Case Study: Production Data and Pressure Transient Analysis of Horseshoe Canyon CBM Wells
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract The Horseshoe Canyon (HSC) CBM play of the Western Canadian Sedimentary Basin is unique to low-rank coal reservoirs because of lack of water production; the production characteristics are qualitatively similar to conventional low-pressure dry gas reservoirs. However, the complex geologic history of the coals and non-coal interbeds has imparted strong vertical and lateral heterogeneities that make the play difficult to characterize using conventional methods. For example, in a typical HSC well, there are often > 10 seams to complete, which may exhibit strong contrasts in initial pressure, gas content, thickness and permeability. Further, the lateral continuities of the individual seams vary, and are often not correlatable from well-to-well. Recently, advances in production data analysis (PDA) methodologies have been made for CBM wells; techniques developed for tight gas, and conventional oil and gas reservoirs have been adapted by incorporating some CBM reservoir properties. For example, the popular flowing material balance (FMB) technique, as well as production type-curve and pressure transient analysis (PTA) have been modified to include relatively simple CBM reservoir behavior (ex. equilibrium desorption). These methods, however, are primarily restricted to the analysis of single-layer reservoirs; significant errors in estimates of original-gas-in-place (OGIP) and other reservoir properties may occur if strong contrasts exist from layer-to-layer. In this work, multi-layer analysis tools are discussed, including analytical simulators that are used to history-match layer-allocated rates and pressures, and layer-specific FMB, which is used as a PDA method for individual layers. A study was undertaken to establish the applicability of advanced PDA methods to the quantitative assessment of HSC reserves. Single-layer and multi-layer analysis tools were first tested against artificial data created with a numerical simulator. Next, single-layer-equivalent analysis was performed on > 40 real wells using type-curve, FMB, and analytical simulation. Many of the wells exhibit an early "cleanup" period with inclining or flat production, precluding analysis of transient flow data. Finally, a more rigorous multi-layer analysis was performed on a subset of wells where spinner surveys, and individual-seam pressure buildup data, collected at several points in time during the producing life of the well, were available. Analysis of this subset of wells included PTA of the individual seams, individual seam material balance, and multi-layer (up to 6) analytical simulation history-matching of total commingled flow rates, individual coal zone rates estimated from spinner surveys, and shut-in pressures. The resulting reservoir property estimates (ex. total OGIP) were then compared to the single-layer-equivalent analysis; the single-layer-equivalent analysis appears to yield conservative estimates of OGIP. Future work will include continued comparisons of multi-layer vs. single-layer PDA, development of new PDA methods for analyzing multi-layer reservoirs, investigation of additional constraints on permeability and other reservoir properties that can be used in multi-layer history-matching process, and time-lapse PTA work to quantify changes in layer permeability and skin during depletion.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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