An Unconventional Rate Decline Approach for Tight and Fracture-Dominated Gas Wells
Bibliographic record
Abstract
Abstract Traditional decline methods such as Arps’ rate-time relations and their variations do not work for super-tight or shale gas wells where fracture flow is dominant. Most of the production data from these wells exhibit fracture-dominated flow regimes and rarely reach late-time-flow regimes even over several years of production. Without the presence of pseudoradial and boundary-dominated flows (BDF), neither matrix permeability nor drainage area can be established. This indicates that matrix contribution is negligible compared to fracture contribution and the expected ultimate recovery (EUR) can not be based on a traditional concept of drainage area. An alternative approach is proposed to estimate EUR from wells where fracture flow is dominant and matrix contribution is negligible. To support these fracture flows, the connected fracture density of the fractured area must increase over time. This increase is possible due to local stress changes under fracture depletion. Pressure depletion within fracture networks would reactivate the existing faults or fractures, which may breach the hydraulic integrity of the shale that seals these features. If these faults or fractures are reactivated, their permeabilities will increase, facilitating enhanced fluid migration. For fracture flows at a constant flowing bottomhole pressure, a log-log plot of rate over cumulative production vs. time will yield a straight line with a unity slope regardless of fracture types. In practice, a slope of higher than unity is normally observed due to actual field operations, data approximation and flow regime changes. A rate-time or cumulative production-time relationship can be established based on the intercept and slope values of this log-log plot and initial gas rate. Field examples from several super-tight and shale gas plays for both dry and high liquids gas production were used to test the new model. All display the predicted straight line trend, with its slope and intercept related to the type of fractured flow regimes. In other words, a certain fractured flow regime or a combination of flow types that dominate a given area or play due to its reservoir rock characteristics and/or fracture stimulation practices all produce a narrow range of intercepts and slopes. An individual well performance or EUR can be derived based on this range if the best-three-month average or the initial production rate of the well is already known or estimated. The results show that this alternative approach is easier to use, gives a reliable EUR, and can be used to replace the traditional decline methods for unconventional reservoirs. The new approach is also able to provide statistical methods to analyze production forecasts of resource plays and to establish a range of results of these forecasts, including probability distributions of reserves in terms of P90 (lower side) to P10 (higher side).
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".