Reinterpretation of Flow Patterns During DFITs Based on Dynamic Fracture Geometry, Leakoff and Afterflow
Bibliographic record
Abstract
Abstract The goal of this study is to explain the full spectrum of flow patterns observed before and after closure during diagnostic fracture injection tests (DFITs) by considering the dynamic nature of fracture geometry, variable leakoff rate and afterflow volume caused by wellbore storage. A fit-for-purpose simulation model is used to simulate DFITs and generate pressure responses in low-permeability (tight) reservoirs. The cohesive zone model in Abaqus® is used to simulate hydraulic fracture propagation and closure. A customized leakoff model incorporated into the software accounts for variable leakoff rate as a function of reservoir properties, fracture pressure, fracture surface area and exposure time. The afterflow is modeled by including a wellbore volume and accounting for wellbore storage. Results are compared to field data to explain the full spectrum of flow patterns and fracture dynamics observed in pressure transient analysis of DFITs. The overall falloff period is interpreted, using PTA diagnostic plots, for relative magnitudes of afterflow, leakoff rate and fluid flow in the formation. Initially, afterflow is high, resulting in fracture expansion, which is characterized by a unit slope on the Bourdet-derivative plot. The afterflow does not necessarily end after the unit slope terminates; the end of fracture expansion is signaled by a characteristic hump on the derivative plot. During fracture expansion, the afterflow decreases and the leakoff rate increases due to the larger fracture area. When the leakoff rate dominates over afterflow, fracture closure mechanics can be conceptualized as a moving hinge-closure, where the fracture volume reduces, and fracture tip extension occurs as fluid is pushed to the tip of fracture (indicated by fluctuations in the derivative). The transition from afterflow to leakoff dominance and the moving hinge-closure manifest as a semi-horizontal trend on the Bourdet-derivative. Subsequently, a progressive fracture closure occurs gradually along the fracture, identified by an increasing trend or a sharp decline on the primary pressure derivative, depending on the conductivity. Different estimates of closure pressure will be obtained early and late in this process. The pressure behavior immediately after full closure is observed to be affected by the residual leakoff and the continuing afterflow. Once all of these fracture, wellbore and leakoff processes are abated, the reservoir response is observed. This study provides a clear understanding of the different mechanisms affecting pressure behavior during DFITs for tight reservoirs in order to arrive at more reliable estimates of fracturing parameters and reservoir properties. As an example, mechanisms leading to false before- and after-closure radial flow identification are explained.
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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 | 0.001 | 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".