo‐pressure and pseudo‐time to accommodate the effects of variations in pressure‐dependent PVT parameters. Analytical and semi‐analytical solutions to the model are obtained and discussed. These provide a convenient approach to estimate radial permeability in the core by nonlinear fitting to match the semi‐analytical solution with the recorded gas production data. Results indicate that the radial permeability of the shale determined using methane is in the range of 1×10−6 – 1×10−5 mD and decreases with a decrease in average pore pressure. This is contrary to the observed change in permeability estimated using helium. Bedding geometry has a significant influence on shale permeability with permeability in parallel bedding orientation larger than that in perpendicular bedding orientation. The superiority of the VPG method is confirmed by comparing permeability test results obtained from both VPG and SPG methods. Although several assumptions are used, the results obtained from the VPG method with reservoir gas are much closer to reality and may be directly used for actual gas production evaluation and prediction, through accommodating realistic pressure dependent impacts.

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The use of alternating conditional expectation to predict methane sorption capacity on coal

Cited by 19 publications

References 51 publications

Synergy of Parameters Determining the Optimal Properties of Coal as a Natural Sorbent

Synergy of Parameters Determining the Optimal Properties of Coal as a Natural Sorbent

Estimation of CO2–brine interfacial tension using an artificial neural network

Radial Permeability Measurements for Shale Using Variable Pressure Gradients

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