Understanding Waterflood Response in Tight Oil Formations: A Saskatchewan Case Study
Bibliographic record
Abstract
This article, written by JPT Technology Editor Chris Carpenter, contains highlights of paper SPE 171671, “Understanding Waterflood Response in Tight Oil Formations: A Case Study of the Lower Shaunavon,” by Adrian Thomas, SPE, Anjani Kumar, SPE, and Kenny Rodrigues, SPE, Computer Modelling Group, and Ryan Sinclair, SPE, Colin Lackie, Angela Galipeault, and Mike Blair, Crescent Point Energy, prepared for the 2014 SPE/CSUR Unconventional Resources Conference—Canada, Calgary, 30 September–2 October. The paper has not been peer reviewed. An 18-well numerical-simulation model was built to represent an operator’s Lower Shaunavon waterfloodpilot area. Numerical simulation was used, and a history match on the pilot area was performed. By use of parameters obtained from the history match, a representative model was built and a sensitivity study was performed on hydraulic-fracture spacing and well spacing in both primary-depletion and waterflood scenarios. Modeling-Work-Flow Description The Shaunavon is partitioned into lower and upper members. The lower member is an authigenic carbonate shelf, while the upper member has a strong clastic influence from the west. Oil is trapped hydrodynamically; the oil fairway crosses both stratigraphic and structural trends. The Lower Shaunavon is divided into four intervals in the study area. The lowest interval is a calcareous cryptocrystalline mudstone. Sitting above this interval is the B Marker, which is a slightly more energetic environment. The A Marker marks a regressive lag as a result of a sea-level drop. It consists of wackestone to some packstone rock and is bounded above and below by mudstones. The uppermost interval represents a high-energy environment. A geological model was developed for the lower Shaunavon pilot area on the basis of well logs, petrophysical data, and surface maps. The model was developed further into a dynamic simulation model by incorporating pressure/volume/temperature data, relative permeability, well trajectory, well completion, and historical well-production and -injection information for all wells located within the pilot area. A history match was performed on a single-well submodel to obtain improved values of reservoir hydraulic-fracture properties in the surrounding region. These values were applied to the full pilot area, and the model was simulated in an attempt to achieve a history match. Once the pilot area was history matched, forecast runs of an additional 50 years were performed to gauge future production along with future drilling scenarios. By use of the properties obtained through history matching, a new generalized model was built and different forecast scenarios were run to determine well spacing under both primary depletion and waterflood. For a discussion of reservoir-parameter selection and simulation-model setup, please see the complete paper.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".