M.J. Lemos de Sousa

The measurement of coal porosity with different gases

Abstract Sorption processes can be used to study different characteristics of coal properties, such as gas content (coalbed methane potential of a deposit), gas diffusion, porosity, internal surface area, etc. Coal microstructure (porosity system) is relevant for gas flow behaviour in coal and, consequently, directly influences gas recovery from the coalbed. This paper addresses the determination of coal porosity (namely micro- and macroporosity) in relation to the molecular size of different gases. Experiments entailed a sorption process, which includes the direct method of determining the “void volume” of samples using different gases (helium, nitrogen, carbon dioxide, and methane). Because gas behaviour depends on pressure and temperature conditions, it is critical, in each case, to know the gas characteristics, especially the compressibility factor. The experimental conditions of the sorption process were as follows: temperature in the bath 35 °C; sample with moisture equal to or greater than the moisture-holding capacity (MHC), particle size of sample less than 212 μm, and mass ca. 100 g. The present investigation was designed to confirm that when performing measurements of the coal void volume with helium and nitrogen, there are only small and insignificant changes in the volume determinations. Inducing great shrinkage and swelling effects in the coal molecular structure, carbon dioxide leads to “abnormal” negative values in coal void volume calculations, since the rate of sorbed and free gas is very high. In fact, when in contact with the coal structure, carbon dioxide is so strongly retained that the sorbed gas volume is much higher than the free gas volume. However, shrinkage and swelling effects in coal structure induced by carbon dioxide are fully reversible. Methane also induces shrinkage and swelling when in contact with coal molecular structure, but these effects, although smaller than those induced by carbon dioxide, are irreversible and increase the coal volume.

Documented international enquiry on solid sedimentary fossil fuels; Coal: definitions, classifications, reserves-resources and energy potential

Abstract This paper deals with all solid sedimentary fossil fuels, i.e. coal, the main one for geological reserves and resources, peat, and oil shales. Definitions of coal ( The 50% ash limit, already adopted by UN-ECE for coal definition, allows the creation of a new category—the organic shales (50–75% ash)—comprising energetic materials still valuable for thermal use (coal shales) or to be retorted for oil production (oil shales). Geological relations between coals, oil shales, solid bitumen, liquid hydrocarbons, natural gas, and coalbed methane are also examined together with environmental problems. As a final synthesis of all topics, the paper discusses the problems related with a modern geological classification of all solid sedimentary fuels based on: various rank parameters (moisture content, calorific value, reflectance), maceral composition, and mineral matter content (and washability). Finally, it should be pointed out that the paper is presented as series of problems, some of them old ones, but never resolved until now. In order to facilitate the next generation of coal geologists to resolve these problems on the basis of international agreements, all sections begin with documented introductions for further questions opening an international enquiry. The authors hope that the answers will be abundant enough and pertinent to permit synthetic international solutions, valuable for the new millennium, with the help of interested consulted authorities, international pertinent organisations, and regional experts.

A progress report on the Alpern Coal Classification

Abstract The Alpern Coal Classification has already been largely utilized and successfully applied, both to Laurasian (North Atlantic) and Gondwana coals. It was accepted on basic principles by the International Committee for Coal Petrology, and, as the official contribution of France, it has been recently also partly adopted by the Economic Commission for Europe of the United Nations in Geneva (1988). This paper deals with the improvement of the previous versions of the classification, mainly by introducing new statistical data in order to establish more accurately proposed rank limits. A ternary division for RANK is maintained with the categories: low-rank coal or lignite (instead of brown coal because high-rank lignites may be black not brown), medium-rank coal or bituminous coal, and high-rank coal or anthracite. The prefixes hypo-, meso- and meta-, are used for rank subdivision, thus avoiding non-coherent previous prefixes such as sub-(bituminous) and semi-(anthracite). The selected rank parameters are: moisture holding capacity (ash free) and calorific value (moist, ash free) for lignites, mean random reflectance for bituminous coals and anthracites. Correlations for bed moisture (ash free) and calorific value (dry, ash free) are given for lignites. Correlations for volatile-matter content, mean maximum vitrinite-reflectance, and hydrogen content are also given for bituminous coals and anthracites. TYPE is determined from maceral data and is divided into: vitric (vitrinite (V) > 60%), fusic [V liptinite (L), and liptic (V) . I). The ash content and the washability potential at 10% ash level are used to determine GRADE (or FACIES) and allow the distinction between transportable clean coals and non-washable coals. The run-of-mine ash content (dry basis) permits the division between: coal, middlings, and shale. If the type is liptic, the subdivisions “sapropelic coals” and “oil shales” are used. These are not washable but are solid fuels with a positive energy potential. If the coals to be classified are clean (or washed) the vertical axis becomes free and can be used, for example, for swelling properties in bituminous coals. The system has been recently computerized and allows for data to be displayed effectively for all relevant fields of application. Computer-output examples are presented for coals from a Euramerican and a Gondwana basin.

