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Record W4236526866 · doi:10.2523/97898-ms

Heavy-Oil Uncertainties Facing Operators in the North Sea

2005· article· en· W4236526866 on OpenAlexaboutno aff
K. L. Morton, Magdy Samir Osman, Stephen Kew

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental scienceMarine engineeringComputer sciencePetroleum engineeringGeologyEngineering

Abstract

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Heavy Oil Uncertainties Facing Operators in the North Sea Kirsty Lorna Morton; Kirsty Lorna Morton Schlumberger Search for other works by this author on: This Site Google Scholar Magdy Samir Osman; Magdy Samir Osman Schlumberger Search for other works by this author on: This Site Google Scholar Stephen Anthony Kew Stephen Anthony Kew Xcite Energy Resources Ltd Search for other works by this author on: This Site Google Scholar Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, Alberta, Canada, November 2005. Paper Number: SPE-97898-MS https://doi.org/10.2118/97898-MS Published: November 01 2005 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Morton, Kirsty Lorna, Osman, Magdy Samir, and Stephen Anthony Kew. "Heavy Oil Uncertainties Facing Operators in the North Sea." Paper presented at the SPE International Thermal Operations and Heavy Oil Symposium, Calgary, Alberta, Canada, November 2005. doi: https://doi.org/10.2118/97898-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE International Thermal Operations and Heavy Oil Symposium Search Advanced Search AbstractRising oil price and demand has led to increased effort to develop reservoirs in the North Sea that were previously considered uneconomical by major operators. The recent DTI 'Promote' licensing initiative has encouraged smaller oil companies to apply for exploration/appraisal acreage on a limited financial commitment basis for two years before initiating a more traditional work program.Companies using this option to develop heavy oil reservoirs in the North Sea, many of which were discovered in the 70's, face a number of uncertainties traditionally associated with heavy oil. These include the determination of density and live oil viscosity at reservoir temperature where no clear correlation exists and the determination of reservoir properties from a limited range of historical data. In the offshore environment heavy oil developments are further complicated by the high front-end costs, limited reservoir size and uncertainty in geology and productivity. Only four of the heavy oil fields discoveries on the UK Continental Shelf (UKCS) have reached development and we review these fields to illustrate the challenges.Many of the reservoir and fluid uncertainties can be addressed with modern logging and analysis methods and recommendations for data gathering campaigns in these environments are provided. The technological challenges of an offshore heavy oil development can be met with advances in sand control, ESP technology and EOR techniques. Combined together these solutions provide more accurate production forecasts, which help the economics of developing the resource to be better understood.The proposed appraisal and development of a heavy oil field situated in Block 9/3b is used as a case study to highlight the challenges faced by operators in the development of heavy oil fields in the North Sea. Re-evaluation of historical data was used to develop a range of production forecasts that fully capture the potential and risk of the development.IntroductionHeavy oil (HO) is currently viewed as one of the most important sources of oil available to meet future demand in markets currently served by the North Sea. The UK DTI estimate that there is 9.2 billion barrels of heavy oil in place in the UKCS, equivalent to half the conventional oil in place in the region. Conventional UKCS oil production is expected to decline to approximately half the current production within the next seven years1 and heavy oil is seen as a vital resource to help fill in increasing gap in demand and production. Various initiatives, such as Promote licenses, have been put in place to encourage exploration of heavy oil plays.The Promote license initiative follows the following pattern. The initial term is divided into two year blocks; the first 'Promote period' is available at a 90% discount and the second two years requires a payment of the full fee. At this stage the prospect must be drilled or dropped. A second term is then available to the operator on traditional terms. By limiting the financial commitment in the first two years, operators are encouraged to investigate fields that traditionally fall short of large operator metrics.Many of the heavy oil fields on the UKCS were discovered in the 1970's. However, at that time, technology did not exist to meet the challenges to produce a sufficiently high oil rate over for sufficient time to make a development commercially attractive, particularly in a high cost, offshore environment.The aim of this paper is to highlight the particular challenges in the North Sea and, through a review of current developments, illustrate how these challenges are met. A case study of a Block 9/3b currently under appraisal illustrates how recent technology can be used to reduce the risk associated with this type of development. Keywords: heavy oil, appraisal, determination, seismic data, completion, xcite energy resource ltd, completion fluid, heavy oil field, spe, operator Subjects: Reservoir Characterization, Improved and Enhanced Recovery, Formation Evaluation & Management This content is only available via PDF. 2005. SPE/PS-CIM/CHOA International Thermal Operations and Heavy Oil Symposium 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)0.000
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 score0.026
Threshold uncertainty score0.268

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 head0.018
GPT teacher head0.260
Teacher spread0.241 · 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".

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Citations0
Published2005
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Has abstractyes

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