Multi-stage Hydraulic Fracturing Design In Horizontal Wells With The Use Of Drill Cuttings
Bibliographic record
Abstract
Abstract Successful multi-stage hydraulic fracturing of horizontal wells requires a clear understanding of the in-situ stress profile. This implies knowledge of rock properties and pore pressure variations throughout the wellbore. These properties can be determined with a good level of certainty when complete data sets are available. In practice, however, data scarcity from horizontal wells is the rule rather than the exception. This has led in most instances to performing multi-stage hydraulic fracturing jobs in symmetric intervals throughout the horizontal well without regard to the optimum locations where hydraulic fractures should be initiated. This study shows how data extracted from drill cuttings collected in a horizontal well can be used for optimizing multi-stage hydraulic fracturing. The cuttings are used in the laboratory for measuring porosity and permeability and for estimating geomechanical properties (e.g. Young Modulus, Poisson's ratio, brittleness index). The data permit generating the in-situ stress profile and other geomechanical parameters in a hydraulic fracturing model. A comparison is made of two cases in a horizontal well of the Western Canada Sedimentary Basin (WCSB), where only a gamma ray log is available: In one case drill cuttings are used for estimating geomechanical properties to select fracture initiation zones; in the other case symmetric fracturing stages are selected without giving consideration to geomechanical properties. The conclusion is reached that the petrophysical and geomechanical knowledge acquired from the study of drill cuttings leads to better rates and improved ultimate recoveries.
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How this classification was reachedexpand
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) | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".