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Integrating a Deterministic Lithology Model for Subsurface Correlation, Eocene Green River Formation, Uinta Basin, Utah


The Green River Formation of the Uinta basin is an Eocene lacustrine system comprised of carbonates, siliciclastics, and rich oil shales. Log evaluation is difficult, due to the formation's complex mineralogy and thin interbedded nature of diverse rock types. Historically, log correlations have used a zoned model, which excludes detail and suggests continuity that is misleading on a bed-by-bed basis. Methods to determine lithology at a finer scale by using advanced logging tools and stochastic models require specialized software, expert users, and can be cost prohibitive. However, a simple, deterministic model can be applied which utilizes widely available logging measurements: gamma ray, density, neutron porosity, and photoelectric effect. This four mineral solution gives an output of volume percent of quartz, calcite, dolomite, and mixed clay. To obtain these volume percentages, log-based calculations yield an apparent matrix density (RHOmaa) and an apparent photoelectric cross section (Umaa). These values are plotted on one of two mineral identification triangle plots: 1) quartz-calcite-dolomite; or 2) quartz-calcite-clay. The triangle utilized is determined by the gamma ray value, with low gamma ray values (“cleaner” or less clay) using the first triangle and high gamma ray values (“shaley” or more clay) using the second. The quartz and clay triangle end points are considered “floating” and are adjusted using elemental analysis on the formation. These volume percentages are normalized to sum 1, and have been filtered for adverse logging conditions. The final result is similar to elemental analysis logging tools and is obtained at a lower cost utilizing commonly available software suites. The volume percentages allow for more detailed correlations that better convey this complex lithologic system and clearly show vertical variability and stratigraphic changes from littoral to profundal lake environments. Lithofacies clearly identified by the resulting volume percentages include clean carbonate beds and oil shales. High-feldspathic content rocks generally require a more mobile quartz end point, but result in the identification of thin siliciclastic beds. Calibration of lithology is accomplished by using gamma ray and XRF data derived from nearby analogous carbonate and siliciclastic outcrops, and wireline log suites tied to core.