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Record W1983441163 · doi:10.2118/170109-ms

A Case Study in the Application of Bitumen Geochemistry for Reservoir Characterization in SAGD Development

2014· article· en· W1983441163 on OpenAlex
J. N. Sereda, Bruce R. James

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueSPE Heavy Oil Conference-Canada · 2014
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsSuncor Energy (Canada)
FundersSuncor Energy Incorporated
KeywordsBaffleAsphaltOil shaleGeologyOil sandsPetroleum engineeringOil fieldSteam-assisted gravity drainageGeochemistryGeotechnical engineeringEngineeringMaterials science

Abstract

fetched live from OpenAlex

Abstract Predicting the presence of sealing or baffling shale layers in a reservoir is important as they are detrimental to the steam assisted gravity drainage (SAGD) recovery process widely used in the Athabasca oil sands. Baffles and barriers divert or halt steam chamber growth and thus slow oil production, possibly reducing bitumen recovery. However, predicting whether a shale layer is baffle or barrier is difficult. They are hard to correlate between appraisal wells as they are highly eroded in the fluvial depositional environment of the McMurray formation. Several authors have observed that a barrier or baffle in a reservoir can be detected by discontinuities in the vertical grading of bitumen viscosity or composition that is caused by intense biodegradation. This paper presents a case study that tests bitumen geochemistry as a tool for predicting the presence of baffling or sealing shale at two different Athabasca oil sands fields. Geochemical analysis of cuttings and core from multiple wells at two fields (Field 1 and 2) were analyzed to measure spatial variations in geochemical compositional at each field and to determine what parameters were the most robust in predicting barriers and baffles. Geochemical predictions of barriers or baffles were compared to barriers and baffles to SAGD steam chamber growth using field production and other geological data. Results indicate that geochemistry is valuable for aiding in the characterization of barriers and baffles. For the wells tested in this study, geochemically predicted baffles and barriers were also baffles and barriers for SAGD steam chamber growth. Geochemistry is also successful in detecting baffles at thin shale layers that are difficult to see on gamma logs and in wells with significant lost core where shale layers cannot be visually examined. In this study, Field 1 bitumen was more degraded than Field 2, and showed significant lateral heterogeneity in bitumen composition trends. Field 2 on the other hand had very little lateral variability in geochemical trends. Alkylnaphthalenes, alkylphenanthrenes, and steranes were found to be effective indicators of baffles and barriers at both fields, despite the greater heterogeneity at Field 1. Geochemical analysis from drill cuttings and from core stored at ambient conditions for 10 years provided good quality data for predicting baffles and barriers. Geochemistry provides a tool to help improve the interpretation of lateral shale continuity, and has future implications for SAGD design, such as determining pay thickness, optimal well location, and as a baseline in production allocation studies.

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.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.730
Threshold uncertainty score0.375

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 head0.022
GPT teacher head0.230
Teacher spread0.208 · 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