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Record W2017897956 · doi:10.2118/2007-158

TINBOP Cyclic Steam Injection Enhances Oil Recovery in Mature Steamfloods

2007· article· en· W2017897956 on OpenAlexaboutno aff
Christophe Morlot, D. D. Mamora

Bibliographic record

VenueCanadian International Petroleum Conference · 2007
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsCitationLibrary scienceComputer scienceEngineeringInformation retrieval

Abstract

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Abstract In a previous paper (SPE/PS-CIM/CHOA 97850), we presented our findings on a novel cyclic steam injection method that we developed. The Top-Injection Bottom- Production (TINBOP) method consists of injecting steam in the short string and producing fluid from the long string of a well. Our simulation study shows TINBOP increases oil recovery by 57–93% compared to that with conventional cyclic steam injection. In this paper, we present results of our simulation study that compares TINBOP cyclic steam injection against steamflooding, using typical properties of the mature Lombardi reservoir, San Ardo field, California. The field contains heavy oil of 11 °API and insitu viscosity of 3000 cp. A 30?30?20 Cartesian model is used that represents one-eight of a 10-acre inverted 5-spot pattern. A total 37 years are simulated: 17 years under natural depletion followed by 20 years steamflooding or 20 years TINBOP (with the same amount of steam injected). Simulation results indicate TINBOP cyclic steam injection enhances oil recovery to 76% OOIP compared to that with conventional steamflooding, 69% OOIP. The workover cost to convert an existing well to a TINBOP well appears relatively small compared to the gain in oil recovery. Introduction Heavy and extra-heavy oil resources are estimated to be more than 2.5 trillion STB. The vast resources of the Orinoco and Canada extra-heavy oil or bitumen regions are well documented, and offer large targets for in-situ and surface ecovery techniques. Potential recoverable heavy and extraheavy is estimated to be 856 MMSTB with current technology. There are two forms of steam injection, steamflooding or steam drive, and cyclic steam injection or stimulation (CSS) or huff-and-puff. In steamflooding, steam is continuously injected into fixed well patterns of injection wells, while fluids are produced in designated wells. Depending on the reservoir properties and pattern, steamflooding oil recovery factor may be as high as some 60% of original oil-in-place (OOIP) [1]. In cyclic steam injection, the primary objective is to reduce the oil viscosity near the vicinity of the wellbore. Oil recovery factors with CSS are generally lower, typically less than 15% OOIP [1]. Steam Over-Ride The main factor that adversely affects oil recovery under steamflooding is steam over-ride, particularly in mature steamfloods. As shown in Fig. 1, as a result of gravity segregation, the injected steam quickly rises to the top of the reservoir, by-passing the oil below it [1]. The steam is preferentially produced at the production well because of its significantly lower viscosity. In mature steamfloods, the overlying steam region (steam chest) may extend throughout the field. Only a thin layer of oil near the oil-steam interface is directly heated by the steam. This heated oil layer then slowly drains to the production well by gravity. Steam-override is practically unavoidable. The objective of steam management is to maximize oil recovery and minimize steam injection cost. How can we accelerate and increase the recovery of the "cold" oil underlying the steam chest? We have developed a novel method (TINBOP) which attempts to do exactly this.

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.007
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.008
GPT teacher head0.229
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), 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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Citations3
Published2007
Admission routes1
Has abstractyes

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