Integrated Reservoir Characterization and 3D Modeling of the Monteith Formation: Tight Gas Sandstones in the Western Canada Sedimentary Basin, Alberta, Canada
Bibliographic record
Abstract
Abstract The Monteith Formation is an important tight gas reservoir in the Deep Basin, Alberta, and consists of a progradational succession of shallow marine sediments, non-marine carbonaceous and coaly, coastal plain facies, and coarse-grained fluvial deposits, from base to top, respectively. This study compares rock properties and production performance of the uppermost lithostratigraphic unit ("Monteith A") and the lowermost portion ("Monteith C") of the Monteith Formation in the Western Canada Sedimentary Basin (WCSB) in Alberta. The study is based on multi-scale description and characterization techniques using cores and drill cuttings, including multiple laboratory measurements of key reservoir parameters such as porosity and permeability. A second stage of the study involves the use of laboratory measurements obtained from cores and drill cuttings and their integration with well logs to produce a numerical 3D model of the study area. The 3D model is used to history match gas production, and forecast performance of new wells in those areas where the geologic model indicates potential for gas production. The ultimate goal is to provide a better understanding of the distribution of reservoir properties in the study area, for developing drilling prospects and their production potential. In addition to that, the reservoir modeling stage is carried out by implementing a recently developed methodology that integrates a Variable Shape Distribution (VSD) model, capable of capturing different reservoir properties through the whole scale spectrum without any data truncation. This new methodology introduces an extension of the VSD approach for reservoir simulation purposes. The results are showing that the Monteith A unit has better rock quality than the shallow marine sandstones of the Monteith C interval. This is most likey due to larger pore throat apertures ranging between 0.5 and 1 microns, relatively higher proportion of preserved intergranular pore space within these coarser-grained framework grains. Furthermore, the best production performance is found from wells that are actually producing from the uppermost interval. The resulting 3D reservoir model will allow to improve field development strategies for this and other similar unconventional gas reservoir in the Deep Basin of Alberta.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".