Measurement of the normal/tangential fracture compliance ratio (<i>Z</i><sub><i>N</i></sub>/<i>Z</i><sub><i>T</i></sub>) during hydraulic fracture stimulation using S‐wave splitting data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
ABSTRACT We develop a method to invert S‐wave splitting (SWS) observations, measured on microseismic event data, for the ratio of normal to tangential compliance ( Z N / Z T ) of sets of aligned fractures. We demonstrate this method by inverting for Z N / Z T using SWS measurements made during hydraulic fracture stimulation of the Cotton Valley tight gas reservoir, Texas. When the full SWS data set is inverted, we find that Z N / Z T = 0.74 ± 0.04. Windowing the data by time, we were able to observe variations in Z N / Z T as the fracture stimulation progresses. Most notably, we observe an increase in Z N / Z T contemporaneous with proppant injection. Rock physics models and laboratory observations have shown that Z N / Z T can be sensitive to (1) the stiffness of the fluid filling the fracture, (2) the extent to which this fluid can flow in and out of the fracture during the passage of a seismic wave and (3) the internal architecture of the fracture, including the roughness of the fracture surfaces, the number and size of any asperities and the presence of material filling the fracture. These factors have direct implications for modelling the fluid‐flow properties of fractures. Consequently, the ability to image Z N / Z T using SWS will provide useful information about fractured rocks and allow additional constraints to be placed on reservoir behaviour.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 it