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Record W4240862314 · doi:10.2523/100942-ms

Strategies and Techniques for a Giant Sandstone Oilfield Development: A RoadMap To Maximize Recovery

2006· article· en· W4240862314 on OpenAlexaff
Xiaoguang Lu, YuPu Wang, Yongqing Zhang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsGeologyPetroleum engineeringComputer scienceMining engineering

Abstract

fetched live from OpenAlex

Strategies and Techniques for a Giant Sandstone Oilfield Development: A Road Map To Maximize Recovery XiaoGuang Lu; XiaoGuang Lu PetroChina Intl Ltd Search for other works by this author on: This Site Google Scholar YuPu Wang; YuPu Wang Search for other works by this author on: This Site Google Scholar YongQing Zhang YongQing Zhang Search for other works by this author on: This Site Google Scholar Paper presented at the SPE Asia Pacific Oil & Gas Conference and Exhibition, Adelaide, Australia, September 2006. Paper Number: SPE-100942-MS https://doi.org/10.2118/100942-MS Published: September 11 2006 Cite View This Citation Add to Citation Manager Share Icon Share Twitter LinkedIn Get Permissions Search Site Citation Lu, XiaoGuang, Wang, YuPu, and YongQing Zhang. "Strategies and Techniques for a Giant Sandstone Oilfield Development: A Road Map To Maximize Recovery." Paper presented at the SPE Asia Pacific Oil & Gas Conference and Exhibition, Adelaide, Australia, September 2006. doi: https://doi.org/10.2118/100942-MS Download citation file: Ris (Zotero) Reference Manager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex Search nav search search input Search input auto suggest search filter All ContentAll ProceedingsSociety of Petroleum Engineers (SPE)SPE Asia Pacific Oil and Gas Conference and Exhibition Search Advanced Search AbstractDaqing, the largest heterogeneous multi-layer none marine reservoir oilfield in China celebrated its 45thbirthday in Ocotober 2005. Boasting 27 continuous years of plateau oil production over one MMBOD, the largest industry polymer-flooding oilfield in the world, and excellent developing effect, its development strategies and techniques applied provide a road map to maximize oil recovery:Life cycle reservoir studies give insight into reservoir, and providea foundation for plan of development, implementation of infilling, and associated workover jobs such as zonal stimulation, zonal waterplugging.Early reservoir pressure maintenance by internal water flooding maintains reservoir pressure close to its original status, providing sufficient reservoir energy, enabling high and stable production rate for a long period as well as improving recovery.Performance monitoringconducted in the whole process of development, of which, separate layer performance monitoring is one of the most important foundation for in-depth understanding subsurface development potential.Pilot tests are conducted before any key development strategies and measures are applied to ensure their success.Separate layer production/water injection of multi-layer and heterogeneous reservoir and novel completion are the key measures for enhancing poorly drained reservoir water flooding, improvingits sweeping efficiency.Multi-time and progressive infilling drilling develops bypass oil resulting fromthe geological complexities of reservoirs.Widely applying polymer flooding enhances oil recovery by over 10%.Innovativetechnology makesdevelopment of marginal reservoirs/fields economical.Outstanding development of the giant field has proven the validity of above strategies and techniques with an oil recovery factor current at over 51% in the main block.IntroductionMajor challenges facing petroleum industry are to maximize recovery for a mature asset, extend the life of traditional producing areas, to optimize development of a new field as new reserve becomes increasingly complex. The average conventional crude oil recovery quoted in petroleum industry is 35%. However, a 10% incremental recovery translates to about 1.4 trillion barrels of recoverable resources, or roughly an additional 50-year supply of global crude consumption at current rates (Saleri, 2006). The estimate reminds us that there are vast potential resources of hydrocarbons in the world thatare waiting for new technology to tap them. Numerous efforts focusing on matured assets aiming at finding new oil in old reservoir and revitalizing old-field have been made. These efforts emphasize the importance of application of integrated approaches or multidisciplinary reservoir management. However, maximizing oil recovery is not only a system engineering, but also lifecycle process running through various stages of oilfield development from initial development, production increasing and reaching its plateau, to production declining as the oil field reaches the mature state of its development. Keywords: waterflooding, oil field, enhanced recovery, la-sa-xing oil field, separate layer, Upstream Oil & Gas, Placanticline, Pilot Test, polymer flooding, water cut stage Subjects: Improved and Enhanced Recovery, Waterflooding This content is only available via PDF. 2006. Society of Petroleum Engineers You can access this article if you purchase or spend a download.

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: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.494
Threshold uncertainty score0.430

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 head0.014
GPT teacher head0.254
Teacher spread0.240 · 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
GenreMethods

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
Published2006
Admission routes1
Has abstractyes

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