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Record W2046273957 · doi:10.2118/2003-129

Foam Cement Applications for Zonal Isolation in Coalbed Methane Wells

2003· article· en· W2046273957 on OpenAlexaffabout
EG Fidan, Ergün Kuru, Tayfun Babadagli

Bibliographic record

VenueCanadian International Petroleum Conference · 2003
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCoalbed methaneCementPetroleum engineeringIsolation (microbiology)GeologyMaterials scienceEngineeringWaste managementComposite materialCoalCoal mining

Abstract

fetched live from OpenAlex

Abstract This paper discusses the application of foam cement technology for zonal isolation in coal bed methane (CBM) wells. CBM reservoirs have unique cleat structures that are weaker and less stable than conventional reservoirs. As the gas storage mechanisms in the CBM reservoirs release methane and other light gases through diffusion, bedding structures can be even more destabilized. Conventional cement sheaths may not withstand annular deformation and may crack because of cyclic stress loads. Results of recent laboratory tests and field applications have shown that foam cement can be effectively used to eliminate zonal isolation problems associated with the application of conventional cement jobs in CBM wells. Laboratory tests have shown that a foam-cemented annulus can elastically absorb stresses from the pressure-induced expansion of internal casing and deform without failure. The foamed cement can maintain bond and overall integrity in such tests at up to 10,000 psi internal casing pressure. In cycling tests, foam cement was found to withstand 100 cycles, up to 90% of shear failure index, without noticeable damage. Results of some recent laboratory tests are presented in this paper. Zonal isolation using foamed cement has been successfully conducted in many wells drilled in western Canada CBM reservoirs. An example of recent foamed cement application in a CBM well is also presented. Introduction Foam cement is a mixture of cement slurry, foaming agent, foam stabilizer, and nitrogen gas. When the foam cement is properly generated, a stable and lightweight slurry that looks like gray shaving cream can form (Fig. 1). When foam slurries are properly mixed and sheared, they often contain microscopic, discrete bubbles that will not coalesce or migrate. The bubbles formed are not interconnected (Fig. 2), which results in a low-density cement matrix with low permeability and relatively high strength. Historically, the primary purpose of foamed cement was to decrease the density of slurry. However, many other advantages have been identified, and subsequent applications of foam cement are well documented.1–7 This paper describes the most recent technology in foam cement application. Characteristics of the foam cement and laboratory test results are summarized. Guidelines for field applications are provided, and an example of a field application of foam cement in a CBM well is also presented. Physical Properties Of Foam Cement The following section briefly discusses some of the favorable physical properties of foam cement. Lightweight Stable foam cement can yield 720 kg/m3 downhole density at bottomhole conditions. During primary cementing, foam cement can prevent formation breakdown, lost circulation, and post-job cement fallback. The extremely lightweight quality of foam is especially useful for lost-circulation plugs where conventional methods of cementing may not be applicable. Excellent Strength-to-Density Ratio Foam cement has an excellent strength-to-density ratio (Fig. 3). Slurries that contain less water are usually stronger than those that carry a lot of water. With inert nitrogen gas as a filler material, slurries of even very low density can still have high solids content, which causes the ultimate strength to be relatively high.

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 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: none
Teacher disagreement score0.950
Threshold uncertainty score0.999

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 head0.014
GPT teacher head0.219
Teacher spread0.205 · 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 teacher head, 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".

Quick stats

Citations8
Published2003
Admission routes2
Has abstractyes

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