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Record W2054544343 · doi:10.2523/iptc-14974-ms

Numerical Simulation of ES-SAGD Process in Athabasca Oil Sands with Top Water and Gas Thief Zones

2011· article· en· W2054544343 on OpenAlexafffund
Xia Bao, Zhangxin Chen, Hui Deng, Ziqiang Guo, Song Yu

Bibliographic record

VenueAll Days · 2011
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsOil sandsSteam-assisted gravity drainageGeomechanicsPetroleum engineeringSteam injectionGeologyAsphaltOil fieldEnhanced oil recoveryUnconventional oilGeotechnical engineeringComputer simulationReservoir simulationMechanicsMaterials science

Abstract

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Abstract Overlying top water and gas thief zones have a detrimental effect on the Steam-Assisted Gravity Drainage (SAGD) recovery process since steam penetrates into these zones which results in great heat loss. Due to the presence of these top thief zones, recovering bitumen by the SAGD process has become challenging for the Athabasca oil sands. Numerical simulations, laboratory experiments and field production data have demonstrated that oil production tends to decrease as the depletion of top gas occurs; also, heat loss to the overlying thief zone will be more significant when a top water zone is present. Indeed, SAGD is a coupled geomechanical, thermal and fluid flow problem because continuous steam injection changes reservoir pore pressure and temperature, which can alter the effective stress in-situ. Therefore, to represent the physics of thermal flow and soil geomechanics, a coupled geomechanical simulation that solves the flow and stress equation simultaneously in the reservoir is crucial for modeling the SAGD process. The objective of this paper is to construct a 3D geostatistical model for the Surmont pilot and implement coupled geomechanical modeling for the SAGD process aiming at investigating the impact of dilation and thermal expansion on the surface subsidence and bitumen recovery. Reasonable history match of oil and water rates has been achieved and steam chamber profiles have been conformed to the field data from the observation wells. An Expanding Solvent Steam-Assisted Gravity Drainage (ES-SAGD) process has been investigated on a full field-based heterogeneous simulation model using an optimal solvent mixture. Finally, geomechanical effects on the ES-SAGD process are investigated through an iterative coupling approach. Introduction The negative impacts of top water and gas cap on SAGD performance have been previously presented and discussed in the literature (Good et al. 1997; Nasr et al. 2000; Law et al. 2000). Both experimental and simulation approaches were conducted to determine SAGD steam chamber growth in the presence of a top thief zone. It was observed that the overlying top water and gas thief zones have a detrimental effect on the Steam Assisted Gravity Drainage (SAGD) recovery process since steam penetrates into these zones and results in great heat loss (AEUB, 1998). Thermal SAGD simulations models have been constructed and successfully matched using the computer assisted history-matching approach. The optimization strategies have been proposed in terms of the operating pressure and subcool control. Furthermore, ES-SAGD possibilities have been investigated using different solvent mixture co-injected with steam. Through a sensitivity study, an optimal solvent mixture has been proposed for this case with a top thief zone. SAGD is a coupled geomechanical, thermal and fluid flow problem because continuous steam injection changes reservoir pore pressure and temperature, which can alter the effective stress in-situ. Dilation behavior associated with volumetric strains is triggered by the continuous steam injection, which causes the increase of porosity and permeability. Therefore, the fluid flow behavior must be coupled to the geomechanical behavior of the oil sands. Investigating the interaction between the cap rock integrity, dilation and thermal expansion under the continuous steam injection is the motivation of this study. ES-SAGD Investigation ES-SAGD is the co-injection of small amount solvent additive with steam in the SAGD process. Solvent will condensate at the boundary of the steam chamber and diffuse into bitumen, which will reduce the oil viscosity, yield the higher oil drainage and reduce the amount of steam required.

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 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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.922
Threshold uncertainty score0.155

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.229
Teacher spread0.216 · 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 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
Published2011
Admission routes2
Has abstractyes

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