Original-Gas-In-Place Sensitivity Analysis of the Manville Group in the Western Canada Sedimentary Basin
Bibliographic record
Abstract
Abstract A sensitivity analysis of the Original-Gas-In-Place (OGIP) in the Manville group of the Western Canada Sedimentary Basin (WCSB) is carried out by using Star Plots in order to determine (1) what parameters have that largest impact on the gas volume estimation, (2) what is the error in the volume estimation, and (3) what is percent error in the choices of effective porosity and Archie’s exponents m and n on water saturation. The Manville group in the WCSB contains a very large resource of natural gas that was quantified to be in the order of 1500 tcf (Masters, 1984). The gas in place calculations are based on the volumetric equation that takes into account area (A), net pay (h), effective porosity (PHI), true resistivity of the formation (Rt), water resistivity (Rw), porosity exponents "m" and "n," and initial pressure (Pi). The sensitivity analysis is carried out by choosing possible errors around each input parameter. This permits to concentrate evaluation efforts on the tools and data that have the largest effect on the calculated values of OGIP. It is concluded that intuition does not necessarily distinguish the data with the largest impact on the calculations. For example, the water resistivity (Rw) is the parameter with the smallest impact on OGIP estimations presented in this study. Based on results, three new polynomial correlations are developed to represent the effect of porosity (PHI) and the m and n exponents on water saturation estimations for the Manville Group. These correlations will improve significantly the way in which uncertainty and risk associated with reserves estimation are quantified.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".