Logging While Tripping-A New Alternative in Formation Evaluation
Bibliographic record
Abstract
Abstract Logging While Tripping (LWT) is a recent development in formation evaluation technology that provides a means by which open hole logs are obtained more quickly and with less risk than is currently possible using conventional wireline or measurement-while-drilling techniques. LWT Services Inc., a Calgary based company, has developed this new approach to the logging process which involves using specially modified drill collars and memory-based logging tools positioned within the drillstring to record log data as drillpipe is tripped out of the well. LWT tools are deployed and retrieved from the drillstring only when log data is required. After the data is acquired and the tools retrieved from the well, casing can be run without an additional hole-conditioning trip, saving considerable rig time. Risk is minimized because logging tools are not exposed to the open wellbore, but stay protected inside the drillstring. Service quality is reviewed by showing examples dealing with data quality and depth control. While LWT's compensated neutron provides an open hole quality measurement, some correction is needed to provide absolute porosity values in varying borehole sizes. Depth control examples compare favourably to wireline conveyed logs with an accuracy approaching +/- 1 m per 3,000 m of total depth. A few applications for this new technology are anticipated to be:Horizontal wells which are currently not evaluated due to the prohibitive cost and risk associated with pipe conveyed and MWD/LWD systemsReconnaissance logging, done at any time throughout the drilling of the well, will enable geologists to identify zones and monitor well trajectoryUnderbalanced, air-drilled wells can be logged as they are drilled, thereby eliminating the need to run open hole logs under pressure. Presently, LWT Services Inc. is working on a prototype 1 11/16 in. induction tool. In order to make induction measurements from inside the drillstring, a nonconductive composite drill collar has been constructed, tested, and successfully drilled 850 ft. in a test well in Oklahoma. Another development includes a compensated photoelectric density tool. Background Logging While Tripping (LWT) represents a new approach in the process of open hole data acquisition. LWT makes use of memory-based logging tools positioned in the drillstring to record data as drill pipe is tripped out of the well. Unlike measurement-while-drilling tools, LWT tools are not a permanent part of the drillstring but instead are deployed and retrieved from the drillstring only when log data is required. Currently, LWT provides FIGURE 1: LWT operation. (Available in full paper) compensated neutron and gamma ray services while the dual induction and photoelectric density are under development. While in its early stages of development, LWT's technology is aimed at providing drillers with significant cost savings in the area of open hole data acquisition. These cost savings will be realized in two principal areas:Decrease in rig time for the logging process and,Decrease in risk of tool loss or damage downhole. This paper presents an overview of LWT's operation, service quality, and applications supported by several examples. In closing, a brief review of future prospects is presented.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".