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Record W4239037957 · doi:10.2523/106817-ms

Evaluation of the Potential for Gas and CO2 Leakage Along Wellbores

2007· article· en· W4239037957 on OpenAlexaffabout
Theresa L. Watson, Stefan Bachu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsAlberta Energy
Fundersnot available
KeywordsWatsonCitationLeakage (economics)Computer scienceInformation retrievalWorld Wide WebArtificial intelligence

Abstract

fetched live from OpenAlex

Evaluation of the Potential for Gas and CO2 Leakage Along Wellbores Theresa Lucy Watson; Theresa Lucy Watson T.L. Watson & Associates Inc. Search for other works by this author on: This Site Google Scholar Stefan Bachu Stefan Bachu Alberta Energy & Utilities Board Search for other works by this author on: This Site Google Scholar Paper presented at the E&P Environmental and Safety Conference, Galveston, Texas, U.S.A., March 2007. Paper Number: SPE-106817-MS https://doi.org/10.2118/106817-MS Published: March 05 2007 Connected Content Related to: Evaluation of the Potential for Gas and CO2 Leakage Along Wellbores Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Watson, Theresa Lucy, and Stefan Bachu. "Evaluation of the Potential for Gas and CO2 Leakage Along Wellbores." Paper presented at the E&P Environmental and Safety Conference, Galveston, Texas, U.S.A., March 2007. doi: https://doi.org/10.2118/106817-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Health, Safety, Security, Environment, Search Advanced Search AbstractImplementation of carbon dioxide storage in geological media requires a proper assessment of the risk of CO2 leakage from storage sites. Leakage pathways may exist through and along wellbores which may penetrate or be near to the storage site. One method of assessing the potential for CO2 leakage through wells is by mining databases that usually reside with regulatory agencies These agencies collect data concerning wellbore construction, oil and gas production, and other regulated issues for existing wells. The Alberta Energy and Utilities Board (EUB), the regulatory agency in Alberta, Canada, collects and stores information about more than 315,000 oil, gas and injection wells in the province of Alberta, Canada. The EUB also records well leakage at the surface as surface casing vent flow (SCVF) through wellbore annuli and gas migration (GM) outside casing, as reported by industry.The evaluation of a leakage pathway through wellbore casing or annuli and what causes these wellbore leaks is a first step in determining what factors may contribute to wellbore leakage from CO2 storage sites. By utilizing available data, major factors which contribute to wellbore leakage were identified.Data analysis shows that there is a correlation between these SCVF/GM and economic activity, technology changes, geographic location and regulatory changes regarding well completion and abandonment. Further analysis indicates a relationship between low annular cement top, external corrosion, casing failure and wellbore leakage (SCVF/GM). Other factors that could affect the presence of wellbore leakage, such as wellbore deviation, surface casing depth and wellbore density, were also investigated.This paper presents the findings of the data analysis and a method to evaluate the potential for leakage along wells in an area where CO2 storage is intended. This information is useful not only for future operations of CO2 storage in geological media, but also for current operations relating to the exploration and production of hydrocarbons.IntroductionThe possibility of removing CO2 from an industrial emission stream and storing it in deep geological media to reduce the impact on the atmosphere of green house gas is being extensively investigated1. More than 80 CO2 injection schemes have been in operation since as early as the 1970's for tertiary oil recovery as miscible floods2, with the side benefit of CO2 removal from the atmosphere. Other gas injection schemes are also in use within the oil and gas industry, such as natural gas storage and acid gas disposal.In the case of CO2 sequestration, the storage unit must be near leak free, to the atmosphere or other geological formations, to justify the costs and to meet safety requirements and greenhouse gas reduction objectives. This paper will focus on human created leakage paths, in particular wellbores that were previously drilled for exploration and production of oil and gas reserves and were subsequently abandoned. The work reported here determines important factors which can be used to predict which wellbores are mosre likely to leak, have future abandonment liablilty and if these wellbores will adversely impact CO2 storage shemes in the future. The analysis is based on data for more than 315,000 wells drilled up to the end of 2004 in the province of Alberta, Canada.BackgroundPotential Wellbore Leakage PathwaysFigure 1 illustrates typical wellbore construction and abandonment profiles for Alberta, Canda. From these diagrams one can identify potential leakage pathways from a CO2 storage reservoir or gas-bearing formation. For a leak to occur three elements must exist3:A leak sourceA driving force such as buoyancy or head differentialA leakage pathway Keywords: wellbore integrity, Wellbore Design, casing and cementing, Scvf Gm, information, casing design, Upstream Oil & Gas, co 2, CO2 capture, regulatory change Subjects: Wellbore Design, Casing and Cementing, Unconventional Production Facilities, Wellbore integrity, Casing design, CO2 capture and management This content is only available via PDF. 2007. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.011
GPT teacher head0.226
Teacher spread0.215 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

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".

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Citations29
Published2007
Admission routes2
Has abstractyes

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