Spectral Noise Logging Integrated with High-Precision Temperature Logging for a Multi-Well Leak Detection Survey in South Alberta
Bibliographic record
Abstract
Abstract Gas or fluid ingress into the cement channel and then up to the surface through the surface casing annulus is called Surface Casing Vent Flow (SCVF), which causes Sustained Annulus Pressure (SAP) as a common occurrence in the petroleum industry. Gas may also migrate to the surface outside the outermost casing string, which is often referred to as external Gas Migration (GM) or seepage. In some countries with shallow coal reserves, gas migration sometimes occurs in association with coalbed gas (CBG) development. Dewatering the coal seams or lowered water levels in coal, whether induced by drought or by domestic aquifer pumping, can result in the release of methane and other natural gases in coal (NGC). Hydrocarbon gases released into the atmosphere is an environmental concern. More importantly, leaking fluids may contaminate subsurface fresh-water reservoirs, resulting in a major catastrophe for the environment and human population. According to the latest statistics, 6% of almost 270 000 operating and idle wells analysed in Alberta were found to contain leaks, 5.5% of them having SCVF and 0.5% gas migration [2]. Operators are bound by the Alberta Energy Regulator (AER) to identify and eliminate leaks and perform remedial operations as outlined in AER's rules and directives. Even if a well is to be abandoned, the operators must precisely identify the location of the leak and its source to perform a successful plug-and-abandonment (P&A) operation. P&A activities are non-revenue generating activities. The right diagnostic technology is critical for correct leak source identification to eliminate the costs associated with numerous unsuccessful attempts. The technique of Spectral Noise Logging (SNL) coupled with High Precision Temperature (HPT) Logging have extensively benefited oil industry outside Canada in accurately identifying fluid flow behind multiple casing pipe barriers and in locating leaks and their sources [3–5]. This paper describes two case histories for eight wells in the Western Canadian Sedimentary Basin (WCSB) in South Alberta region for two clients, where application of these techniques enabled gas leak source identification in a series of wells suffering from minute leak rates and also helped to discover some regional lateral flows and cross-flows.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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".