Analysis of Transient Linear Flow Associated with Hydraulically-Fractured Tight Oil Wells Exhibiting Multi-Phase Flow
Bibliographic record
Abstract
Abstract Hydraulically-fractured vertical and horizontal wells completed in the tight formations typically exhibit long periods of transient linear flow that may last many years or decades. From this transient linear flow period, the linear flow parameter (xf√k) may be extracted. However, changes in effective permeability to the oil phase during production, caused by wellbore pressure falling below the saturation pressure, affect the flow dynamics in tight oil reservoirs and complicate the analysis. The use of methods that assume single-phase flow properties, such as the square-root of time plot, can lead to significant errors in linear flow parameter estimates. In this study, an analytical method is introduced to mathematically correct the slope of the square-root-of-time plot for the effects of multi-phase flow through the use of modified pseudovariables. Although the correction was derived for wells producing at constant flowing pressure during transient linear flow, the method is extended for wells producing at variable rate/flowing pressures. In order to evaluate pseudovariables used in the correction, the saturation-pressure relationship must be known. In this work, an analytical method for evaluating the saturation-pressure relationship is also developed. The results of our new analytical method for linear flow analysis are validated against numerical simulation. The new method yields linear flow parameter estimates that are within 10% of those input into the numerical simulator.
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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 | 0.000 |
| 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) | 0.001 | 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".