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Record W1970785046 · doi:10.2118/08-07-10-cs

Conditions Favourable to Infill Drilling in Waterfloods in Sandstone Reservoirs Containing Medium/Heavy Oils

2008· article· en· W1970785046 on OpenAlexaboutno aff
A.K. Singhal, S.J. Springer

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2008
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsInfillGeologyDrillingPetroleum engineeringOil in placeGeotechnical engineeringPetroleumEngineeringCivil engineeringPaleontology

Abstract

fetched live from OpenAlex

Abstract Production histories of four waterfloods, each with several infill wells, were examined to identify conditions favourable to infill drilling in sandstone reservoirs containing heavy/medium oils under waterflood. The dominant role of reservoir heterogeneity was inferred from the nature of performance of newer and older infill wells. Due to these heterogeneities, some of the mobile oil contained within the reservoir is not drained by the older wells, but infill wells could drain a portion (up to 25%) of this oil. Based on the cases studied, conditions favourable for infill wells were:Current oil rates of older wells greater than 3 m(3)/d and watercut less than 75%.Original Oil-in-Place (OOIP)/well for the reduced spacing greater than 80 E3m(3) and total recovery factor (primary + waterflood) greater than 25%. It is recommended that these criteria be validated by further technical and economic studies. Introduction Infill drilling was initially proposed as a means of draining incremental reserves, besides accelerating established oil drainage, based mainly on geological considerations and simulation studies(1–4) mostly dealing with the carbonate reservoirs of Texas. This work aims to obtain clues for identifying attractive infill opportunities in clastic reservoirs containing medium/heavy oils under waterflooding. Our expectation was that, with the growing database on performance of infill wells of recent years, some of the initial premises could be revisited and a fresh attempt could be made to obtain additional insights. Intuitively, as infill wells are brought on stream, they would accelerate oil production, depending on the amount of mobile oil remaining within the drainage region. They may also be able to drain oil from certain poorly connected parts of the reservoir that would otherwise be left unrecovered. They should, therefore, add value to the ongoing waterflood. It goes without saying that value added (returns) should be consistent with the risks (investment) involved. This study focuses on production performance of infill wells in four different waterfloods in heavy/medium oil sandstone reservoirs of Alberta, Canada. It has been suggested(3) that infill wells enable better pattern control and connectivity in waterfloods, shorten life and improve areal and vertical sweep by the injected water. Therefore, infill well's performance should largely depend upon reservoir heterogeneity, besides factors such as mobility ratios, average ultimate recovery factors and maturity of exploitation reflected in the prevailing oil rates and watercuts. Reservoir heterogeneity in the vertical direction is usually characterized by Dykstra-Parson's coefficient. For lateral or aerial heterogeneity, a method based on performance of previous infill wells was recently proposed(5, 6). This method involves plotting cumulative oil production versus frequency data for previous infill wells from the same (or analogous) project on a lognormal graph, and examining the slope of the curve around the median (50% probability). The basic assumption here is that reserves from contemporaneous infill wells, like the distribution of many geological parameters, should follow a lognormal trend. However, significant deviations from the lognormal distribution are usually observed (e.g. Figure 1).

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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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.445
Threshold uncertainty score0.958

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0080.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.017
GPT teacher head0.250
Teacher spread0.232 · 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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Citations2
Published2008
Admission routes1
Has abstractyes

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