Chemical Prevention of Corrosion-Induced Premature Well Failures Using a Novel Lubricity Mitigation Strategy
Bibliographic record
Abstract
Abstract The sucker rod systems and tubing strings play a crucial role in the mechanical oil recovery process; their stability and reliability are desirable factors in optimizing oil production from a well. Although durable, these metallic downhole tools and equipment can experience failure during oil recovery. These failures usually stem from accumulated fatigue induced by corrosion or associated mechanisms. The dilapidation of these costly crucial pumping components often leads to expensive downtimes, lost production, and unnecessary maintenance costs, which can all be exacerbated by frequent failures. While such downhole equipment failures have traditionally and simplistically been prevented using conventional corrosion inhibitors, this approach has proved ineffective in high-failure frequency wells, instigating the use of ancillary production chemicals to address other issues that are symptomatic of observed corrosion mechanisms. It is imperative to develop a mitigation strategy to extend the run life of wells and occlude premature downhole equipment failures, thereby providing increased production time and cost savings for production companies. This paper presents a field-proven methodology that was used to extend the run life of high-failure frequency wells in the Western Canadian Sedimentary Basin (WCSB), involving the continuous application of lubricious corrosion inhibitors. The corrosion inhibitors’ Coefficient of Friction (CoF) was quantified using the Bruker UMT tribology tester. This bifurcate study focuses on two major aspects: a root cause analysis of the high-frequency failures and the corresponding chemical mitigation strategy to address these rampant failures. The scientific root cause analysis showed that wellbore configuration has a substantial and consistent effect on downhole equipment failures and hints at the inimical role of friction in inducing rampant failures, prompting the need to incorporate lubricity in the chemical mitigation strategy, especially for complex directional wells. This successful approach has been implemented in over 3000 wells and has eliminated frequent pumping component failures and extended the run-life of wells in some cases from about three months to up to three years in the Western Canadian Sedimentary Basin (WCSB), resulting in up to $250,000.00 in cost savings on each well from reduced production chemicals usage and lower well-servicing costs. The results from this data-backed study provide a more validated rationale and mitigation approach to dealing with premature well failures. This paper showcases and elucidates an economical and pragmatic chemical mitigation strategy to address frequent well failures and optimize oil production while providing operational recommendations during drilling that are key to improving a well's long-term productivity.
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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) | 0.001 | 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 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".