MétaCan
Menu
Back to cohort
Record W2109819369 · doi:10.2118/2009-046

Impact of Well Configuration on Performance of Steam-Based Gravity Drainage Processes

2009· article· en· W2109819369 on OpenAlexaffabout
Mohamed Rajab Tamer, Ian D. Gates

Bibliographic record

VenueCanadian International Petroleum Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsUniversity of Calgary
FundersMinistry of Education, Libya
KeywordsSteam-assisted gravity drainageDrainageComputer scienceEnvironmental sciencePetroleum engineeringGeologyMaterials science

Abstract

fetched live from OpenAlex

Abstract The volume of heavy oil and bitumen in the oil sands deposits in Western Canada is similar to that of conventional crude oil in the Middle East. This resource is immense but is difficult and energy intensive to extract because the viscosity of the oil is high, typically over 100,000 to 1,000,000+ cP at original reservoir conditions. Current commercial thermal recovery processes used are Steam-Assisted Gravity Drainage (SAGD) and Cyclic Steam Stimulation (CSS). These methods are both energy intensive, emit significant amounts of carbon dioxide to atmosphere, and use large volumes of water to recover the oil. In this work, the focus is on steam-based gravity drainage processes. It has been demonstrated that operating strategy can be altered to improve SAGD performance but it is not clear how well configuration can be changed to improve recovery, energy intensity, thermal efficiency, water use, and flue gas emissions. This paper examines the impact of position and geometry of steam injectors on the performance of steam-based gravity drainage processes in a heterogeneous reservoir. Different injection well configurations including single horizontal (typical SAGD), offset SAGD, and vertical/horizontal well combinations have been evaluated by using a detailed, three-dimensional, geostatistically-populated, large-scale thermal reservoir simulation model derived from core data examinations of the Dover pilot site. The research reveals how injection well configuration impacts energy delivery to the reservoir, thermal efficiency, and how it changes the evolution of the steam conformance zone and oil flow dynamics in the reservoir. The results suggest that several vertical injectors have the potential to deliver steam more efficiently than a single horizontal injector. Introduction In the province of Alberta, Canada, the volume of oil sands as reported by Energy Resources and Conservation Board (ERCB) is about 2.7 billion cubic meters1. Nevertheless, despite their abundance, these oil sands are very viscous and essentially immobile at reservoir conditions. Currently, most in situ recovery processes used to recover oil sands are steambased. One commercial process is the Steam-Assisted Gravity Drainage (SAGD) method which has been used to mobilize and improve the recovery of oil sands by injecting steam into a horizontal well placed above a horizontal producer2,3,4. There are several SAGD projects currently in operation and being developed in the Athabasca area1. However, variability in performance is large; there are many SAGD wellpairs that have performed with low production rates and thermal efficiency1. This is usually a result of reservoir geology and operating strategy. It is required that SAGD or SAGD-variants are robust, that is, they are geotolerant, so that they can be tuned to operate with reasonable thermal efficiency in geologically-diverse oil sands reservoirs. There are a number of design issues that need to be understood to develop and improve the performance of SAGD. Some examples are well configurations and operating conditions such as steamtrap control and injection pressure. Well configurations and its impact on steam-based gravity drainage processes is the main topic of this paper.

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 score0.234
Threshold uncertainty score1.000

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 head0.009
GPT teacher head0.229
Teacher spread0.220 · 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

Citations8
Published2009
Admission routes2
Has abstractyes

Explore more

Same venueCanadian International Petroleum ConferenceSame topicHydraulic Fracturing and Reservoir AnalysisFrench-language works237,207