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Record W2245353730 · doi:10.2523/86476-ms

Scale Control Within North Sea Chalk/Limestone Reservoirs: The Challenge of Understanding and Optimizing Chemical Placement Methods and Retention Mechanism - Laboratory to Field

2004· article· en· W2245353730 on OpenAlexaff
M. M. Jordan, K. Sjursæther, I. R. Collins

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicCalcium Carbonate Crystallization and Inhibition
Canadian institutionsNalcor Energy (Canada)
Fundersnot available
KeywordsExhibitionCitationScale (ratio)Library scienceEngineeringComputer scienceArchaeologyMining engineeringGeographyCartography

Abstract

fetched live from OpenAlex

Scale Control Within North Sea Chalk/Limestone Reservoirs. The Challenge of Understanding and Optimizing Chemical Placement Methods and Retention Mechanism: - Laboratory to Field. M.M. Jordan; M.M. Jordan Ondeo Nalco Energy Services Search for other works by this author on: This Site Google Scholar K. Sjursaether; K. Sjursaether Ondeo Nalco Energy Services Search for other works by this author on: This Site Google Scholar I.R. Collins I.R. Collins BP Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Symposium and Exhibition on Formation Damage Control, Lafayette, Louisiana, February 2004. Paper Number: SPE-86476-MS https://doi.org/10.2118/86476-MS Published: February 18 2004 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Jordan, M.M., Sjursaether, K., and I.R. Collins. "Scale Control Within North Sea Chalk/Limestone Reservoirs. The Challenge of Understanding and Optimizing Chemical Placement Methods and Retention Mechanism: - Laboratory to Field.." Paper presented at the SPE International Symposium and Exhibition on Formation Damage Control, Lafayette, Louisiana, February 2004. doi: https://doi.org/10.2118/86476-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Conference and Exhibition on Formation Damage Control Search Advanced Search AbstractThe scale control challenges for two North Sea carbonate reservoirs are reviewed in this paper. Whilst carbonate reservoir are not the largest source of hydrocarbon within the North Sea, they are very significant on a global bases.The mechanism of scale inhibitor chemical retention observed for phosphonate, polymer, and vinyl sulphonate co-polymer inhibitors on carbonate reservoir substrates is outlined. Chemical placement represents the most significant technical challenge when performing scale squeeze treatments into fractured chalk reservoirs. Examples from over 50 field treatments applied in reservoirs E and V, where both phosphonate and vinyl sulphonate polymer chemicals have been deployed, are used to illustrate the difference in chemical retention observed in laboratory evaluations. The laboratory studies demonstrated clear potential for significant extension in treatment lifetime by changing from a phosphonate to a vinyl sulphonate co-polymer-based scale inhibitor. The selection and qualification of chemical placement systems for deployment of inhibitors in fractured carbonate reservoirs are also outlined. To this end, novel technologies to enhance conventional scale inhibitor chemical placement are vital to economic success during water flood projects.IntroductionThe correct selection of scale inhibitor for the control of mineral scale within reservoirs and associated production tubing is vital if economic hydrocarbon production is to be maintained. The following section will outline the principle differences between carbonates and sandstone reservoirs, which makes scale inhibitor selection and application a technical challenge.What is Carbonate?Carbonate reservoirs are principally composed of carbonate minerals, which include calcite (CaCO3), dolomite (Ca,MgCO3), ankerite (Ca,Mg,FeCO3), and siderite (FeCO3). Carbonate reservoirs can be sub-divided into chalk and limestone. Chalk reservoirs are composed of small spherical/plate-like particles (cocoliths) of calcium carbonate from the skeletons of marine organisms, which became compacted and cemented to form rock with a higher primary porosity - this shown in Figure 1. Limestone is generally formed by the deposition of fine carbonate mud with associated fragments of biogenetic material (shells, etc) which is compacted to form rock.1,2 Such a limestone reservoir would generally have a low primary porosity but a high secondary porosity owing to the dissolution of some of the rock caused by reaction of pore fluids during burial.Fluid Flow in Carbonate ReservoirsFlow within carbonate reservoirs generally occurs as a result of fluid flow within fractures (both natural and induced), which enhance production. The fluid flows first through interconnecting pores, and then, second, along the fracture paths to the well bore. The pores formed during sediment deposition are generally poorly connected within carbonate reservoirs resulting in a lower permeability/porosity ratio than for sandstone reservoirs. The deposition of scale, both carbonate and sulphate, within carbonate reservoirs results in a decline in total production rate, with the fractures becoming restricted owing to the deposition of scale as a film. In the smaller fractures, the deposition and restriction of flow could be associated with the migration of scale particles which block, or reduce, fluid paths. Mechanical or acid generated fractures can sustain a significant amount of damage (95% of the fracture face not contributing) before the fluid production from such a well is significantly rimpacted.3 Keywords: application, flow in porous media, squeeze treatment, fracture, remediation of hydrates, international symposium, injection, brine, placement, wax remediation Subjects: Hydraulic Fracturing, Production Chemistry, Metallurgy and Biology, Reservoir Fluid Dynamics, Improved and Enhanced Recovery, Unconventional and Complex Reservoirs, Inhibition and remediation of hydrates, scale, paraffin / wax and asphaltene, Flow in porous media, Carbonate reservoirs This content is only available via PDF. 2004. 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 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)0.001
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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score0.291

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.037
GPT teacher head0.292
Teacher spread0.254 · 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 designBench or experimental
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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Citations8
Published2004
Admission routes1
Has abstractyes

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