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Diagenetic Polygonal Faults in the Niobrara: An Integrated Look from Outcrops to Subsurface

Abstract

For close to one hundred years, geologists have known about randomly oriented normal faults in the outcrops of Niobrara Formation in Western Kansas. These faults have dips close to forty-five degrees and a few hundred feet of vertical displacement. They have been interpreted as being slump features caused by salt dissolution in underlying Permian strata. Recently, 3D seismic data in the Denver Basin has helped identify a polygonal fault system within the Niobrara Formation. Polygonal faults are layer bound extensional features that develop in fine-grained rocks. Faults observed in outcrop were related to faults interpreted on seismic over the Wattenberg and Silo fields of Colorado. We interpret the faults in Kansas outcrops to be an extension of the polygonal fault system identified in the subsurface Niobrara and not related to salt dissolution. This would be the first outcrop of a polygonal fault system documented in North America. A primary focus of this study was to understand the potential causes for the nucleation and development of the polygonal fault system. Observational-analytical study was conducted to explore the natural factors controlling what we denote as “pressure/volume contraction-induced fracturing” in mudrocks. The relationship between several factors controlling water-expulsion fracturing in mudrocks was investigated. These factors include the role of early diagenetic shrinkage of smectite, and interlayer water expulsion during continuous hydration of saline water. This is followed by late diagenesis causing shrinkage and more interlayer water expulsion due to transformation of smectite to illite. A hypothesized model for the diagenetic polygonal fracturing is proposed: 1) diagenesis of swelling clays, 2) volume contraction and water expulsion, 3) horizontal stress decrease, then 4) polygonal fracturing. Examining aspects of the diagenetic polygonal faults by utilizing different kinds of data sets can significantly enhance our understanding of their origin and impact prediction of subsurface polygonal fault networks.