A Simulation Study on Enhanced Gas Recovery from Unconventional Resources (Coal Bed Methane)
Bibliographic record
Abstract
During the past 20 years of research on CBM reserves, it has been found that CBM resources as unconventional are highly potential for natural gas production and used as geological sinks for CO2 storage where ECBMR by CO2 injection evolved as a new strategy of development. It has been proven that affinity of CO2, CH4, and N2 coal is in the ratio of 4:2:1. The main drawback of enhanced coal bed methane recovery by CO2 injection found to be the reduction of coal permeability due to matrix swelling effects and it has been found that, N2 gas has the capacity to reduce the partial pressure of CH4 which helps in quick desorption of CH4 and early production. Apart from this, the production of pure CO2 gas in surface facilities for sequestration is a costly process. The different behavior of CO2 and N2 towards coal making it as a separation medium which cuts the surface separation cost. The produced gas is a mixture of CH4 and N2 and separation units are required to increase the quality of CH4 gas to pipeline specification and recent economic studies says that this cost is less than the cost of CO2 generation. But the question is what exact compositions of flue gas are reliable to obtain the benefit of enhancing gas recovery? Therefore, the focus of this thesis is to develop an approach to evaluate the potential of CBM resources as a sink for CO2, and to assess how effective is the recovery of the CH4 gas trapped in coal beds using flue gas (CO2 and N2) injection. In finding so, first, sensitivity analysis, uncertainty assessment studies have been conducted on 11 hypothetical coal bed simulation models that are developed based on different well completion methods and in each model (M-5 to M-11) flue gas (with normalized compositions CO2 – 0.99, N2- 0.01) is injected. The results derived from the study will help the design of a reliable operating strategy in implementing the CO2 sequestration and enhanced CBM recovery using flue gas injection in deep coal zones in Western Canadian Sedimentary Basin, Canada and elsewhere.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.003 | 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 teacher head, 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".