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Record W2007967062 · doi:10.4043/21402-ms

Changes of Operating Procedures and Chemical Application of A Mature Deepwater Tie-back -Aspen Field Case Study

2011· article· en· W2007967062 on OpenAlex

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.

Bibliographic record

VenueOffshore Technology Conference · 2011
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsProduced waterWater injection (oil production)Environmental scienceAsphaltenePetroleum engineeringFlow assuranceWaste managementEngineeringHydrateEnvironmental engineeringChemistryChemical engineering

Abstract

fetched live from OpenAlex

Abstract The Aspen field is located in about 3050 ft water in the Gulf of Mexico on GC243 block and tied back to Bullwinkle production facilities on GC65 block via dual 16-mile wet-insulated pipelines. Its first production began in December 2002. The project was a fast-track, marginal field with an assumption of quick reservoir pressure decline. Hydrate is managed primarily by MeOH injection during startup and shutdowns. The reservoir fluids are complex. Downhole sample tests showed asphaltene onset pressure was 6500 psig (~500 psi above bubble point). An asphaltene inhibitor was continuously injected downhole as well as scale inhibitor since the field was suspected with scale and asphaltene issues in the earlier production life. The produced water has a total dissolved salt of 230,000 mg/l. The oil production has declined significantly from initial production while the water cut reaches up to 80%. The characteristics of field production have been changed significantly since the initial production date. A review was conducted by flow assurance team working with its chemical supplier. During the study period a large amount of fluid tests were conducted and chemical application program were reviewed by chemical supplier's experts along with the operator's engineering team. Planning to field execution took more than one year, resulting in termination of downhole injection of asphaltene inhibitor and scale inhibitor. Additionally there was a reduction in methanol usage and other topside chemicals, and the operating guidelines were revised. The financial benefits include cost reduction, as well as quicker startup and shutdown. This paper will present the methodologies, organization, tests, recommendations, field execution plan and results after implementation of the recommendations. The case study also demonstrates how the operation team and engineering support team of an operator can work with suppliers, utilizing the industry experience, to achieve best results. Introduction In deepwater water asset operations, understanding the multiphase flow system and associated chemical applications are two major components to properly formulate operating procedures. During the exploration and development phase of a project, design criteria usually tend to be conservative. After a field starts production, periodic reviews will confirm the validity of design promises and improve operational efficiency. In the petroleum industry, wax, asphaltene, hydrates, scale, internal corrosion, sand production were always the major problems in production operation, great deal efforts were made to understand the issues and develop chemicals to ease these issues, especially for deepwater developments. Significant progress has been made on the chemistry aspects through university and industry consortia [1-5]. Petroleum production operation should be based on and treated as a system[6] operation. Systematic approach is more important to the success of the deepwater project due to the long subsea pipelines and cold environment as well as high costs associated with subsea intervention. Phase-equilibrium (chemistry, including inhibitors) and multiphase flow behaviors (modeling) are the two key subjects (components) to understand a production system, and are related to each other. A systematic approach with a focus on fluid characterization was presented by Jamaludin et al.[7] As more reserves are discovered in deeper waters; more attention is paid to the flow assurance issues.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.546
Threshold uncertainty score0.579

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 head0.016
GPT teacher head0.220
Teacher spread0.204 · 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