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Record W2017028829 · doi:10.2118/06-10-01

Completion Operations in Low Permeability Deep Basin Gas Reservoirs: To Use or Not to Use Aqueous Fluids, That is the Question

2006· article· en· W2017028829 on OpenAlexaffabout
G. Coskuner

Bibliographic record

VenueJournal of Canadian Petroleum Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsHusky Energy (Canada)
FundersOrta Doğu Teknik Üniversitesi
KeywordsPetroleum engineeringGeologyPermeability (electromagnetism)Structural basinNatural gasNatural gas fieldDrillingSaturation (graph theory)Fossil fuelWorkoverWater injection (oil production)Tight gasPetrologyDirectional drillingPetroleum reservoirHydraulic fracturingGeomorphologyChemistryWaste managementMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Abstract Many tight gas formations are water-wet and undersaturated where the initial water saturation in the reservoir is less than the capillary equilibrium irreducible water saturation. Using aqueous-based stimulation and workover fluids causes water to be trapped in the near wellbore region, thereby significantly impairing the ability of gas to flow. Therefore, hydrocarbon fluids are better suited for completion operations in such reservoirs. Laboratory data revealing the sensitivity of one such formation to aqueous fluid invasion are discussed and actual field examples are provided in three different formations. Introduction As the oil and gas industry matures and known reserves continue to be depleted, the focus moves towards more challenging environments. One such environment is the Deep Basin area of West Central Alberta where vast reserves of natural gas and associated liquids are present in a number of low permeability reservoirs(1). Similar areas also exist in the U.S., such as the Powder River Basin, Permian Basin, and the Green River Basin. In situ effective gas permeabilities in such reservoirs are in the 0.1 mD range or less. It should be noted that while routine core measurements in the laboratory may indicate permeabilities of up to 1 mD for such reservoirs, the effective gas permeability in the reservoir will be significantly less(2, 3). Although horizontal wells are being used with increasing frequency in exploiting such reservoirs, the vast majority of the wells drilled are vertical wells in the Deep Basin. This is mainly due to the differences in the cost of drilling. A typical horizontal well can be as much as two to four times more expensive than a vertical well for such deep targets. Also, because most horizontal wells are completed barefoot in tight gas reservoirs, the drilling induced damage becomes quite important for the performance of these wells. Therefore, it is critical that a suitable drilling fluid be used in drilling horizontal wells. This was discussed in an earlier article(4). The gas flow rate from a vertical well can be maximized by stimulation. Vertical wells in tight gas formations are usually stimulated by hydraulic fracturing after drilling. Hydraulic fracturing is accomplished by pumping a large volume of fluid mixed with additives and a solid proppant (usually sand) into the formation at high injection rates, cracking the reservoir rock. The fluid is used as a carrier so the proppant can be pumped, and once the proppant has been placed in the fracture, the well is usually flowed back to a tank to recover the carrier fluid. The permeability of the proppant is very high. However, some of the carrier fluid will be imbibed into the freshly exposed matrix rock and remain in place. Depending on the characteristics of the fluid, the permeability of the fracture face may be impaired. The same can also be said for fluids used in workover operations as well. In many low permeability gas reservoirs aqueous fracturing fluids are used due to their cost advantage and safety considerations(5, 6).

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.014
GPT teacher head0.235
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2006
Admission routes2
Has abstractyes

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