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Record W2991400340 · doi:10.2118/191575-pa

Eagle Ford Huff ‘n’ Puff Gas-Injection Pilot: Comparison of Reservoir-Simulation, Material Balance, and Real Performance of the Pilot Well

2019· article· en· W2991400340 on OpenAlex
Daniel Orozco, Alfonso Fragoso, Karthik Selvan, Graham Noble, Roberto Aguilera

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsNexen (Canada)University of Calgary
Fundersnot available
KeywordsOil shalePetroleum engineeringEagleHydraulic fracturingShale oilReservoir simulationNatural gasVolume (thermodynamics)Balance (ability)Dry gasMaterial balanceEnvironmental scienceTight oilGeologyChemistryEngineeringWaste managementPhysicsChromatographyThermodynamics

Abstract

fetched live from OpenAlex

Summary In this study we compare real data from an Eagle Ford Shale huff ‘n’ puff (H&P) gas-injection pilot with reservoir simulation and tank material-balance calculations. The comparison is good and supports the conclusion that oil recovery from the Eagle Ford (and likely other shales) can be increased significantly using H&P. For H&P to work, the injected gas and the in-situ oil in the shale must be contained vertically and laterally following hydraulic fracturing. Containment is critical for the success of H&P. Containment implies that the injected gas flows into the hydraulic fractures, penetrates the tight matrix, and does not escape or leak outside the target stimulated reservoir volume (SRV). Vertical and lateral containment exists in the Eagle Ford as demonstrated previously (Ramirez and Aguilera 2016) with an upside-down distribution of fluids: Natural gas is at the bottom of the structure, condensate in the middle, and oil at the top. Two different matching and forecasting approaches are used in this study: reservoir simulation and tank-material-balance calculations. The results show a good history match of primary recovery and secondary recovery by H&P in the pilot well. The history match is good in the case of both reservoir simulation and tank material-balance calculations. Once a match is obtained, the simulation and material balance are used to forecast secondary recovery over a period of 10 years with sustained H&P injection of dry gas. The results indicate that dry-gas H&P can increase oil recovery from the Eagle Ford Shale significantly. Under favorable conditions, oil recovery can be doubled and even tripled over time compared with the primary recovery. The addition of heavier ends to the H&P gas injection can increase oil recovery even more, putting it on par with recoveries in conventional reservoirs. The benefit of H&P occurs in the case of both immiscible and miscible gas injection. The H&P benefits can likely be also obtained in other shale reservoirs with upside-down containment of dry gas, condensate, and oil. The novelty of this work is the combined use of reservoir simulation and tank material-balance calculations to match the performance of an H&P gas-injection pilot in the Eagle Ford Shale of Texas. We conclude that oil recoveries can be increased significantly by H&P.

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)0.001
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 score0.029
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.021
GPT teacher head0.268
Teacher spread0.247 · 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