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Record W2231085720 · doi:10.2118/175450-ms

Spectral Noise Logging Integrated with High-Precision Temperature Logging for a Multi-Well Leak Detection Survey in South Alberta

2015· article· en· W2231085720 on OpenAlex
Arthur Aslanyan, Irina Aslanyan, Radhakrishnan Karantharath, Roza Minakhmetova, Hassan Kohzadi, Mohsen Ghanavati

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueSPE Offshore Europe Conference and Exhibition · 2015
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsAnnulus (botany)Petroleum engineeringCasingCoalCoal miningNatural gasEnvironmental scienceAquiferLoggingGeologyMining engineeringMethaneNatural gas fieldEngineeringWaste managementGeotechnical engineeringGroundwater

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.137
Threshold uncertainty score0.924

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.030
GPT teacher head0.221
Teacher spread0.190 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it