Abstract:

The Piceance Basin is located in northwest Colorado and was formed during the Late Cretaceous–Paleogene Laramide tectonism, which partitioned the stable Cretaceous Interior Seaway foreland basin into a series of smaller basins. The basin is defined by reverse faults and associated anticlinal fold structures on the margins.
From the Late Cretaceous to Cenozoic, the Piceance basin transited from marine to terrestrial depositional setting as a result of the Laramide deformation and the recent vertical regional uplift. Depositional environments varied from shallow marine, fluvial, paludal, lacustrine and terrestrial settings and formed the prolific Mesaverde petroleum system. The earliest commercial production came from a Cretaceous tight sand reservoir situated in Williams Fork Formation of the Mesaverde Group. The underlying coastal plain coals became thermally mature later in the Cenozoic and charged the adjacent Mesaverde Williams Fork Formation with natural gas.
Diverse depositional environments not only led to the development of petroleum system but also produced many heterogeneities and “unknowns”, which makes the study of the basin evolution history very challenging. Basin and petroleum system modeling utilizes an integrated approach to link these multiple complex geologic processes into a model framework, to explore the uncertainties and to test hypothesis, and scenarios. The Piceance Basin is an ideal settings for investigating a sedimentary basin with diverse depositional settings and exploring uncertainties associated with changing basin history.
This thesis is divided into three chapters addressing the following research objectives: (1) To integrate geological, geochemistry and engineering data into a basin model frame work and enhance understanding of Piceance Basin history; (2) To investigate possible geological constraints that reduce the uncertainty in terrestrial basin modeling efforts; (3) To tackle complex uncertainties in basin and petroleum system modeling and disentangle the input model parameter’s impact on the model response with the aid of efficient uncertainty quantification tools.
Chapter 1 presents a comprehensive basin study for the Piceance Basin. This work utilizes integrated data and reconstructs a numerical basin model to summarize the basin evolution history from the Late Cretaceous to present day. During this exercise, a conceptual model was first designed to capture the basin’s transformation from marine to terrestrial, with simplification of the basin tectonic history into two major deformation and inversion events. The Cretaceous Cameo Coal source rock maturation history were investigated via the constructed basin model framework. Given limited published calibration data, basin models were calibrated mainly with vitrinite reflectance data. The basin model predictions agree well with the measured thermal maturation data. This work contributed a regional scale 3-dimensional basin model for the study area. The model may serve as a research vehicle for further studies, such as geological scenario tests, unconventional resources characterization and other Laramide basin research.
This chapter was co-authored with Dr. Carolyn Lampe, Dr. Stephan A. Graham, Dr. Allegra Hosford Scheirer, Leslie Magoon and Dr. Tapan Mukerji. It was presented at the AAPG Hedberg Research Conference (April 3-8, 2016), Santa Barbara, California, U.S. An abbreviated version of this chapter is planned for future submission to this conference’s proceedings volume.
Chapter 2 presents a novel approach that utilizes paleoclimate data to constrain the basin thermal history, especially for terrestrial basins with substantial uplift history. Basin thermal history is a critical part of sedimentary basin studies, especially for understanding the hydrocarbon generation in a petroliferous basin. Two boundary conditions are required to quantify basin thermal conditions: the basal heat flow as the lower boundary condition and the sediment surface temperature as the upper thermal boundary condition. For marine basins, the sediment surface temperature is often estimated from water surface temperature, corrected by water depth from paleobathymetry information. However, as our study area was elevated and exposed subaerially, the sediment surface temperatures can no longer be estimated by water-sediment interface temperature; rather, the surface temperatures are impacted by complicated factors and are subject to larger variations. In our work, we developed a Cenozoic temperature proxy in the study area by utilizing paleoclimate studies focused on macro floral assemblages. The resulting interpreted surface temperature largely reduced the uncertainty in paleo-thermal condition estimation. This work also demonstrates the importance of capturing the surface temperature variation for elevated terrestrial setting basins.
This chapter was submitted to Basin Research in winter, 2015, and is in review at this time. Co-authors include Daniel E. Ibarra, Jeremy K. Caves, Dr. Tapan Mukerji and Dr. Stephan A. Graham. My role in this research was designing and implementing the workflow, all basin model construction and comparisons, and results interpretation. Daniel E. Ibarra and Jeremy K. Caves conducted the paleoclimate data analysis. Dr. Tapan Mukerji provided critical modeling guidance. Dr. Graham initiated the collaboration and project design.
Chapter 3 presents the effort of tackling complex input uncertainties and disentangling their correlations with basin model spatial and temporal responses. Uncertainty quantification and sensitivity analysis workflows are implemented, subtle correlation between the input parameter and the basin model responses were identified; source rock geochemical properties may impact the present-day porosity and pore pressure in the underburden rock. Knowing the sensitivity propagation on both spatial and temporal model domain enhances our understanding of highly nonlinear basin models, and brings insights for future model improvement.
This chapter was submitted to Journal of Petroleum Sciences and Engineering in spring, 2016, and is in review at this time. Dr. Tapan Mukerji is the co-author. My contributions to this work include project design, implementing the Monte Carlo workflows by creating scripting files, basin model construction and testing, and results interpretation. Dr. Tapan Mukerji provided the initial project design and critical guidance on results interpretation.

Press the Back button in your browser.

Copyright 2016, Yao Tong: Please note that the reports and theses are copyright to their original authors. Authors have given written permission for their work to be made available here. Readers who download reports from this site should honor the copyright of the original authors and may not copy or distribute the work further without the permission of the author, Yao Tong.