Continuous Measurement-While-Drilling Surveying System Utilizing Low-Cost SINS
Bibliographic record
Abstract
Abstract In the oil and gas drilling process, measurement-while-drilling (MWD) systems are usually used to provide real-time monitoring for the position and orientation of the bottom hole assembly (BHA). The current MWD systems can be categorized into magnetometer-based systems and gyroscope-based systems, which both compute the wellbore trajectory based on stationary surveys at the desired station using a mathematical model with certain assumptions. This current technology neglects the actual trajectory between surveying stations. This research proposed a system using low-cost strapdown inertial navigation system (SINS) to avoid the limits of traditional methods. Demands have been rising for a continuous survey that captures the actual trajectory between the stationary surveying stations, especially in case of directional drilling process. Based on this technology, "dogleg" along the trajectory can be estimated more accurately. Therefore, a low-cost SINS consisting of three MEMS accelerometers and three MEMS gyroscopes is proposed to estimate the trajectory and satisfy the cost demand of commercial companies. This MWD surveying system could eliminate the size constraint of conventional inertial sensors and thus can be used in small well drilling. The core algorithms in the system are SINS mechanization and unscented Kalman filtering (UKF). Due to the large noise in MEMS sensors especially under large shocks and high vibrations, this wellbore survey system will exhibit an unlimited growth of position, inclination, tool face angle and azimuth errors if there are no external observations to update the surveying system. The following external aiding information can be used as updates for the MEMS-based INS in the drilling procedure: the length and velocity information of the total pipelines, the zero velocity information during periodic stop intervals and azimuth information from the magnetometers. Performances the following different solutions: (1) MEMS sensors; (2) MEMS sensors + length/velocity update; (3) MEMS sensors + length/velocity update + ZUPT; and (4) MEMS sensors + length/velocity update + ZUPT + mag-based heading were analyzed. The proposed method was validated by 4 different simulation cases with respect to a typical wellbore trajectory: build, hold and drop wellbore profile. Situations of external aiding information being temporarily unavailable were considered in the simulation. The performance and feasibility of the presented continuous borehole surveying method had been demonstrated in this paper. The proposed low cost SINS-based MWD method can eliminate the costly nonmagnetic drill collars for the magnetometers, overcome the size limitation of gyroscope-based MWD systems for small wells drilling, survey the borehole continuously without interrupting the drilling process, and improve the overall accuracy by utilizing UKF technique.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".