Coal bed methane gas in-place estimation for the North-Western region of Zimbabwe
Why this work is in the frame
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Bibliographic record
Abstract
Coal Bed Methane (CBM) is natural gas occurring in coal seams. It can be used for domestic (heating and cooking) and industrial purposes, electricity generation, transportation (as compressed natural gas or liquefied natural gas), and in boilers supporting mining operations. It is established that Zimbabwe has CBM in the North-Western region. At the time of this study, only one organization (Industrial Development Corporation) has reported an Original Gas in Place (OGIP) estimate for the region as 765 Bm3. In this study we use Monte Carlo Simulation (MCS) to estimate the range of OGIP values for the region. MCS is a widely used probabilistic method, preferred over deterministic methods in which only best-estimate values of parameters are used to predict a single OGIP value. This single OGIP value may be either positively (overestimated) or negatively skewed (underestimated). However, the probabilistic approach using MCS accounts for the uncertainty in values of parameters. This is done by incorporating appropriate range and probability distributions (e.g. triangular, normal, uniform, etc.) of input parameters (e.g. target area, formation thickness, coal bulk density, and adsorbed methane content), and repeating calculations to generate a cumulative distribution curve for the OGIP. The generated curve provides statistical confidence levels represented as probability distributions, i.e. P10, P50, and P90 represents low, mid, and high probability estimates, respectively. Our results show that P10, P50, and P90 values for the North-Western region OGIP are 5699 Bm3, 2347 Bm3, and 706 Bm3, respectively. The Resource Density (RD) estimation is found to range from 0.015 Bm3/km2 to 0.113 Bm3/km2 over the geographic area. This range is comparable to Alberta plains shallow and deep basins in Canada which boosts a higher level of confidence for CBM potential in Zimbabwe. The results are encouraging for further exploration and planning of exploitation of CBM in Zimbabwe.
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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) | 0.000 | 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 it