Submitted by Paul L. Heller and Snehalata Huzurbazar, University of Wyoming

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QUANTITATIVE CHARACTERIZATION OF RAPID CHANGES IN ALLUVIAL STACKING PATTERN AND IMPACT ON RESERVOIR CONTINUITY: MORRISON FORMATION (UPPER JURASSIC) AND WASATCH FORMATION (PALEOGENE), WESTERN COLORADO

Heller and Snehalata Huzurbazar, University of Wyoming INTRODUCTION: An impression gathered over the years, anecdotally and from cursory observation, is that net:gross ratios in fluvial successions

1). Net:gross ratios between Figure 1. Net to gross ratio of several fluvial sequences located these end-members appear to be in east-central Utah and west-central Colorado.

1 QUANTITATIVE CHARACTERIZATION OF RAPID CHANGES IN ALLUVIAL STACKING PATTERN AND IMPACT ON RESERVOIR CONTINUITY: MORRISON FORMATION (UPPER JURASSIC) AND WASATCH FORMATION (PALEOGENE), WESTERN COLORADO AND EAST CENTRAL UTAH Submitted by Paul L. Heller and Snehalata Huzurbazar, University of Wyoming INTRODUCTION: An impression gathered over the years, anecdotally and from cursory observation, is that net:gross ratios in fluvial successions in alluvial basins tend to be bimodal. For example, preliminary data from fluvial units in the central Rocky Mountains suggests that net:gross ratios tend to be less than 40% or more than 70% (Fig. 1). Net:gross ratios between Figure 1. Net to gross ratio of several fluvial sequences located these end-members appear to be in east-central Utah and west-central Colorado. less common in the rock record. Furthermore, at least some of these.-/'(0%."'12%)*+,*38 alluvial systems are notable by how rapidly the transition takes place between these two end members. For example, the Morrison!"#$%&"'(%)*+,*Formation, on the Colorado Plateau, undergoes a rapid transition from )7#12"%)*+,*sand-rich deposits of the Salt Wash.8 Member (typically >70% net to gross) to the Brushy Basin Member (<25%) (Fig. 2a). The Wasatch Formation in western Colorado also shows a rapid transition from 3$4*##%5/#6(%)*+,*relatively mud-rich fluvial deposits of the Atwell Gulch Member to the sandy Molina Member (Fig. 2b), Figure 2. A. The Morrison Formation, east-central Utah, followed by a rapid transition back showing the sand-rich Salt Wash Member and the overlying into mud-rich Shire Member. Brushy Basin Member. B. Lower part of Wasatch Formation in Various models have been west-central Colorado showing lower mud-rich Atwell Gulch Member and overlying sandier Molina Member. proposed to explain such changes in stacking pattern, from long-term change in basin aggradation (subsidence) rate, climate-induced changes in water supply, sediment supply and vegetation along extant river systems, changes in base-level, and autocyclic changes in river pattern or behavior (e.g. (Allen, 1978; Leeder, 1978; Bridge and Leeder, 1979; Olsen et al., 1995; Heller and Paola, 1996; Demko et al., 2004; Hajek and Heller, 2004; Gibling, 2006; Rygel and Gibling, 2006; Davies and Gibling, 2010). 1

2 Each of these models has implications regarding the distribution, continuity, connectivity, and compartmentalization of fluvial reservoirs. At present it is unclear why this bimodality, if real, exists and to what degree changes in stacking pattern can be correlated to changes in other characteristics of the unit channel fills that compose the sand bodies. THIS STUDY: Our objectives are to evaluate possible external controls on changes in fluvial stacking pattern in settings where rapid changes in net:gross ratios exist and to characterize the range of organization of fluvial stacking patterns with the ultimate goal of making stratigraphic predictions as to the distribution and geometries of fluvial sand bodies in ancient systems. The specific goals of this study are to address two questions: 1) Are there any changes in preserved channel-belt characteristics that covary with changes in stacking pattern? 2) How organized (i.e. random vs. clustered vs. regular) are sand body distributions in both vertical sequences as well as across regions? This study will involve field data collected from outcrops and well logs from several fluvial units in the central Rocky Mountains. Field work will concentrate on two units: the Morrison Formation (Late Jurassic), well exposed in eastern Utah to western Colorado and intermittently exposed farther east to the Front Range of Colorado, and the Wasatch Formation (Paleocene-Eocene), well exposed in parts of the Piceance Creek Basin in western Colorado. These units share several important characteristics for this study. First, these units are not coastal plain deposits, but represent wholly nonmarine lithofacies deposited far from contemporaneous shorelines. As such, base-level changes from marine influences likely have little impact on their overall depositional characteristics, although other base-level changes may affect the units (e.g. Demko et al., 2004). Secondly, these units exhibit unambiguous, rapid changes in stacking patterns between high and low net:gross ratios (Fig. 2). These changes can be traced across large areas within the deposits so that down basin trends in architecture can be mapped. Thirdly, paleosols are common in the mud-dominated intervals, allowing more precise local lateral correlation of sandbodies through the muddy intervals to record their stratigraphic positions. This is important because clustering of channel bodies, possibly by avulsion processes, has been observed in some mud-rich fluvial successions (Hajek et al., 2010) and has been noticed in parts of the Brushy Basin Member of the Morrison Fm. In at least some fluvial reservoirs (e.g. the Lance Formation of Wyoming and the Mugaroo beds of western Australia), sand body clusters are also recognized. Hence, it is important to understand the spatial relationship of sand bodies. Lastly, across large parts of the study area exposure of these units is excellent with little vegetation cover obscuring exposures. This will facilitate measurement of preserved geometries. Field Study- In the field study we will collect quantitative data on geometries and sedimentologic characteristics of individual sand bodies that compose the alluvial architecture. These measures include: paleoflow depth (reconstructed from bar clinoform relief), characteristic grain size, incision depth, representative aspect ratio (i.e. generalized to roughly orthogonal to average local paleoflow direction), sand body incision depths, crevasse splay distributions (i.e. whether crevasse splay deposits are associated with sand bodies), sand body thickness and number of stories. From these data 2

