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Record W2930831635 · doi:10.2118/195223-ms

Mechanisms for Huff-n-Puff Cyclic Gas Injection into Unconventional Reservoirs

2019· article· en· W2930831635 on OpenAlexaff
B. Todd Hoffman, J. M. Rutledge

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsCenovus Energy (Canada)
Fundersnot available
KeywordsAdvectionPetroleum engineeringDarcy's lawPenetration (warfare)MechanicsDiffusionFluid dynamicsVolumetric flow rateGeologyEnvironmental sciencePorous mediumGeotechnical engineeringPorosityThermodynamicsEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract Unconventional oil reservoirs such as the Eagle Ford have had tremendous success over the last decade, but challenges remain as flow rates drop quickly and recovery factors are low; thus, enhanced oil recovery methods are needed to increase recovery. Interest in cyclic gas injection has risen as a number of successful pilots have been reported; however, little information is available on recovery mechanisms for the process. This paper evaluates oil swelling caused by diffusion and advection processes for gas injection in unconventional reservoirs. To accurately evaluate gas penetration into the matrix, the surface area of the hydraulic fractures needs to be known, and in this work, three different methods are used to estimate the area: volumetrics, well flow rates and linear fluid flow equations. Fick's law is used to determine the gas penetration depth caused by diffusion, and the linear form of Darcy's law is used to find the amount from advection. Then, with the use of swelling test information from lab tests, we are able to approximate the amount of oil recovery expected from cyclic gas injection operations. During the gas injection phase, gas from the fractures can enter the matrix by both advection (Darcy driven flow) and diffusion. We estimate that over 200 million scf of gas can enter the matrix during a 100 day injection/soak period. Using typical reservoir and fluid parameters, it appears that 40% is due to diffusion and 60% is due to advection. Sensitivity analysis shows that these numbers vary considerable based on the parameters used. Analytical models also show that during a 100 day production timeframe, over 14,000 stock tank barrels (STB) of oil can be produced due to huff-n-puff gas injection. Both gas injection and oil recovery amounts are compared to recent Eagle Ford gas injection pilot data, and the model results are consistent with the field pilot data. By determining the relative importance of the different recovery mechanisms, this paper provides a better understanding of what is happening in unconventional reservoirs during cyclic gas injection. This will allow more efficient injection schemes to be designed in the future.

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 score0.387
Threshold uncertainty score0.989

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)0.0010.000

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 head0.006
GPT teacher head0.218
Teacher spread0.211 · 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

Citations33
Published2019
Admission routes1
Has abstractyes

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