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Record W4232119116 · doi:10.2118/2009-144

Drilling Challenges in the Bitumen Saturated Grosmont Formation

2009· article· en· W4232119116 on OpenAlexaff
S. E. Arseniuk, D.L. Becker, K.R. Barrett, D. Keller

Bibliographic record

VenueCanadian International Petroleum Conference · 2009
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsLaricina Energy (Canada)
Fundersnot available
KeywordsAsphaltPetroleum engineeringDrillingComputer scienceGeologyMaterials scienceComposite materialMetallurgy

Abstract

fetched live from OpenAlex

Abstract The Upper Devonian Grosmont formation, located in the West Athabasca Oil Sands Deposit, contains an estimated 318 billion barrels of bitumen. The reservoir is a heavily karsted and fractured, bitumen-saturated dolomite with up to 38% porosity and permeabilities commonly measured in the Darcies. These properties make the Grosmont an excellent candidate for Steam Assisted Gravity Drainage (SAGD). Grosmont SAGD development will be exposed to similar operating conditions as McMurray SAGD projects, and will have similar logistics, well construction and materials challenges. However, there are many additional challenges, including severe loss circulation, that further complicate well design. This paper presents the challenges experienced by Laricina Energy, drilling Grosmont wells at Saleski and Burnt Lakes over the last three seasons. It will also address additional areas for future research and development in the drilling of vertical and horizontal wells. Introduction The Athabasca Deposit is recognized for its oil sands, which have received a great deal of attention because of their enormous bitumen reserves. Most of the focus has been put on exploiting the McMurray sands; however a large resource of bitumen is also present within the Devonian carbonate. The Grosmont formation alone is estimated to contain 318 billion barrels of bitumen and significant additional bitumen resources exist in the overlying Ireton and Winterburn formations. High porosities, permeabilities, oil saturations, and pay thickness make the Grosmont an attractive reservoir. The Grosmont has been sub-divided into four units, of which the upper two, the Grosmont C and D are bitumen bearing on Laricina's leases at Saleski(1). The bitumen bearing interval is approximately 50m thick and the net to gross pay ratio commonly exceeds 90%. The Grosmont Formation has been subjected to an intense period of karsting and carbonate dissolution that has resulted in extensive leaching and porosity development on a massive scale. The reservoir rock is highly fractured, and consists of interbedded porous carbonate sandstones, vuggy dolomites and dolomite breccias. Breccia intervals have exceptionally high porosity and permeability. Examination of core from many brecciated intervals reveals the presence of angular dolomite rock fragments that appear to float in a matrix of fine dolomite sediment and bitumen. Porosities are typically 20–35% (up to 38%) and permeabilities are commonly measured in the Darcies. The Grosmont is slightly under-pressured, at approximately 1400 kPa. Most of the techniques used for the production of bitumen rely on heating the formation to temperatures typically in excess of 200 °C to reduce bitumen viscosity, although solvent processes may be an effective way to reduce this temperature. To date, Steam Assisted Gravity Drainage (SAGD) has emerged as the most popular recovery technique and it is being implemented at several projects. These techniques should also be applicable to the carbonate formations. Laricina plans to use SAGD technology in combination with solvents to recover bitumen from the Grosmont. Through the 1970s and 1980s, several thermal pilots were conducted on the bitumen deposits of the Grosmont formation, including Unocal's Buffalo Creek (2).

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 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 score0.313
Threshold uncertainty score0.991

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)0.0000.000

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 head0.025
GPT teacher head0.206
Teacher spread0.181 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations3
Published2009
Admission routes1
Has abstractyes

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