Bibliographic record
Abstract
Technology Focus Drilling and completion (D&C) fluids are used in every well and are critical to drilling efficiency and reservoir productivity. Technological advances of D&C fluids are more evolutionary than revolutionary. Over time, these evolutionary changes have accumulated such that the quantity of knowledge and available technologies is extensive. This is where we are today for all fluids-related technologies. Clearly, the industry has more scientific knowledge about how fluids behave, and the number of unique options available to drill or complete a particular well has never been greater. Recent advancements of note are nonaqueous fluids (the rheology of which is affected less by temperature), novel weighting agents, increasingly complex drill-in fluids, cleanup options for openhole completions, and significantly improved fluids-processing equipment. The difficult part is sorting out what to use and when. Keep in mind that many of these new technologies have increasingly narrow applications. As engineers, our goal should be to select the most effective technology for a particular task, not necessarily the most recently developed "new technology." Many fluids with a history of use in a given area or for a particular application are used for good reason; they work well! But the world is changing. D&C costs are increasing at rates not seen for more than 25 years, and the kinds of wells being drilled are changing. So it is critical to re-examine each application continually and strive to choose fluids that minimize problems and yield a better-quality well. I frequently am surprised when people do not understand the fundamental information about fluids that is documented in classic SPE technical papers. Only by understanding these fundamentals can a person make good decisions about which fluid or technology to use in a given application. For those of you who are new to the industry and are interested in D&C fluids, I recommend that you take time to read classic fluids papers and keep up with at least the topics of currently published papers. While they have not been updated recently, I recommend and often cite information from the SPE Reprint Series, especially No. 44 Drilling Fluids and No. 22 Drilling. Please take time to read the paper summaries that follow as well as the papers listed below; you will learn something. Drilling and Completion Fluids additional reading available at the SPE eLibrary: www.spe.org SPE 108653 • "Assessment of the Fate and Ecological Risk of Synthetic-Paraffin-Based-Drilling-Mud Discharges Offshore Sarawak and Sabah (Malaysia)" by P.B. Dorn, Shell, et al. SPE 112687 • "Automatic Measurement of Drilling-Fluid and Drill-Cuttings Properties" by A. Saasen, SPE, StatoilHydro, et al. SPE 110341 • "Unique Characteristics of Mixed-Metal-Oxide Fluid Cures Lost Circulation While Meeting European Environmental Regulations" by Reinhard Oswald, Petrom, et al. Additional reading available at OnePetro: www.onepetro.org OTC 19210 • "Understanding the Impact of Completion-Brine Packer Fluids on Cracking Susceptibility of CRA Materials for Deepwater Applications" by Paul H. Javora, BJ Services, et al.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.002 |
| Insufficient payload (model declined to judge) | 0.190 | 0.107 |
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".