Development of an Intelligent System for the Analysis of both Static and Real-time Oil and Gas Well Drilling Data
Bibliographic record
Abstract
The growing demand of digital oilfield in oil and gas industry leads extensive research on the development of engineering software for the analysis of real-time oil and gas drilling data. The Intelligent Drilling Advisory system (IDAs) is an engineering software and being developed to provide a way for the drilling engineers to visualize, collaborate and analyze drilling operational data in real-time in an office environment. WITSML (Wellsite Information Transfer Standard Markup Language) is a web-based oil and gas industry standard used to conduct transfer of drilling data between the developing system (IDAs) and onsite or remote WITSML servers. IDAs uses WITSML SOAP interfaces to retrieve both static and real-time drilling data updating from the server and provide meaningful analysis using different engineering modules for enhanced decision-making to the ongoing drilling operation. The intelligent system is successfully tested with real WITSML servers to verify the functionalities of the engineering modules, as well as, the system itself.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".