Characterizing Moisture and Gas Content of Coal by Low-Field NMR
Bibliographic record
Abstract
Abstract Coalbed Methane (CBM) shows great potential to be an important energy source. One key factor for the successful development of CBM processes is to characterize coal on its moisture and gas content. Usually, the moisture and gas content of coal are determined from laboratory analysis. Low-field nuclear magnetic resonance (NMR) is a relatively new technique used in logging and in the analysis of fluids contained in reservoir rocks. This paper investigates the potential for coal characterization by low-field NMR. Low-field NMR detects hydrogen-bearing molecules and, in reservoir rock samples, distinguishes between ‘free’ bulk fluid and ‘bound’ surface fluid. Coal contains free water in the cleats as well as moisture that forms an integral part of the coal structure. Methane gas is a light hydrocarbon gas and coal contains free methane gas in fractures and adsorbed methane in internal surfaces. NMR characterization of moisture and adsorbed gas in coal and implications for moisture, adsorption isotherm and gas content measurements are explored. Experiments of moisture-free coal, moist coal and coal/water mixtures indicated drastically different spectra. From these spectra, free and bound water could be estimated using a methodology that is currently applied in clay-rich formations. In this paper, two sets of data are presented. First, measurements at ambient conditions provided a reference to other conventional moisture and cutoff data. Second, a high-pressure cell for the measurement of adsorbed coal was used and comparisons were made. Coal samples in the form of powder and chunk were used. The paper focuses on the methods and results to date. Introduction Coalbed methane (CBM) has evolved into a commercially profitable source of natural gas. Canada has vast resources of coal and it has been estimated that the total in-place reserves are 36 ? 1012 m3. Over 60% of Canada's CBM assets are in Alberta(1). Coalbed methane has the potential of contributing a significant portion of Canadian natural gas production in the near future. One key factor for the successful development of CBM processes is to characterize coal on its moisture and gas content. Usually, the moisture of coal is determined from coal proximate analysis and the gas content of coal is determined by the desorption measurement in the laboratory. Low-field NMR is a relatively new technique used in logging and in the analysis of fluids contained in reservoir rocks. Nuclear magnetic resonance occurs when the nuclei of certain atoms (i.e. hydrogen proton) are immersed in a static magnetic field and exposed to a second oscillating magnetic field(2). NMR provides a non-destructive analytical method of detecting hydrocarbons in reservoirs(3) and characterizing the hydrocarbon gas(4). Generally, the NMR spectrum can provide three types of information: the quantities of the fluids in the rock, the mobility (viscosity) of these fluids and information about the pores that contain these fluids. As a source rock and at the same time a reservoir rock, coal contains large amounts of water and methane. Water exists as free water in the cleats as well as the moisture that forms an integral part of the coal structure.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".