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Record W4224250131 · doi:10.2118/209243-ms

Enhanced Oil Recovery Screening of Oil Fields in Central California for ASP Alkali Surfactant Polymer

2022· article· en· W4224250131 on OpenAlexaboutno aff
Thomas J. Hampton

Bibliographic record

VenueSPE Western Regional Meeting · 2022
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsRanking (information retrieval)Scope (computer science)Petroleum engineeringEnhanced oil recoveryProcess (computing)Fossil fuelEnvironmental scienceComputer scienceDatabaseGeologyEngineeringWaste managementInformation retrieval

Abstract

fetched live from OpenAlex

Abstract Objectives/Scope This paper demonstrates the potential of alkali surfactant polymer (ASP) within the Central California Oil Fields, which covers Kern, Tulare, and Fresno Counties. Typically, enhanced oil recovery (EOR) screening is performed across a wide range of processes and is applied to individual reservoirs on a case-by-case basis. This study focuses on a single EOR ASP process across multiple fields and pools specific to Central California. Methods, Procedures, Process Reservoir characteristics and Canadian analogs were used to screen for the ASP potential in Central California. Reservoir characteristics data were digitized and taken from what is locally known as the "Gold Book" of Central California (Volume 1, 1998, published by the California Division of Oil & Gas, subsequently renamed CalGEM (California Geologic Energy Management Division). The book contains data for 137 oil and gas fields with 605 pools. Various ASP screening methods and analogs were applied to this dataset. Candidates were then ranked for detailed future analyses. Results, Observations, and Conclusions Screening resulted in the identification of 166 of the 605 pools that passed the Taber and Delamaide screening methods and compared well to analogous Canadian successful commercial ASP projects. Fields were then ranked according to various reservoir properties, size of potential recovery, and location (access to chemicals). The top five, with supporting data, are shown. Graphs and maps were used to illustrate the top-ranked pools along with their locations. Novel/Additive Information The results of initial screening and ranking of Central Californian pools illustrate its potential for ASP applications. Although there have been some ASP studies and pilots conducted in the San Joaquin Basin oil fields, the results are not in the public sphere. Some data have been published by CalGEM on two successful ASP pilots in the Shallow Oil Zone of the Elk Hills Oil Field, California. This study was performed to show possible application of ASP in 166 pools within the 605 pools in the San Joaquin Basin by using publicly available information to identify oil fields that warrant further detailed investigations of oil chemistry, core analysis, reservoir simulation, risk assessments, and in-depth economic studies.

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 categoriesMeta-epidemiology (narrow)
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 score0.557
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 head0.017
GPT teacher head0.235
Teacher spread0.219 · 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.

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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