we will look for which, if any of these measures covary with changes in net:gross ratios. Our hypothesis is that external controls (e.g. discharge, source rock, avulsion style, etc) are likely manifested as changes in more than stacking pattern alone.

The Salt Wash Member appears to show an increase in flow depths down basin, as would be expected in a tributary system.

3 we will look for which, if any of these measures covary with changes in net:gross ratios. Our hypothesis is that external controls (e.g. discharge, source rock, avulsion style, etc) are likely manifested as changes in more than stacking pattern alone. Preliminary data for both members of the Morrison Formation in east-central Utah had average flow depths of about 1.5 m (Fig. 3). The Salt Wash Member appears to show an increase in flow depths down basin, as would be expected in a tributary system. This member also contains many crevasse splay events found in association with channel fills (Fig. 4) and thus, may provide a means of connection between otherwise isolated sand bodies. Such units directly below channel deposits suggests that aggradational (aka progradational) avulsions are typical for this member (Mohrig et al., 2000; Slingerland and Smith, 2004; Jones and Hajek, 2007). While splay deposits directly associated with sand bodies are far less frequent in the Brushy Basin Member (Fig. 4), it seems, on cursory examination, that the number of splays per channel throughout the entire deposit may not change among members. If true, the only difference between members of the Morrison Formation may be stacking density and nothing else. That is, perhaps the only difference between members is the abundance of overbank mudstones preserved. We will build on this preliminary data set and measure the variety of features listed above associated with sand bodies as well as within the overbank deposits (frequency, grain size and continuity of splay deposits, etc). Statistical Study - The second aspect of this study is the development Figure 1. Paleoflow depth data for the Salt Wash and Brushy Basin members of the Morrison Formation along an NE to SW cross section running from Grand Junction, Colorado to Capital Reef National Monument, Utah. Flow depths are interpreted from fully preserved bar clinoforms within sandbody stories. Figure 2. Number of splays found within one average paleoflow depth beneath sand bodies in members of the Morrison Formation along same transect as Figure 3. of a statistical approach to be used to characterize and, ideally, correlate sandbody distributions in fluvial sequences focusing on the proximity and organization of sandbodies in vertical sequences and how these distributions vary across basins. Our approach utilizes a recently developed methodology in statistics, called functional data analysis (Ramsay and Silverman, 2005). In essence this analysis treats a sequence of data values (e.g. gamma-ray log data from a well as a function of depth) as an individual data point. The data point is then analyzed by fitting a function in terms of basis functions, such as the Fourier or b-spline bases. Once these functions are obtained for each data point (in our case gamma-ray log data), the functions can then be used to address the issue of determining whether there is clustering or regular spacing of sandbodies by using established techniques such as functional cluster analysis or functional principal components analysis, for estimated functions at different locations. The degree in which functions change describes, quantitatively, how the structure of the 3

The functions can also be 'registered' which helps with identifying patterns that might not 'line up' at the same depth index.

4 data varies in time (i.e. in vertical sequence) and in space (across a basin). In this case, digitized well-log data for each well represents an observation, and we will be able to look for potential clustering of these data across different locations. The functions can also be 'registered' which helps with identifying patterns that might not 'line up' at the same depth index. This approach was recently used by Huzurbazar and Humphrey (2008) to analyze and correlate water pressure data from boreholes on the Bench Glacier in Alaska. Figure 5 provides an example of the final clustering in which the original data is plotted but they are grouped together based upon the results of the clustering algorithm. Each cluster is composed of two functional observations (i.e. data sets from two wells), but clusters A, F and I had members which were 'close' in the functional clustering algorithm, while the members of O were more distant. The goal of the functional clustering in this case is to cluster water pressure records that look similar. Not surprisingly the results of the cluster analysis shows them to be similar. This example is fairly simple and as seen in the figure, the similar looking observations were clustered as such. We expect that application to lithologic proxy data from well logs will yield more complex patterns, but still the algorithm will show stratigraphically similar clusterings of data. Figure 3. Analysis of water level data from 8 wells, grouped into 4 groups by the clustering algorithm. Groups A, F and I each contain two data sets that cluster together (i.e. the statistical distance between them is close), while Group O are poorly clustered (i.e. they cluster at much larger statistical distances). In order to apply this approach to subsurface data sets, we request, as part of this proposal, access to digital well-log data from fluvial sequences in alluvial basins, particularly gamma ray and porosity data. The units need not be the same formations studied in the field portion of this study. In fact, one of the units we would most like to acquire well log data for is the Lance Formation of Wyoming State. In our preliminary study (Hajek et al., 2010), the Lance Formation was found to be statistically clustered (Fig. 6), and so is a promising unit to focus efforts on. We would like to compile enough regional data to study statistically both local variability in stratigraphic organization as well as describe the degree of change in organization across and between basins. 4

