Production-Data Analysis of Single-Phase (Gas) Coalbed-Methane Wells
Bibliographic record
Abstract
Summary Coalbed-methane (CBM) reservoirs commonly exhibit two-phase-flow (gas plus water) characteristics; however, commercial CBM production is possible from single-phase (gas) coal reservoirs, as demonstrated by the recent development of the Horseshoe Canyon coals of western Canada. Commercial single-phase CBM production also occurs in some areas of the low-productivity Fruitland Coal, south-southwest of the high-productivity Fruitland Coal Fairway in the San Juan basin, and in other CBM-producing basins of the continental United States. Production data of single-phase coal reservoirs may be analyzed with techniques commonly applied to conventional reservoirs. Complicating application, however, is the unique nature of CBM reservoirs; coal gas-storage and -transport mechanisms differ substantially from conventional reservoirs. Single-phase CBM reservoirs may also display complex reservoir behavior such as multilayer characteristics, dual-porosity effects, and permeability anisotropy. The current work illustrates how single-well production-data-analysis (PDA) techniques, such as type curve, flowing material balance (FMB), and pressure-transient (PT) analysis, may be altered to analyze single-phase CBM wells. Examples of how reservoir inputs to the PDA techniques and subsequent calculations are modified to account for CBM-reservoir behavior are given. This paper demonstrates, by simulated and field examples, that reasonable reservoir and stimulation estimates can be obtained from PDA of CBM reservoirs only if appropriate reservoir inputs (i.e., desorption compressibility, fracture porosity) are used in the analysis. As the field examples demonstrate, type-curve, FMB, and PT analysis methods for PDA are not used in isolation for reservoir-property estimation, but rather as a starting point for single-well and multiwell reservoir simulation, which is then used to history match and forecast CBM-well production (e.g., for reserves assignment). CBM reservoirs have the potential for permeability anisotropy because of their naturally fractured nature, which may complicate PDA. To study the effects of permeability anisotropy upon production, a 2D, single-phase, numerical CBM-reservoir simulator was constructed to simulate single-well production assuming various permeability-anisotropy ratios. Only large permeability ratios (>16:1) appear to have a significant effect upon single-well production characteristics. Multilayer reservoir characteristics may also be observed with CBM reservoirs because of vertical heterogeneity, or in cases where the coals are commingled with conventional (sandstone) reservoirs. In these cases, the type-curve, FMB, and PT analysis techniques are difficult to apply with confidence. Methods and tools for analyzing multilayer CBM (plus sand) reservoirs are presented. Using simulated and field examples, it is demonstrated that unique reservoir properties may be assigned to individual layers from commingled (multilayer) production in the simple two-layer case.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.002 | 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".