Optimized Natural Gas From Coal Stimulations in the Western Canadian Sedimentary Basin, Part I: Database Collection
Bibliographic record
Abstract
Abstract The Western Canadian sedimentary basin (WCSB) contains numerous coal seams of various ranks and petrophysical characteristics. The process presented in this paper correlates the area of interest with the rich historic volume of data that is available. Production, detailed stimulation data, engineering designs, petrophysical analysis, fluid analysis and sophisticated computer work come together in the application to produce a statistical approach to initial stimulation designs. The final design evolves with respect to the characteristics of the well of interest. Designing stimulations for coal beds is complicated based on the small amount of unshared and unformatted data that exists in any one place. The significant accomplishment of this paper is rooted in obtaining a large amount of useful data from the many small, incomplete and confusing data sources. Although the data has always existed in various formats and places, the completions or wells rarely reference the target of Natural Gas from Coal (NGC). Cooperation by industry partners enhances the efforts to combine information and improve correlations of well production responses to stimulations. This paper presents the first step in developing a comprehensive design philosophy and database collection to assist is optimizing future NGC wells and plays. Introduction The use of offset treatment data is a valuable tool in the design of fracture stimulation treatments when used properly. However, "just doing what was done before" is not necessarily providing the best design. Offset data is only one aspect of an engineer's repertoire that should also include a thorough knowledge of the reservoir, the client's expectations and goals as well as a solid background of experience. However, designing fracture stimulation treatments for coal seams is a relatively new process. Complicating this learning curve is the shortage of data available to industry due mainly to the tight-hole status of many NGC projects. Everyone wants to benefit from the learning curves of others, but are sure to carefully guard their own experience. However, this state of secrecy is not unwarranted since relatively large tracts of land are waiting to be purchased and developed. Based on the extended times required to show economical production, tighthole status is requested for as long as 5 years to ensure as much secrecy as possible while developing the plays and positioning for future land sales. Through sophisticated data mining techniques, an extensive NGC database can be pieced together using internal and industry data. This data set includes coal reservoir data, completions and production impact results across a wide geographical and geological area encompassing all the major coal plays in the WCSB. The use of this data, while respecting our tight-hole information, is a valuable tool in the design of effective NGC stimulations. Outline of Project Although gas bearing coal bed deposits are pervasive throughout Western Canada, the variation in reservoir quality is significant. To effectively stimulate various coal seams, a thorough understanding of the particular coal is required. Through a detailed analysis of the available data, trends of effective stimulation designs can be developed.
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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 | 0.001 | 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 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".