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Record W2039593663 · doi:10.2118/2008-118

Application of Temperature Observation Wells During SAGD Operations in a Medium Deep Burial Extra Heavy Oil Reservoir

2008· article· en· W2039593663 on OpenAlexaboutno aff
Han Wang

Bibliographic record

VenueCanadian International Petroleum Conference · 2008
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsnot available
Fundersnot available
KeywordsCitationPetroleum engineeringPetroleumEnvironmental scienceGeologyEngineeringComputer scienceLibrary sciencePaleontology

Abstract

fetched live from OpenAlex

Abstract The SAGD pilot test in Liaohe oilfield of China is the first one conducted in the medium-deep extra heavy oil reservoir (650-800 m), using the combination of vertical injectors and horizontal producers. Temperature observation wells play the important role in the understanding of the pilot performance and optimization of the operation process. This paper will present the objectives, principle, interpretation and application of the temperature observation wells in the pilot area. The production problems were identified and solutions were sought to improve the SAGD performance, through the use of data obtained from the observation wells. Introduction This paper is the continuation of CIPC paper 2006–146 presented in 2006. That paper introduced the successful test of the SAGD pilot in a medium-deep extra heavy oil reservoir in China[1]. The pilot has been expanded to include 12 horizontal wells since the presentation of the last paper two years ago. The earlier two wells have reached a daily oil rate of over 100 t/d per well. The current recovery factor is about 27% and the anticipated ultimate recovery is over 60%. Compared with the Canadian SAGD projects, the reservoirs in Liaohe oil field of PetroChina resulted in two difficulties using the SAGD technologies: (1.) reservoir depth exceeds 500 meters (530-810 m) compared to 200–500 meters in Canadian SAGD projects[2], the heat loss from the wellbore is relatively high and this increased the difficulty for injection and production facilities and (2.) the depletion by Cyclic Steam Stimulation (CSS) prior to SAGD application while majority of the Canadian SAGD projects are commenced in the original reservoir conditions. The current recovery factor by CSS in Liaohe is about 20%. Prior depletion by CSS complicates the conversion to SAGD applications and determination of operating parameters due to the altering in the distribution of the remaining oil saturation (Fig 1). To overcome the difficulties associated with the SAGD applications in this reservoir, Lioahe Oilfield Company has taken various measures including the combination of vertical injectors and horizontal producers. The horizontal producers are placed in the lower part of the reservoir between two rows of vertical injectors to maximize the access of remaining oil saturations. A steam separator has been used to achieve high quality steam injection to maintain a quality of over 75% into the reservoir sand face (vertical depth of the reservoir is about 790 m); an over-sized tubing pump has been applied to provide the adequate lift capacity for the producers (peak liquid rate of 500 m3/d per well and the wellhead temperature of 180 °C). The monitoring of reservoir temperature is most important for any thermal processes. The thermal couples are usually used in the thermal recovery process. However, it can not provide the continuous and on time measurements as required by SAGD temperature monitoring. A distributed fiber optical temperature sensor system has been developed in recent years to provide the distributed, continuous and multiple functioned optical temperature measurement system.

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 score0.325
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
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 head0.016
GPT teacher head0.219
Teacher spread0.203 · 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

Citations5
Published2008
Admission routes1
Has abstractyes

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