Intelligent Wired Drill-Pipe System Provides Significant Improvements in Drilling Performance on Offshore Australia Development
Bibliographic record
Abstract
Abstract An ‘Intelligent’ wired drill-pipe system has recently been used on a large offshore development in North West Australia for Apache Energy Limited. The IntelliServ® network is designed to overcome the shortcomings of mud pulse telemetry in terms of real-time data transmission speeds and pulser reliability. By utilising this unique system of Intellipipe® wired drill pipe and associated drilling tools connecting the Rotary Steerable System and LWD string to the surface, transmission speeds of up to 57,000 BPS theoretically can be achieved. For the development of the Van Gogh Field, Apache Energy Ltd decided to utilise the IntelliServ system along with Halliburton's rotary steerable system and LWD tools. This paper will describe the wired drill pipe network and its integration with a drilling assembly containing a rotary steerable system, multiple formation evaluation and drilling dynamics sensors. The objectives for running the wired drill pipe system on this project will be discussed and the actual operational experience reviewed. Topics to be covered will include the improvements in drilling optimisation and drilling performance, the increased accuracy in wellbore placement, and the improved quantity and quality of the formation evaluation data received in real-time. The future uses and benefits of this technology also will be reviewed. Introduction Modern MWD and LWD sensors now generate so much data that it is not possible to take full advantage of this data due to the limitations imposed by conventional mud pulse telemetry systems. Although advances have been made in the form of data compression and batch transmission modes, mud pulse transmission is still the limiting factor in many potential applications. Typical LWD assemblies may now consist of tool combinations including gamma-ray, multiple resistivity, density and neutron petrophysical measurements. The latest LWD sensors can provide formation images, sonic waveforms, and multiple geosteering signals, all of which require large bandwidths in order to take full advantage of them. In addition, directional survey data, downhole drilling optimisation measurements also may be transmitted. This amount of data can place a great strain on conventional mud pulse telemetry systems. As drilling rates increase the data density of the real-time measurments becomes increasingly sparse until at some point, drilling rates must be held back to ensure that a useable log is received in real-time.
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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 | 0.000 | 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 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".