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Record W2284743671 · doi:10.2118/177600-ms

Modelling Foam Displacement in Fractured Carbonate Reservoirs

2015· article· en· W2284743671 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

VenueAbu Dhabi International Petroleum Exhibition and Conference · 2015
Typearticle
Languageen
FieldEngineering
TopicEnhanced Oil Recovery Techniques
Canadian institutionsnot available
FundersCMG Reservoir Simulation Foundation
KeywordsEnhanced oil recoveryDisplacement (psychology)CarbonatePorous mediumPetroleum engineeringMaterials sciencePorosityMechanicsGeologyComposite material

Abstract

fetched live from OpenAlex

Abstract Foam displacement has been employed in several field pilots which report improvement in mobility control, sweep efficiency, delayed gas breakthrough and EOR. However, foam behavior in highly heterogeneous porous media in general and fractured reservoir in particular is not well understood. Effective application of foam for enhanced oil recovery requires a good understanding of physical displacement processes (e.g. adsorption, foam generation, foam decay) at the laboratory and field scale. This is particularly important for the more complex fractured carbonate reservoirs which host over half of the world's remaining conventional oil reserves. We investigate the effect of foam displacement in fractured carbonate reservoirs using numerical simulations tuned to experimental data to compare recovery for different injection strategies at different scales. In the experiments, high quality foam was generated by the injection of surfactant solution and N2 gas either in-situ or prior to injection. A mechanistic Lamella Density model was used to simulate core-scale laboratory experiments and history match the unknown foam parameters. We applied our understanding of foam displacement processes at the core scale to a reservoir model at the inter-well scale where additional heterogeneities were encountered. For this model we used a cross section of highly heterogeneous simulation model of a middle Jurassic carbonate ramp that is an analogue to the Arab D formation in Qatar. We used this model to test the effect of foam injection for different injection mechanisms, analyze the displacement processes, and compare the overall sweep and recovery. Foam injection showed very promising results by diverting the flow from the high permeability fractures to the matrix, allowing for a better sweep efficiency that lead to a noticeable increase in differential pressure. Pre-formed foam yielded a higher recovery (around 78% of OOIP) compared to the in-situ generated foam in the core samples. This might be due to the smooth nature of the fractures leading to fewer snap off sites for foam generation. Varying the foam injection strategies (i.e. pre-formed foam, co-injection, and SAG) resulted in at least a 12% change in recovery compared to conventional water flooding and water-alternating gas injection. Foam quality, foam stability and injection mechanism were all factors that controlled sweep efficiency. Our results illustrate how the laboratory-scale displacement mechanisms could operate on a larger (i.e. inter-well) scale where additional heterogeneities are encountered and the ratio of viscous to capillary and gravity forces changes. Our simulations also demonstrate that uncertainties in parameterizing foam models using experimental data from core floods translate into considerable uncertainties for predicting recovery at the field-scale. Still, foam can be an effective agent to increase oil recovery in fractured carbonate reservoirs by improving sweep efficiency and reducing gravity override.

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)0.000
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 score0.238
Threshold uncertainty score0.618

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 head0.024
GPT teacher head0.243
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