Wellbore Strengthening in Sandstones by Means of Nanoparticle-Based Drilling Fluids
Bibliographic record
Abstract
Abstract Drilling operations of both conventional and unconventional oil and gas accumulations are becoming more challenging especially in deep-water operations. Due to the narrow mud weight window in offshore wells, a proper wellbore stability analysis is required for a cost-effective execution. Wellbore strengthening is an approach used to increase the fracture pressure of the rock, widen the mud window and consequently enhance the well integrity and mitigate mud losses. This paper demonstrates the feasibility of wellbore strengthening in permeable formations using oil-based mud (OBM) containing in-house prepared nanoparticles (NPs) combined with graphite. A significant increase in the fracture pressure was achieved and the predominant wellbore strengthening mechanism was identified. Fracture pressure increase was quantified by carrying out hydraulic fracturing tests on 5 3/4″×9″ Roubidoux sandstone cores. A 9/16″ wellbore was drilled, cased and cemented to simulate well conditions. Overburden and confining pressure were applied on the cores while testing to simulate a normal-faulting regime. Two injection cycles were applied allowing 10 minutes of fracture healing between the cycles. The fracture pressure was increased by 65% when calcium-based NPs (NP2) blends were used, whereas it increased by 39% in the presence of iron-based NPs (NP1). Optimum NPs concentrations were established after a comprehensive experimental screening. A strong relationship between wellbore strengthening and mud filtration at high-pressure high-temperature (HPHT) using a filter press on ceramic discs was found. Optical microscopy, scanning electron microscope (SEM) and energy dispersive X-ray spectroscopy (EDX) analyses were conducted on the hydraulically fractured cores. The fractures were seen to be completely sealed from tip to wellbore. Therefore, tip isolation by the development of an immobile mass was identified as the predominant wellbore strengthening mechanism. A 40 micron-seal containing homogeneously dispersed NPs and graphite was observed. In addition, a 300 micron-filter cake was developed around the wellbore also containing homogeneously dispersed NPs.
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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".