Source rock/dispersed organic matter characterization—TSOP research subcommittee results

Abstract Because sedimentary organic matter consists of a diverse mixture of organic components with different properties, a combination of chemcial and petrographic results offers the most complete assessment of source rock properties. The primary purpose of this Society for Organic Petrology (TSOP) subcommittee is to contribute to the standardization of kerogen characterization methods. Specific objectives include: (1) evaluation of the applications of different organic matter (petrographic) classifications and terminology, and (2) integration of petrographic and geochemical results. These objectives were met by completing questionnaires, and petrographic, geochemical and photomicrograph round-robin exercises. Samples that were selected for this study represent different petrographic and geochemical properties, and geologic settings to help identify issues related to the utilization of different classifications and techniques. Petrographic analysis of the organic matter was completed using both a prescribed classification and the individual classification normally used by each participant. Total organic carbon (TOC), Rock-Eval pyrolysis and elemental analysis were also completed for each sample. Significant differences exist in the petrographic results from both the prescribed and individual classifications. Although there is general agreement about the oil- vs gas-prone nature of the samples, comparison of results from individual classifications is difficult due to the variety of nomenclature and methods used to describe an organic matter assemblage. Results from the photomicrograph exercise document that different terminology is being used to describe the same component. Although variation in TOC and Rock-Eval data exists, geochemical results define kerogen type and generative potential. Recommendations from this study include: 1. (1) A uniform organic matter classification must be employed, which eliminates complex terminology and is capable of direct correlation with geochemical parameters. 2. (2) A standardized definition and nomenclature must be used for the unstructured (amorphous) organic matter category. Subdivisions of this generalized amorphous category are needed to define its chemical and environmental properties. 3. (3) Standardized techniques including multimode illumination, types of sample preparations and data reporting will help eliminate variability in the type and amount of organic components reported.

Detection and evaluation of hydrocarbons in source rocks by fluorescence microscopy

Abstract In pursuing the detection of hydrocarbons in sedimentary rocks by conventional petrological methods, an attempt has been made to correlate standard fluorescence parameters with the quality and quantity of hydrocarbons present in crushed rocks embedded in epoxy resin. The capacity of the embedding resin, commonly used in the preparation of petrographic samples, to extract and physically fix hydrocarbons is recognized. This phenomenon permits one to measure monochromatic fluorescence parameters, I 546 and Q (u.v.) 650/500, on the trapped hydrocarbons and to correlate these parameters with selected geochemical data. The potential application of using these petrological parameters to evaluate oil quantities and qualities is tested using real case studies. It is also shown that it is possible to directly detect the mature zone in each case.

Gas diffusion coefficient in coal: calculation of tangent slope accuracy through the inflection point determination

This investigation aims to develop an accurate method to calculate the tangent slope (b) - a fundamental parameter to calculate gas diffusion coefficients under different pressures - using inflection point determinations. The authors also studied the different tangent slope behaviours depending on the experimental gas sorption used. The single Langmuir model for individual gases and the extended Langmuir model, for multicomponent gas mixtures were applied to fit experimental gas sorption isotherm data. Two coals were selected in order to minimize and/or avoid the maceral composition and vitrinite mean random reflectance effects. Samples were submitted to three different gas compositions, viz. 99.999% CH4; 99.999% CO2; and a gas mixture containing 74.99% CH4 + 19.99% CO2 + 5.02% N2. Results showed that the first and the second derivatives calculated to define the first inflection points represent exactly the final limit of tangent slopes.

Increasing Sorption Isotherms Accuracy: Weibull Modelling and Linear Regression

Relying on an adequate mathematical approach, two different mathematical procedures can be applied to the huge database produced during gas sorption isotherm experiments in order to obtain accurate data to be used in the industrial practice. To treat data determined from gas sorption isotherms without a careful mathematical support will produce inaccurate results, because all the determinations will be dependent on human decision. The minimum error reported since the first stage of a sorption isotherm determination, which corresponds to volume calibrations of reference and sample cells performed through the use of helium, will produce enormous inaccuracies on sorption isotherm behavior. These inaccurate behaviors may sometimes invalidate any Coalbed Methane recovery and CO2 injection programs. The study consisted on investigating gas sorption isotherm accuracies determined during the first part of the sorption process, which is mainly conducted by monitoring the pressure decline with time, in the reference and the sample cells (when both cells are not in contact), until the stabilization stage is achieved. Three samples from two different coals were selected in order to study their gas sorption behavior, in terms of a clear mathematical approach, when submitted to three different gas compositions, viz. 99.999% methane (CH4); 99.999% carbon dioxide (CO2); and a gas mixture containing 74.99% CH4 + 19.99% CO2 + 5.02% nitrogen (N2). Sorption experiments allow to conclude that the three samples present the same mathematical response during the first part of the sorption process. However, all gas sorption data (adsorption and desorption) collected from reference cell have a better fitting to a Modified Weibull Model, and all gas sorption data (adsorption and desorption) collected from sample cell respond in a trustworthy way to a Linear Regression Model. Confidence bands and prediction intervals (or bands) were also computed.