Large-Scale Laboratory Investigation of the Effects of Proppant and Fracturing-Fluid Properties on Transport
Bibliographic record
Abstract
Abstract The primary function of fracturing fluids is to provide the means and media for the transport and placement of a conductive proppant pack in the created fracture such that resident hydrocarbons may be more easily produced. In recent years significant effort and expense has been invested to develop an ideal fracturing fluid system. Such efforts have been often been akin to the proverbial dog chasing his tail, rather than on the addressing the engineering objective to place a conductive propped fracture. Development focus has been primarily on optimization of fluid rheological stability to get the treatment pumped and secondarily to mitigating any damage caused by new fluid system. Post-frac production analysis frequently demonstrates less than anticipated fracture area, suggesting excessive proppant-pack damage or that the proppant was not placed in designated areal location due to inadequate proppant transport. Recent testing was conducted in a large-scale slot apparatus at the Well Construction Technology Center in Oklahoma to evaluate the relative effects of proppant slurry component characteristics and the proppant transport capability. The effects of various fluid specific gravities, fluid viscosities, proppant specific gravities, proppant sizes, slurry flow rates, and slot widths were investigated. Testing included fluids from slickwater to gelled, weighted brines, proppants from 40/70 Ottawa sand to 14/30 ultra-lightweight proppants, pump rates from 0.1 to 1.0 bbl/ft/min, and slot widths from 0.25 to 0.5". Evaluation of the proppant transport testing data and the comparative abilities of current fracturing slurry system technologies to achieve placement of a productive propped fracture will be discussed.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".