Questioning the Existence of Hydraulic Fracturing-Induced LPLD Events in a Barnett Shale, Texas, Microseismic Dataset
Bibliographic record
Abstract
Summary Recent studies have identified and characterized a type of seismic event, known as an LPLD event, which have been detected in microseismic data sets acquired during hydraulic fracturing operations (e.g. Das and Zoback, 2011 ; 2013a ; 2013b ; Mitchell et al., 2013 ; Kwietniak, 2015 ). These events have been interpreted to be manifestations of slow-slip along preexisting fractures which are presumed to either be misaligned with respect to the current day principal stress directions or have high clay content ( Das & Zoback, 2013a ; 2013b ). A study by Caffagni et al. (2015) advise that care must be undertaken when analyzing and interpreting such events as regional earthquakes could be misinterpreted as LPLD events in vertical downhole seismic monitoring array data sets. We here show that signals associated in time with such LPLD events could be observed on many Earthscope USArray stations, even at distances up to 350 km from the injection well. The spatial coverage of the USArray enabled all of the LPLD events to be relocated in the North Texas-Oklahoma region, outside of the stimulated reservoir volume. We conclude that these LPLD events are not directly related to the hydraulic fracture stimulation process or the induced reservoir deformation process.
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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 | 0.002 |
| 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 | 0.001 |
| 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".