Improving Drilling Efficiency and BHA Reliability Using Hybrid-Mode Telemetry
Bibliographic record
Abstract
Abstract Most MWD systems use Mud Pulse (MP) or Electro Magnetic (EM) telemetry. Each telemetry system has very specific applications and limitations due to the governing physics. The Hybrid-Mode Telemetry of MP and EM in one system widens the operational envelope and increases drilling performance covered by a single BHA. This paper discusses the applications and benefits of Hybrid-Mode Telemetry with proven field deployments for both conventional and unconventional drilling. The Hybrid-Mode Telemetry system is designed to operate with either the EM or MP channel, or to use both channels simultaneously and independently. The latter case also supports the parallel transmission of two different data streams. With this flexibility, Hybrid-Mode Telemetry can increase drilling performance significantly through reducing survey time, reducing downlinking time, and increase reliability by having two telemetry channels serving as back up for each other. Furthermore, with a maximum system bandwidth capability of up to 20 bits per second and zero downtime on transmission, the Hybrid-Mode Telemetry technology also enhances data rate for Formation Evaluation, Geosteering, and Automation drilling. Hybrid-Mode Telemetry allows for the EM channel to transmit up to 16 bps, and the Mud Pulser channel up to 3.6 bps. With high data rates of 20 bps, high signal strength, and advanced algorithms capable of reliably decoding signals as low as 0.01 mV (10 times more sensitive than typical industry capabilities of 0.1-0.2mV), the Hybrid-mode Telemetry provides superior data and decoding capabilities for today's land-based drilling markets. Hybrid-Mode Telemetry has been successfully used in conventional wells for more than 10 million feet drilled, mainly in onshore North America and Canada. In comparison with legacy Mud Pulse in the same areas, Hybrid-Mode Telemetry showed on average a 37% reduction in drilling time with Motor BHAs. The drilling time reduction is mainly driven by higher data rate, reduction in stationary survey time, and higher reliability of the entire system – up to 99% operating efficiency. This allowed for optimization of drilling parameters and improved decision-making processes. Field testing of Hybrid-Mode Telemetry with Rotary Steerable BHAs is currently ongoing for unconventional drilling applications at deeper drilling depths, involving more complex well profiles and faster drilling rates compared to Motor drilling wells. While sufficient data for evaluation and conclusion is still to be gathered, the Hybrid-Mode Telemetry is expected to contribute to a gross ROP increase by 15-30%. This paper will present, in detail, techniques observed from field data on how to maximize drilling efficiencies through survey time reduction, flow independent downlinking, and optimized telemetry configurations that increase data rate while drilling. In addition, the paper will also describe drilling applications using Hybrid-Mode Telemetry.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".