Application of In-House Prepared Nanoparticles as Filtration Control Additive to Reduce Formation Damage
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Bibliographic record
Abstract
Abstract Nanoparticles (NPs) are currently being studied as a drilling fluid additives especially for application in very low-permeability formations such as shales. Application for conventional permeable rocks is still a subject of discussion. In this work, successful application of in-house prepared iron-based nanoparticles (NP1) and calcium-based nanoparticles (NP2) to reduce filtration loss in conventional permeable media has been experimentally quantified for oil-based mud (OBM) utilizing the high-pressure high-temperature (HPHT) filter press at 500 psi and 250°F. Ceramic discs were used as the filtration medium in this application to test the performance of the NPs and glide graphite as a conventional lost circulation material (LCM) for porous media. These experiments were carried out in the presence of graphite at low and high concentrations. Filtration reduction trends were observed and a reduction up to 76% was achieved. API filter press was also used to investigate the behavior of NPs and graphite under low pressure and temperature conditions (LPLT). NP1 and NP2 at the two graphite concentrations showed a reduction up to 100%. NP1 gave higher reduction especially at low concentrations under HPHT conditions, while NP2 yielded significant reduction at high concentration under HPHT. These trends were reversed under LPLT, giving a new insight on NPs performance under different pressure and temperature conditions. At HPHT and LPLT, the effect of graphite as a filtrate reduction agent is less significant as the NPs concentration increases. High graphite level had a positive effect on filtration reduction in combination with NP1 at HPHT and LPLT. This was not the case for the blends containing NP2 at HPHT. The effect of NPs and graphite was tested individually showing a different performance compared to the combination of them. Impact of NPs and graphite on rheology was also quantified allowing identification of the more sensitive parameters in the blends. It is concluded from this study that blends containing NPs and graphite can be successfully implemented in OBM to minimize formation damage in porous media.
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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 | 0.001 |
| 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 it