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Record W1965057676 · doi:10.2118/2005-138-ea

Identification of Environmental Effects of Acid Gas Injection Using X-Ray Computed Tomography

2005· article· en· W1965057676 on OpenAlexafffund
M.A. Vickerd, Ronald W. Thring, J. M. Arocena, Richard J. Heck

Bibliographic record

VenueCanadian International Petroleum Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of GuelphUniversity of Northern British Columbia
FundersUniversity of GuelphUniversity of Northern British ColumbiaDuke Energy
KeywordsCitationLibrary scienceIdentification (biology)DownloadComputed tomographyInformation retrievalComputer scienceWorld Wide WebMedicine

Abstract

fetched live from OpenAlex

Abstract With the increasing trend to dispose acid gases (H2S and CO2) generated from natural gas processing, by geologic sequestration, industry and government must carefully assess the compatibility of the rock formation and fluids with the intended injection stream to ensure safe and efficient facility operations. Recent geochemical analysis of carbonate cores, previously subjected to acid gas core displacement tests, prompted an examination of changes to porosity using x-ray computed tomography (CT). Results indicate that increases in porosity may be linked with the increases in permeability observed during the core injectivity testing. Visually distinct areas in the core suggested that changes were non-uniform implying regions of higher consolidation representing lower permeability. In addition, when several voids were subjected to detailed CT image analysis, we observed traces of halite (NaCl) crystals probably resulting from the desiccation of formation water by the extremely dry acid gases. This suggests that the increase in porosity could not be attributed to dissolution processes, but due to fine dislodgement of materials during the high pressure injection. Inadvertently, the permeability increases were resultant of both desiccation effects and particle dislodgement. Introduction Acid gas injection has been accepted as a practical way to dispose of the undesirable H2S and CO2 (acid gases) produced from natural gas processing. This technology allows the production of sour gas reservoirs to be economically viable and provides an environmentally friendlier option in comparison to other disposal alternatives. In order to successfully dispose of the acid gas in a safe and efficient manner, the process of selecting an adequate disposal formation includes assessment of various reservoir conditions in order to determine suitability. One of the requirements is to examine the compatibility of the mineralogy of rock formation and its fluid with the injection stream, usually accomplished through core sensitivity tests. Core Sensitivity Tests The objective of the core sensitivity test is to observe any significant changes in permeability, to ensure that impairment to injection will be minimized. This test is essential because of the potential to damage the formation as a result of the acid gas injection which could jeopardize injection or containment within the formation. Some potential formation effects which may include but is not limited to; desiccation, dissolution and dislodgement of fine materials (1). Desiccation occurs when the formation fluid has significant salinity and the acid gas stream is highly understaturated in water resulting in a salting out effect as the injected stream reduces the initial brackish pore fluids. Dissolution takes place when acid gases dissociate in formation fluids decreasing the pH and increasing the natural water-rock reactions of the reservoir. Fine dislodgement is generally experienced in poorly consolidated cores when subjected to the injection pressures and increased flow rates over the small surface area of the pores. An ideal core would be sufficient in size to allow for monitoring of all of these effects, especially the geochemical effects of dissolution and re-precipitation, if they occur (1). Unfortunately, in practical applications the selection of cores to choose from is limited when using a previously producing well to inject into a depleted hydrocarbon reservoir.

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: Empirical
Teacher disagreement score0.042
Threshold uncertainty score0.497

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 head0.005
GPT teacher head0.193
Teacher spread0.188 · 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

Citations2
Published2005
Admission routes2
Has abstractyes

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