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Record W2904927092 · doi:10.2118/1218-0057-jpt

Waterflooding With Active Injection-Control Devices Improves Oil Recovery

2018· article· en· W2904927092 on OpenAlexaboutno aff
Chris Carpenter

Bibliographic record

VenueJournal of Petroleum Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringCompletion (oil and gas wells)Tight oilWater injection (oil production)Well controlOil in placeGeologyHydraulic fracturingOil productionFossil fuelPetroleumEnvironmental scienceEngineeringMechanical engineeringDrillingWaste management

Abstract

fetched live from OpenAlex

This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 189824, “Strategic Waterflood Optimization With Innovative Active Injection-Control Devices in Tight Oil Reservoirs,” by Kyle Barry, SPE, Ryan McDowell, SPE, and Kevin McArthur, Crescent Point Energy, and Anton Kozin, SPE, Trena Marie Stretch, Avo Keshishian, and Jawad Farid, Schlumberger, prepared for the 2018 SPE Canada Unconventional Resources Conference, Calgary, 13–14 March. The paper has not been peer reviewed. This paper presents the implementation of an approach for improving oil recovery by water-injection optimization using injection-control devices (ICDs) in unconventional reservoirs. In late 2016, a trial campaign began in southeastern Saskatchewan that applied ICDs in relatively low-flow-rate environments to offset production decline and improve recovery. Early-term results show that an improvement in oil recovery greater than 25% over typical waterflood configurations is possible. Introduction To offset production decline caused by normal pressure decline and reservoir drainage, secondary recovery using water injection has been administered in three Saskatchewan tight oil plays. This study will be focused on the Bakken formation, the area with the most-complete historical data set available to the authors. The original completion and well-spacing plan has resulted in occasional direct water channeling from injection to production wells. This is believed to be caused by hydraulic fracturing. In some cases, this communication has limited waterflood sweep efficiency and is referred to as short-circuiting of injection fluid. Chemical and mechanical diversion techniques have been implemented to address short-circuiting with varying degrees of success. Field Development The simplest means to waterflood a multi stage fractured well is to reverse the direction of flow and to bullhead water from the surface without diverting or compartmentalizing fluid flow. Because the water follows the path of least resistance, nonuniform fluid injection along the wellbore and into the formation may occur. In some instances, short-circuiting of producing wells through fracture paths may occur. Using distributed temperature sensing (DTS), the operator was able to investigate wells that were suspected of short-circuiting or channeling. Many attempts were made to redirect flow from the paths of least resistance by use of various viscous fluids and solid diverters. The effectiveness of these treatments was inconsistent and, in some cases, required multiple applications. The operator began investigating the application of mechanical diversion and isolation of sections of the wellbore to enable physical control of flow rates into different areas along the lateral wellbore. Compartmentalization With ICDs The nozzle diameter of ICDs can be adjusted to compensate for variations in reservoir and fracture injectivity resulting from variable permeability effects and frictional pressure losses along the wellbore, known as the heel-to-toe effect. The installations can be run in openhole configurations and within cemented or noncemented tubulars.

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 score0.322
Threshold uncertainty score0.453

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 head0.005
GPT teacher head0.226
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

Citations1
Published2018
Admission routes1
Has abstractyes

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