Investigation of Proppant Shear Behavior Along Fracture/Fault Lines; A Gouge Analogy for Fracture Stability and Earthquake Potential
Bibliographic record
Abstract
ABSTRACT: During Hydraulic fracturing of unconventional reservoirs, proppants keep fractures open after fracturing and thus increase reservoir deliverability. Typically fracture conductivity is used to quantify the efficiency of hydraulic fractures. The efficiency is highly dependent on the proppant placement during fracturing and proppant rearrangement/crushing when the fracture begins to close. This work introduces another criterion for evaluating the efficiency of the hydraulic fracturing operation. This is based on the stability of the fracture and its potential to induce seismic activity. Using the three major types of proppants (resin, ceramic, sand) used in hydraulic fracturing. We investigate the proppant shear behavior of these proppants after fracture closure using a Large Sample Rig to perform triaxial shear experiments. The experiments were at ambient temperature and constant confining pressure of 50Mpa analog to a typical minimum horizontal stress. The fracture geometry is pre-defined through a saw-cut on the Eagleford core sample. The proppants are placed at a gouge thickness of about 2mm to represent the fracture width. The resulting stick-slip during the proppant shearing is the analog for earthquake potential. The energy released during shearing of these proppants is up-scaled to field level at varying shear active fracture lengths. This is to determine the magnitude of a likely earthquake should this mechanism occur in the subsurface. We also tested the replicability/reactivating nature of these events by slide-hold-slide tests during the shearing experiments. The microscopic deformation of proppants and indentation on the Eagle-ford cores were observed. The energy released depends on the minimum horizontal stress, shear active fracture length, slip rate, and proppant type. 1. INTRODUCTION Several works of literature have reported the occurrence of earthquakes around hydraulic fracturing active areas like Texas and Oklahoma, Alberta (Hui et al. 2020, Julie E. et al. 2019, Kumar et al. 2019). The common notion so far is that these seismic events are largely due to the injection of fracturing fluids within pre-existing fault lines, and the disposal of wastewater. Julie E. et al. (2019) reported about 333 wells with hydraulic fracturing-related seismicity after reviewing the "Frac Notice-Seismicity Match Catalog" for a three-year period. They identified 960 earthquakes with magnitude ≥ 2 in the catalog and about 6% of these earthquakes ≥ 3. The largest earthquake associated with a well completion had a magnitude of 3.9. The catalog is based on well seismicity matches using earthquakes that occurred within 5 Km of a well and between the initiation of hydraulically fracturing a well and seven days after the commencement of well flow back as a criterion. There are common observations of wellbore damage either by collapse or shearing especially along horizontal well laterals as a result of formation compaction, subsidence, or movement. This introduces the probability of shearing along already closed hydraulic fractures or pre-existing fault lines. The subsequent release in energy from this mechanism could be a potential contributor to the magnitude of earthquakes resulting from hydraulic fracturing and its related operations.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".