Production Data Analysis of Fractured and Horizontal CBM Wells
Bibliographic record
Abstract
Abstract In recent work, the authors (Clarkson et al 2008a; Clarkson et al 2007; Jordan et al 2006) demonstrated how modern production data analysis (PDA) methods, such as flowing material balance (FMB) and production type-curves, may be adapted to account for the unique reservoir characteristics of coalbed methane (CBM) reservoirs through the appropriate use of material balance and time transforms. Reservoir characteristics related to storage and fluid flow that were addressed included: adsorbed and free-gas storage; single-phase flow of water above desorption pressure (undersaturated coals); 2-phase flow of gas and water below desorption pressure (saturated coals); non-static absolute permeability during depletion; and multi-layer behavior. Example (field) applications of the new PDA methods were limited to vertical wells that were either openhole completed, or slightly stimulated with hydraulic fracturing methods. In this work, new workflows and analytical approaches are provided for analyzing single- and multi-phase flow of CBM from vertical, hydraulically-fractured wells and horizontal wells. The workflow for single-phase CBM wells, which parallels that used in modern pressure transient analysis (well-testing), includes identification and analysis of flow regimes, followed by (model) type-curve matching and analytical (or numerical) modeling. Pseudotime is modified to account for instantaneous desorption. The analysis and methodology for 2-phase flow reservoirs is more complex, requiring additional modification of the pseudovariables to account for changes in effective permeability. A new workflow is introduced for 2-phase CBM wells that includes the transformation of the well production and flowing pressure data into dimensionless type-curve and flowing material balance coordinates using outputs from the simulator used to history-match the production data. Both simulated and field cases are analyzed to illustrate the new procedures and analytical techniques. The primary contribution of the current work is the demonstration that modern production analysis methods, modified for CBM reservoir behavior and combined with analytical (or numerical) modeling, can be used to extract quantitative reservoir information from CBM reservoirs which exhibit a wide-range in production characteristics, and completed in a variety of styles. The methods are expected to be used as a pre-cursor to or in parallel with reservoir simulation, to assist with CBM development decisions.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| 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".