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Record W4390059997 · doi:10.5419/bjpg2023-0012

APPLICATION OF WATER FLOODING AND WATER ALTERNATIVE GAS (WAG) FLOODING TECHNIQUES IN A CARBONATE RESERVOIR: INTEGRATION OF RESERVOIR AND PRODUCTION SYSTEMS FOR DECISION MAKING

2023· article· en· W4390059997 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueBrazilian Journal of Petroleum and Gas · 2023
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
FundersUniversidade Estadual de CampinasPetrobrasComputer Modelling GroupEnergi Simulation
KeywordsProduction (economics)Petroleum engineeringReservoir simulationBenchmark (surveying)Work (physics)Flooding (psychology)Function (biology)Environmental scienceComputer scienceEngineeringGeology

Abstract

fetched live from OpenAlex

The objective of this work is to evaluate the impact of integration between reservoir and production systems on the decision making for field production development. The authors demonstrated, in a benchmark case, the applicability of water injection (WI) and water alternating gas injection (WAG) techniques for various production systems by proposing a novel methodology. This work explores three optimization approaches: (1) based on the complete model considering integrated systems, (2) for production system based solely on reservoir model and followed by the integration and optimization of production system, and (3) derived from (2) considering subsequent integration and optimization for complete model. In the implementation step, production strategies are applied in a reference model. This work compares production strategies, reservoir performance forecast, and the net present value (NPV) objective function. The integrated models yeild similar objective-function values by utilizing a production system that does not alter the bottom-hole conditions significantly, thereby replicating the behavior observed in the non-integrated model. The results of non-integrated reservoir optimizations should be used with caution for decision-making purposes, as the subsequent integration may cause the changes to the the production forecasts. The differences in reservoir behaviors can be attributed to the changes in the dynamics (movement) of fluids from the reservoir to the wells and the type of recovery mechanism affected by well positioning. The implementation of production strategies in the reference model resulted in lower values of NPV (20% for WI and 60% for WAG) than those obtained in the optimization step. The findings demand caution in the application of closed-loop procedures to prevent biased or inaccurate assessments of decisions made solely based on reservoir models. The application of this work can be considered an import study for Carbon Capture Utilization and Storage (CCUS), as well as for energy transition based on WAG optimization.

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.

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)0.002
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 score0.114
Threshold uncertainty score0.392

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 head0.018
GPT teacher head0.290
Teacher spread0.272 · 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