Laboratory Testing and Numerical Modelling of Fracture Propagation from Deviated Wells in Poorly Consolidated Formations
Bibliographic record
Abstract
Abstract This paper presents the results of an integrated laboratory and numerical modelling study on the effect of wellbore deviation and wellbore azimuth on fracture propagation in poorly consolidated sandstone formations. The goal of this project was to develop an understanding of how fractures would transition from single planar fractures to non-planar transverse fractures for fields in the deep-water Gulf of Mexico. The foundation of this work was over 40 fracturing laboratory tests to measure fracture propagation geometries for a range of well deviations, differential horizontal stresses and rock strength. The samples tested were from three outcrops with unconfined compressive strength (UCS) values ranging from 300 – 1000 psi. For boreholes having low deviation angles and small differential stresses a vertical single planar fracture was created, aligned with the wellbore, as expected. As the well trajectory and stress contrast increased the fractures became more complex, with transverse turning fractures no-longer aligned with the wellbore. These laboratory results were used to develop and calibrate a new fully-3D finite element model that predicts non-planar fracture growth. The model matches the details of the laboratory tests, including the transition from planar vertical to nonplanar transverse fractures as the well deviation, azimuth and stress differentials increase. After initial model development and calibration was complete a model of a complex case was run before showing any experimental results to the modellers. The model successfully predicted the transverse non-planar results found in the laboratory; this gave us increased confidence in the model as a predictive tool. This work has now been applied with excellent success to four deepwater fields. We have recommended changes in maximum well deviations, performed post-job analyses on wells that had high deviations, and have increased our understanding of the impact of layered formations on fracture growth in these fields.
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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".