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Record W6959851688 · doi:10.11575/prism/39817

Geological Characterization and Evaluation of Reservoir Quality in The Montney Formation in West-Central Alberta

2022· other· en· W6959851688 on OpenAlexaboutno aff

Bibliographic record

VenuePRISM (University of Calgary) · 2022
Typeother
Languageen
FieldAgricultural and Biological Sciences
TopicPlant pathogens and resistance mechanisms
Canadian institutionsnot available
Fundersnot available
KeywordsFaciesPetrographySiltstoneDolomiteWell loggingReservoir modelingSedimentary rock

Abstract

fetched live from OpenAlex

Hydrocarbons hosted in low-permeability siltstones of the Montney Formation in western Canada are currently being exploited with multi-staged fractured horizontal wells. However, a significant challenge for development is effectively targeting zones for lateral placement and hydraulic fracture stimulation within the typically thick (200-350 m) gross Montney interval. Moreover, at the vertical resolution of standard well logs, the Montney display limited variability, with significant cm-scale changes in geological properties –which can affect reservoir quality– being undetectable. Therefore, this thesis, focused on the Kakwa Field in west-central Alberta, presents a comprehensive characterization of small- and large-scale variations in geological properties using core and drill cutting samples. A high-resolution data set (2.5 cm spacing), including profile measurements of elemental composition, permeability, and rock hardness measured on a complete Montney core, led to the identification of potential geological controls on reservoir quality. The presence of fine-grained laminations (organic-rich), dolomite and anhydrite- cementation, and the abundance of clays, pyrite, and organic matter, have a negative effect on the permeability of Montney reservoirs. The high-resolution data set also allowed the identification of organic-rich mudstone beds throughout the Middle Montney member. Although the organic-rich mudstone facies are interbedded with siltstone facies throughout the upper Middle Montney, they have been generally overlooked due to their small thickness (<10 cm). Through the integration of detailed sedimentologic core descriptions, petrographic evaluations, and laboratory analyses, significant findings were made from the organic-rich mudstone beds: 1) they host primary organic matter (kerogen Type II) with petroleum generative potential. Hence, organic-rich mudstone beds are proposed as partial contributors to the hydrocarbons hosted in relatively organic-lean adjacent siltstone beds; 2) based on sedimentological evidence (e.g., poorly sorted and clay-rich matrix, lack of sedimentary structures), their deposition is associated with hypopycnal flows, highlighting the importance of fluvial processes in the sediment transport of the Montney Formation; 3) they have low hardness (which can be translated into low stiffness and/or rock strength), and, when interbedded with higher-hardness beds, can potentially act as weak interfaces causing blunting of fractures, thus impacting hydraulic fracture growth. The observations gathered from core data were directly applied in a case study that showcases the integration of geological, petrophysical, and geomechanical properties derived from drill cutting samples, well logs, and drilling data, to identify superior reservoir quality intervals along a Montney horizontal well. Significant m-scale heterogeneities were observed in reservoir properties along the 2.5 km length of the well. Superior reservoir quality intervals were associated with predominantly massive, porous siltstone facies, and relatively inferior reservoir quality intervals were associated with either dolomite-cemented facies or laminated siltstones. The primary outcomes from this characterization served as input for a semianalytical model built to predict hydraulic fracture stage performance (as evaluated from predicted hydrocarbon production). Motivated by the importance of rock types to reservoir quality characterization along horizontal wells, an image processing workflow to identify, classify, and quantify rock types using SEM images of drill cuttings is proposed; importantly, a fully labeled data set containing more than 16,000 SEM images of drill cuttings is open-sourced. Lastly, a laboratory-based study was conducted to compare the effectiveness of three methods to clean drill cuttings contaminated with oil-based muds. The reviewed cleaning methods involve the use of 1) an organic solvent (dichloromethane), 2) a furnace (180 °C), and 3) a trademark surfactant. Overall, solvent cleaning was determined to be the best method to remove drilling mud contamination, including the oil and mud fines.

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)0.000
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.132

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.001
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 head0.026
GPT teacher head0.212
Teacher spread0.186 · 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
Published2022
Admission routes1
Has abstractyes

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