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Record W2973448792 · doi:10.2118/196169-ms

Sub-Surface Driven Connectivity Descriptions in the Montney and the Duvernay Inform the Applicability of Single-Point Versus Multi-Point Well Architectures

2019· article· en· W2973448792 on OpenAlexaff
Ben Stephenson, T. Bai, Mathew Fay, Earl Galan, Jeff MacDonald, Ryan Carduner

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2019
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsGeologyPoint barPoint (geometry)MicroseismContext (archaeology)Petroleum engineeringSeismologyPaleontologyGeometryMathematicsFluvial

Abstract

fetched live from OpenAlex

Abstract A single-point entry completion architecture has been implemented in several hydraulically stimulated resource plays across North America. The objective is to understand whether the innate properties of the rock and what we can diagnose about how it hydraulically fractures can inform the question of applicability of single-versus multi-point completion designs. Wells were treated using a single-point entry design in the Montney and the Duvernay and an assessment of well performance was carried out. Multiple diagnostic pads have been carried out over several years in both formations, including microseismic and geochemical fingerprint data allowing for a general characterization of the gross geometry and connectivity. Initial results from a fiber are available in the Montney with a single point completion design. The fracture diagnostic data was compiled and described in the context of the nine main sub-surface controls on the connectivity. In the Montney, it is relatively clear how completion intensity changes, like stage length, in single-point entry wells change the production performance outcome. In the Duvernay, there is significantly more uncertainty. This contrast contributed to the decision to treat several follow-up pads in the Montney via a single-point entry design, whereas a multi-point plug and perf completion is preferred for the Duvernay wells. Costs and stage isolation are considerations, but one other contributing explanation is that the dominantly planar fracture geometry in the Montney enables each stage to contribute proportionally, thus ensuring the stimulation distribution effectiveness from the near-to the far-field. The dry-gas area of the Montney is very stiff, with an absence of natural fractures, a paucity of faults, no containment issues and no significant frac barriers. Conversely, in the Duvernay, the inherent complexity in the fracture geometry complicates the stimulation distribution effectiveness in the far-field. Furthermore, the lower mobility of a liquids-rich hydrocarbon system probably benefits from the potentially tighter frac spacing, possible in a multi-cluster design, even with a probable increase in non-uniformity over single-point. It is hypothesized that in formations that develop complex fracture geometries, ‘putting all your eggs in one basket’ with a single-point entry design, needs to be assessed along with the other value drivers for the well architecture selection.

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)0.000
metaresearch head score (Gemma)0.001
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 score0.041
Threshold uncertainty score0.082

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0040.000

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 head0.016
GPT teacher head0.232
Teacher spread0.215 · 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

Citations0
Published2019
Admission routes1
Has abstractyes

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