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Record W2014187467 · doi:10.4043/15282-ms

Can Heavy Oil and Deepwater be Mixed?

2003· article· en· W2014187467 on OpenAlexaboutno aff
John P. Haney

Bibliographic record

VenueOffshore Technology Conference · 2003
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsSubmarine pipelineProduct (mathematics)Petroleum industryWork (physics)BusinessPetroleum engineeringRisk analysis (engineering)Natural resource economicsComputer scienceEnvironmental scienceEngineeringGeologyOceanographyEconomicsMechanical engineeringEnvironmental engineering

Abstract

fetched live from OpenAlex

Abstract The development of heavy oil offshore in general has been a major challenge for the industry. Making this happen in deepwater presents greater barriers given the economics of such developments, although it is becoming increasing important that solutions be found. This will require addressing three areas to make it viable - well performance, development costs and product value. There are actually factors that give deepwater and remote developments in particular an advantage in heavy oil developments, but there remains numerous hurdles before it can be seen as an option that will compete for investments. Technology and novel business solutions will both be key enablers in making this a reality. Introduction Many Operators have struggled to make heavy oil (less than 20 API gravity) work offshore at all. Shell's global heavy oil production in Canada, Oman, the Netherlands, California and Venezula has all been primarily onshore with a few shallow water fields. The higher costs associated with deepwater developments have made the barrier even higher with typical cost being two-times those of similar light oil fields. However, the increasingly heavy nature of global deepwater discoveries has forced the industry to address this issue now. Shell's experience in heavy oil is being applied to this challenge in Brazil and other deepwater arenas. Is it possible that such developments can be made consistently economically viable and compete with other options? Do deepwater developments by their very nature offer some unique advantages over other areas? To overcome the challenges the "triple hitters" of heavy oil will need to be considered:Reduced well performance (recovery and rate)Increased developments costs, including wells and offshore processing equipmentReduced value for the product in the market Depending on the specific field properties and location, all three of these may need to be overcome. Well performance It is not unusual in heavy oil developments to reduce typical light oil recovery efficiencies by half. The critical factor in this regard being not the gravity of the oil, but the viscosity with a very loose correlation between the two. The resulting reduction of reserves by one half makes typical deepwater developments uneconomic as they are normally driven by high rates and high ultimates per well. It should be recognized that during the exploration and appraisal phase it is critical to properly assess the crude properties for these heavy oils as the range of uncertainty is much larger than typically encountered. This includes increased need for short-term well testing to determine producability. Such testing presents numerous challenges, especially in an exploration mode. Depending upon the oil viscosity, it may require complex submersible pumping systems, lifting equipment and processing equipment that is not standard for offshore testing. Planning and contingency systems are often required to ensure success, including conducting it in a safe and environmentally friendly manner. It is also important during the appraisal phase to obtain reliable oil samples and cores to accurately analyze and predict reservoir properties (relative permeability, porosity, etc,) and performance.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.347
Threshold uncertainty score0.619

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 head0.019
GPT teacher head0.243
Teacher spread0.224 · 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
Published2003
Admission routes1
Has abstractyes

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