Estimated Ultimate Recovery (EUR) as a Function of Production Practices in the Haynesville Shale
Bibliographic record
Abstract
Abstract Recent developments in well completion technologies have transformed the unconventional reservoir systems into economically feasible reservoirs. However, the uncertainty associated with production forecasts and non-uniqueness related with well/reservoir parameter estimation, are the main issues in future development of these reservoirs. In addition, recent operational methods such as restricting rates by decreasing the choke size add up to the uncertainty in production forecasts. This work attempts to investigate the effect of production practices on ultimate recovery. It is observed that wells producing in the Haynesville shale gas play exhibit severe productivity loss throughout their producing life. Production practices such as controlling the drawdown or restricting rates by decreasing the choke size are employed by several operators to deal with the severe productivity loss. In this work our main objective is to investigate the issues (such as stress dependent permeability, proppant embedment, operational problems, etc.) contributing to decreasing well productivity over time. In particular, from modeling standpoint, we focus on stress-dependent permeability as a mechanism, which affects well performance over time. Using a horizontal well with multiple fractures numerical simulation model coupled with geomechanics, we generate synthetic simulation cases including several drawdown scenarios. It is shown that high drawdown cases result in higher effective stress fields around the well and fracture system. We therefore infer that higher effective stress fields result in lower well productivity over time. Based on this hypothesis and diagnostics of field data, we model two different scenarios (i.e., high drawdown and low drawdown cases) for a horizontal well with multiple fractures using two different permeability decay functions and same well/formation model parameters. Our modelling results indicate that low drawdown case yields higher recovery suggesting that rate restriction could be a mitigating factor in decreasing well productivity over time.
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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 | 0.000 | 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) | 0.000 | 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 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".