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Record W2011962125 · doi:10.2118/2004-200

Field-Scale Compositional Simulation of a CO2 Flood in the Fractured Midale Field

2004· article· en· W2011962125 on OpenAlexaffabout
Shauket Malik, S. Chugh, R. A. McKishnie, P. J. Griffith, Robert Guy Lavoie

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsApache (Canada)
Fundersnot available
KeywordsField (mathematics)Flood mythScale (ratio)GeologyEnvironmental sciencePhysicsMathematicsGeographyArchaeology

Abstract

fetched live from OpenAlex

Abstract The Midale Unit in southeastern Saskatchewan has been under waterflood operations for 40 years, and substantial quantities of remaining oil make the Unit a good target for implementation of an EOR process. Although naturally fractured, the Midale Unit proved to be a good candidate for a miscible CO2 flood. Encouraging results from a demonstration CO2 flood in a small part of the Midale Unit (?2,000 acres) prompted an extensive study to evaluate the potential of the fullfield CO2 flood. The study involved analytical modeling and several compositional simulation models, ranging from a small, element-of-symmetry model to the comprehensive, field-scale model. This paper describes the compositional simulation conducted on a large 3D model containing 40,000 grid blocks. The 204-well model covered 20 inverted nine-spot waterflood patterns and the CO2 demonstration flood area including both vertical and horizontal wells; this comprises approximately 25% of the total Unit. The reservoir fluid was characterized using a 9-component Peng-Robinson equation-of-state model. Pattern-based permeability anisotropy was a key parameter used to accurately match individual well response to the waterflood and the CO2 flood. A very good history match was obtained on both the field and the well scale. The tuned model was used to predict future reservoir performance under various operating and development scenarios. Various CO2 injection strategies were considered, including Continuous CO2 flood, Water-Alternating-Gas (WAG) and Hybrid WAG. Under each strategy a detailed sensitivity modeling was performed investigating the optimal CO2 volumes, injectivity, WAG ratio and the benefits of pressure support and limiting the gas production. The study showed that incremental recoveries of 11–15% OOIP can be expected by implementing the optimized CO2 flood scenario. Results of the compositional model were then used to tune the streamline simulator for the full field model. A full field development plan was delivered in 4 months. Introduction The Midale field, located in SE Saskatchewan (Figure 1), was discovered in 1953 and initially delineated on 80 acre spacing. The field produced under competitive drainage until unitization in late 1962, at which time an inverted nine-spot waterflood scheme was implemented. An extensive vertical infill program was undertaken during the mid 1980's to modify the waterflood patterns to increase recovery. In the late 1980's and mid 1990's, horizontal wells and multi-legged perpendicular horizontals were drilled to further improve waterflood conformance. To-date, the Unit has recovered over 20 E6m_ of oil (primarily from waterflood operations) representing about 24% of the Unit's OOIP. A CO2 Flood Pilot project was initiated in 1984 to investigate the applicability of using CO2 to recover some of the large volume of remaining oil that would not be recovered by waterflood operations1–3. This project involved the drilling of 10 closely spaced wells in an area 4.4 acres in size, and it generated an enormous amount of reservoir and geological information. Based on results from the CO2 Pilot project, a larger-scale Midale CO2 Flood Demonstration Project4, consisting of a six-pattern CO2 flood located in the southwestern part of the Unit, began operations in 1992.

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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 score0.102
Threshold uncertainty score0.948

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 head0.014
GPT teacher head0.259
Teacher spread0.245 · 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
Published2004
Admission routes2
Has abstractyes

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