Identification of Activated Fracture Networks Using Microseismic Spatial Anomalies, b-values, and Magnitude Analyses in Horn River Basin
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 analyzed microseismic spatial and temporal distribution, magnitudes, b-values and treatment data to interpret and explain the observed anomalies in microseismic events recorded during exploitation of Shale Gas reservoirs in the Horn River Basin of Canada. We estimated the directional diffusivity to define the microseismicity front curve for each stage of hydraulic fracturing. Based on our definition of front curves, we managed to separate most of the microseismic events data that are related to natural fracture activation from hydraulic fracturing events. We analyzed the b-values for microseismic events of each stage before and after separating fracture activation microseismic events from original data and created a map of b-values in the study area. This allowed us to locate activated fractures mostly in the northeastern part of the study well pad. The b- value map agrees with our assumption of activated fracture locations and high ratio of seismic activities. Suggested fracture locations agree with anomalous events' density, energy distribution and treatment data. We are defining and proposing intermediate b-values for calculation of the stimulated reservoir volume (SRV) in areas with both hydraulically fractured events and events related to natural fracture network activation in those instances where the separation of events based on their origin is not viable.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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