RESERVOIR QUALITY EVALUATION OF THE MERAMEC AND UPPER OSAGE UNITS IN THE ANADARKO BASIN
Bibliographic record
Abstract
The objective of this study is to provide a comparative look at the diagenetic evolution and reservoir quality characteristics of the Meramec and Upper Osage units in the STACK (Sooner Trend Anadarko Basin of Canadian and Kingfisher counties) and NW STACK (extension of the STACK, to the northwest, into portions of Dewey, Blaine, Woodward, and Major counties, Oklahoma). Both are hybrid unconventional plays in the Anadarko Basin of Oklahoma and consists of a complex depositional sequence of Middle Mississippian siliciclastics and carbonates of Meramecian and Osagean age as well as the Late Devonian to Early Mississippian organic-rich Woodford Shale. \nUnsupervised Hierarchical Clustering Analysis (HRA) was performed to connect reservoir-scale petrophysical observations with micro-scale petrographic observations. The clustering analysis yielded five distinct electrofacies in the Meramec that represent depositional trends in mineralogy and diagenetically enhanced intervals of anomalous feldspar dissolution. Implementing HRA provided a genetic-based workflow for reservoir quality prediction and understanding. Wireline data from twelve publicly available wells with core and wireline data from seven other wells provided the framework to demonstrate the predictive workflow presented in this study. \nPaleomagnetic and petrographic data were integrated to discern the diagenetic evolution of each unit. Petrographic analysis revealed a pervasive marine calcite cement in silt-dominated microfacies of the Osage and Meramec. The calcite cement significantly occluded primary porosity and created baffles for vertical fluid flow. The terrigenous input of clay partially protected primary porosity enhancing fluid flow in the more framework dominated microfacies. The primary pore-types observed in good reservoir quality microfacies include: intragranular pores in feldspars, interstitial porosity in clay, and intergranular pores in between other framework grains such as silt. Thermal demagnetization revealed a characteristic remanent magnetization (ChRM) removed at unblocking temperatures ranging from 250°C to 450°C. The ChRM displayed shallow inclinations consistent with an acquisition of approximately 300 Ma. The ChRM is interpreted as a chemical remanent magnetization (CRM) related to the emplacement of hydrocarbons; thus, providing a critical temporal component on the evolution of the petroleum system.
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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 | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".