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Record W4231963390 · doi:10.2118/2009-154

Montney Fracturing-Fluid Considerations

2009· article· en· W4231963390 on OpenAlexaboutno aff
Robert S. Taylor, Gordon McIntosh, Randy Litun, Darren Munn, Brant Bennion, Michael Piwowar, Glen Fyten, Roch Romanson, Ottmar Hoch

Bibliographic record

VenueCanadian International Petroleum Conference · 2009
Typearticle
Languageen
FieldMedicine
TopicTrauma Management and Diagnosis
Canadian institutionsnot available
Fundersnot available
KeywordsFracturing fluidGeologyPetroleum engineeringComputer science

Abstract

fetched live from OpenAlex

Abstract The Montney gas reservoir has become a critically important component of current western Canadian gas supply and offers exciting future potential. However, this reservoir often presents variable and unique stimulation challenges. Unlike reservoirs that display little water sensitivity, such as the U.S. Barnett Shale and possibly the Muskwa in the N.E. B.C. Horn River Basin, recovery of water-based fluids in the Montney can be a key consideration in achieving economic production rates. The use of water-based fracturing fluids in low-permeability reservoirs can result in loss of effective frac half-length caused by phase trapping associated with the retention of the introduced water-based fluid into the formation. This problem is increased by the water-wet nature of most tight-gas reservoirs (where no initial liquid-hydrocarbon saturation is or ever has been present) because of the strong spreading coefficient of water in such a situation. The retention of increased water saturation in the pore system after the injection of water-based completion fluids can restrict the flow of produced gaseous hydrocarbons, such as methane. Capillary pressures of 10 to 20 MPa, or much higher, can be present in low-permeability formations at low water-saturation levels. Inability to generate sufficient capillary-drawdown force using the natural reservoir-drawdown pressure can result in extended fluid-recovery times or permanent loss of effective fracture half-length. Furthermore, use of water in subnormally saturated reservoirs, where much of the connate water has been removed by long-term evaporation effects associated with gas migration, might also reduce permeability and associated gas flow through a permanent increase in water saturation of the reservoir. Secondary costs, such as rig time for swabbing, can add to the negative economic impact. The Montney is found to be a dry-gas reservoir in some areas, transitioning to an oil reservoir in other areas. Because of this, it would not be surprising to encounter retrograde condensate production through the transition areas. In such a case, if sufficient drawdown pressure is applied to reduce reservoir pressure below the dew point, liquid hydrocarbons might condense from the produced gas phase, resulting in two-phase flow and potential trapping of the hydrocarbon liquid phase. Also, some areas of the upper Montney exhibit reservoir pressures in the 30-MPa range, whereas other areas exhibit lower pressures in the 17- to 21-MPa range. The same drawdown on a lower-pressured reservoir could therefore result in condensate condensing from the gas phase, where it would not have in the higher-pressured reservoir. If a third aqueous fracturing fluid is introduced, three-phase flow might occur. The resulting reduced relative permeability to gas might drastically reduce production rates. Also, emulsion-formation potential exists, which could present an additional reduction in fluid flow and recovery. Choice of fracturing fluid must be carefully determined for each area of the Montney, balancing economics with production. It is important to always keep in mind that key reservoir properties can vary dramatically in the Montney, both as a function of geographic location and depth. This paper presents lab test results of regained methane permeability versus drawdown pressure and contact time with Montney core under representative reservoir conditions. Water, foamed water, and hydrocarbon-based fracturing fluid systems are evaluated.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.664
Threshold uncertainty score0.997

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)0.0050.000

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 head0.030
GPT teacher head0.268
Teacher spread0.239 · 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.

Study designObservational
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

Citations11
Published2009
Admission routes1
Has abstractyes

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