Stratigraphic Variability of Mississippian Meramec Chemofacies and Petrophysical Properties Using Machine Learning and Geostatistical Modeling, STACK Trend, Anadarko Basin, Oklahoma
| dc.contributor.advisor | Pranter, Matthew | |
| dc.contributor.author | Hardisty, Lura | |
| dc.contributor.committeeMember | Marfurt, Kurt | |
| dc.contributor.committeeMember | Devegowda, Deepak | |
| dc.date.accessioned | 2019-12-17T16:42:58Z | |
| dc.date.available | 2019-12-17T16:42:58Z | |
| dc.date.issued | 2019-12-13 | |
| dc.date.manuscript | 2019-12-11 | |
| dc.description.abstract | Mississippian deposits and reservoirs in the STACK play (Sooner Trend in the Anadarko [Basin] in Canadian and Kingfisher counties) of central Oklahoma are comprised of silty limestones, calcareous siltstones, argillaceous-calcareous siltstones, argillaceous siltstones and mudstones. Using core-derived X-ray fluorescence (XRF) data and established environmental proxies, the occurrence of specific elements is evaluated and their stratigraphic variability is illustrated. Other proxies are developed for indicator elements based on correlation to established proxies as well as background knowledge on how elements are associated with different minerals, rocks, and organic matter. For the Meramec, six indicator elements or element ratios serve as proxies for clay, detrital sediment, carbonate deposits and calcite cement, and biogenic and continentally derived quartz. Detailed core descriptions and an unsupervised K-means classification were used to cluster elemental data to develop three chemofacies: 1) calcareous sandstone, 2) argillaceous-calcareous siltstone and 3) detrital mudstone. Using a Random Forest approach, core-derived chemofacies were related to well logs and classified in non-cored wells to create chemofacies logs with an overall accuracy of 83%. Core-derived XRF, well logs, and chemofacies logs were integrated to produce a dip-oriented cross-sectional chemofacies model that trends from the northwest to southeast across the southern STACK trend. Chemofacies distributions exhibit the transgressive-regressive-transgressive cycles of the Meramec. The Meramec is composed of seven stratigraphic zones. The stratigraphic variability of chemofacies shows an increase of argillaceous detrital mudstone from the Meramec 1, 2 to the Meramec 3 which is capped by a maximum flooding surface. From the Meramec 4 to the Meramec 5, an increase of the argillaceous-calcareous siltstone and calcareous sandstone represents a progradational shoreline. Rock types, porosity, water saturation and reservoir quality were also modeled to determine the petrophysical properties distributions and how certain petrophysical properties are associated with each chemofacies. A porosity model exhibits an increase in porosity from the calcareous sandstone to detrital mudstone. The average water saturations per chemofacies indicates high water saturation associated with the argillaceous-calcareous siltstone, moderate water saturation associated with calcareous sandstone and low water saturation associated with detrital mudstone. Ideal reservoir quality of chemofacies based on petrophysical properties indicates high reservoir quality within the detrital mudstone and low reservoir qualities in both the argillaceous-calcareous siltstone and calcareous sandstone. Biogenic quartz is associated with drilling issues, specifically frequent bit trips due to its hardness. Interpreted biogenic quartz from element profiles correspond to the calcareous sandstone chemofacies which can be predicted from triple combo logs and mapped. Petrophysical property distributions reflect the stratigraphic variability of chemofacies and rock types throughout the models. | en_US |
| dc.identifier.uri | https://hdl.handle.net/11244/323245 | |
| dc.language | en_US | en_US |
| dc.subject | Chemostratigraphy | en_US |
| dc.subject | STACK Trend | en_US |
| dc.subject | Meramec | en_US |
| dc.thesis.degree | Master of Science | en_US |
| dc.title | Stratigraphic Variability of Mississippian Meramec Chemofacies and Petrophysical Properties Using Machine Learning and Geostatistical Modeling, STACK Trend, Anadarko Basin, Oklahoma | en_US |
| ou.group | Mewbourne College of Earth and Energy::School of Geosciences | en_US |
| shareok.nativefileaccess | restricted | en_US |