Application of Relative Location Techniques to Induced Microseismicity from Hydraulic Fracturing
Bibliographic record
Abstract
Abstract Microseismic monitoring is routinely used for imaging the fracture network induced by hydrofracture treatments. One of the principal sources of uncertainties in the location of hypocentres is the velocity structure used in the location algorithm, which in most cases is approximated by layered models from sonic logs or estimated from perforation shot arrival times. Hypocentral uncertainties can be reduced by an order of magnitude, and the number of events located significantly increased, by using relative location methods that reduce the location volume to a small region around the seismic source. Relative location methods are valid provided that the separation between the processed events is small compared to the ray-path lengths between source and receiver. The location is obtained through the inversion of differential travel times with respect to one chosen master event, minimizing the relative moveout residual. In this study, a new step-wise master-event relative-moveout location is applied to microseismic events induced during hydrofracture treatment. The unique step-wise addition to the technique overcomes the limitations of separation distance by constructing a lattice of master events formed by all available good quality events that are located with a classic location algorithms. The minimization search is extended to the complete fracture volume as defined by the master events, converging to a solution that minimizes the relative moveout residual with respect to any of the available masters within the distance range. The use of arrival time differences with respect to a master event allows the location of events with P- and/or S-wave arrivals. Using the step-wise approach, the increased resolution in seismic location achieved by relative location methods is propagated to the complete set of events in a hydrofracture treatment. Furthermore, the method allows a significantly higher number of events to be located as only one phase (P or S wave) need be identified, assuming the events are in the vicinity of a master event with high quality arrivals. We provide results from an example data set to illustrate the higher resolution and increase in number of located events that can be obtained through the application of the stepwise relative-moveout location algorithm.
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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 | 0.001 | 0.001 |
| 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".