Characterization of Fracture Network System of the Midale Field
Bibliographic record
Abstract
Abstract Enhanced oil recovery from challenging/complex fields requires extensive analysis of reservoir structure and good understanding of the effect of this structure on the dynamics of the process. Naturally fractured reservoirs are good examples of this kind and their fracture network characterization is still a big challenge. In this study, we analyzed the fracture network system of a portion of the Midale field, a naturally fractured carbonate reservoir in the Williston basin of south-eastern Saskatchewan, Canada. Our study aims at an extensive characterization of fracture and fracture network properties and construction of a reliable fracture network model for further use in assessing the oil recovery by CO2 injection and CO2 sequestration potential. We integrated static data such as cores, logs, and well tests to build 3-D discrete fracture network models. Stochastic numerical approach was applied using an emerging commercial software package (FRACA). Fracture network constructed from static data was calibrated using well test data. Several parameters were evaluated in sensitivity studies to determine those characteristics of the network, which have higher influence on the reservoir performance. Simulated well test response was checked against previously published well test data. This study allowed us to recognize uncertainties in critical parameters and propose some measures to manage those uncertainties. Introduction The Midale is a carbonate field located in southeastern Saskatchewan. Following the discovery in 1953, the field was developed on 80-acre spacing and proved to bear 515 MM bbl reserves of 28.7 °API oil. The field belongs to the Mississippian oil trend located along the northern margin of Williston basin. Subsequent to primary production up to 1962, the field was subjected to waterflooding on 83 inverted nine-spot patterns. To maintain the production declining after 1964, an intensive vertical and horizontal infill drilling was undertaken. As of the end of 2006, approximately 1000 wells exist in the field and more than 25% of OOIP was produced with an average watercut of 92%(1). The Midale field is currently being subjected to tertiary recovery by miscible CO2 flooding. This field-scale CO2 injection was preceded by a 4.4 acre pilot project in 1984–1989 which paved the way for a larger demonstration project. The CO2 Flood Demonstration Project encompassed 10% of Midale Unit and paved the way for the field-scale application, which is expected to end up with an incremental recovery of 15% of OOIP(2). The Midale field does not meet typical screening criteria for CO2 flooding. Nevertheless, extensive research and field applications proved that a proper design based on the analyses of the special combination of petrophysical, lithological and fracturing data can result in a successful carbon dioxide flood. 24-meter thick Midale reservoir section consists of two main layers: dolomite-dominated "Marly" and vugular limestone, called "Vuggy". Both strata contain systematic fractures, though the degree of fracturing varies. Numerous studies conducted on the field revealed some characteristics of the natural fracture network (NFN) by both inverse methods such as waterflood and carbon dioxide flood performance analyses, and well test analyses and direct methods such as core and log analyses.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.001 | 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 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".