B A Figure 4. Channel-belt clusters in the Lance Formation, southeast Bighorn Basin, WY. Sandbodies within the Lance Formation are highlighted in yellow.

5 B A Figure 4. Channel-belt clusters in the Lance Formation, southeast Bighorn Basin, WY. Sandbodies within the Lance Formation are highlighted in yellow. Note to the right, above red line A, is a cluster of sandbodies in lower part of the sequence and, to the left (beneath red line B), is at least one cluster of sandbodies higher in the stratigraphic sequence. Synthesis The overall goal of this study is to quantify the type and degree of stratigraphic organization seen in fluvial stratigraphic units. Clustering and abrupt changes in stacking pattern are found in at least some alluvial basins. We suspect that such features may be more common once examined quantitatively. Whether these features form as the result of intrinsic, possibly critical theshold, phenomena or are imposed by external causes is an open question. While we will attempt to isolate the more obvious types of changes in deposition that may be caused by external controls, we will also consider the possible role of self-organization in forming stratigraphic packages. Rule-based synthetic basin filling models will be explored as a way of helping direct data collection. Such approaches are useful in helping evaluate possible stratigraphic controls, although we realize that such models do not capture all of the transient conditions impacting natural basin filling stratigraphy. The impacts of this study on exploration strategies in alluvial basins we would hope would be self-evident. Besides cataloging of sandbody geometries and spacings that can be used to populate reservoir models, we hope to understand the large-scale structure of fluvial basin fills. Mapping of stratigraphic architecture and developing statistical tools for analyzing its organization provide a means of describing architectural elements that form over time scales of tens of thousands to hundreds of thousands of years (i.e. many channel avulsions). Such tools can play a role in predicting the distribution of reservoir sized targets in the sub-surface. DELIVERABLES: In agreement with sponsoring agencies we plan to submit both comprehensive yearly reports along with shorter semi-annual updates of the project progress. These reports can be made in person or by web-based presentations. Products will include: Comprehensive bibliography of the Morrison and Wasatch Formations Tables with summary statistics of quantitative measures from channel belt sand bodies and attendant crevasse splay deposits. Statistical methodologies, codes and results. Interpreted large-scale photo panels. Digital copies of theses and published papers. Annual field trips will be offered to study areas highlighting project results. 5

6 BUDGET AND DATA ACCESS: This study will support at least two graduate students over a three period. Direct costs of supporting a single student (tuition and stipend) is about $27,000/year. In addition funds for research support, PI (2) and field assistant salaries runs about $14,000/year. Above this the University requests indirect costs of 45% on everything except tuition, costing an extra $22,200/year. However this latter cost is negotiable, depending on what the sponsoring agency is willing to cover. Thus, the total cost per year is about $85,000. In order to ease the burden we are submitting this proposal to three companies and asking $28,000 per year for each of three years from each company. In addition, a key part of this study involves statistical study of well-log data. As such we are requesting access to digital data (primarily gamma ray) from appropriate fluvial successions, not necessarily the units of focus for the field study. While such data will be used for analysis, we understand that public dissemination of raw data will not be made without permission. REFERENCES CITED: Allen, J.R.L., 1978, Studies in fluviatile sedimentation: an exploratory quantitative model for the architecture of avulsion-controlled alluvial suites: Sedimentary Geology, v. 21, p Bridge, J.S., and Leeder, M.R., 1979, A simulation model of alluvial stratigraphy: Sedimentology, v. 26, p Davies, N.S., and Gibling, M.R., 2010, Cambrian to Devonian evolution of alluvial systems: The sedimentological impact of the earliest land plants: Earth-Science Reviews, v. 98, p Demko, T.M., Curray, B.S., and Nicoll, K.A., 2004, Regional paleoclimatic and stratigraphic implications of paleosols and fluvial/overbank architecture in the Morrison Formation (Upper Jurassic), Western Interior, USA: Sedimentary Geology, v. 167, p Gibling, M.R., 2006, Width and thickness of fluvial channel bodies and valley fills in the geologic record: A literature compilation and classification: Journal of Sedimentary Research, v. 76. Hajek, E., and Heller, P.L., 2004, Determining fluvial stacking patterns in the lower Castlegate Sandstone (Campanian, Helper, Utah) using Lidar imaging: Geological Society of America Abstracts with Programs, v. 36, p Hajek, E.A., Heller, P.L., and Sheets, B.A., 2010, Significance of channel-belt clustering in alluvial basins: Geology, v. 38, p Heller, P.L., and Paola, C., 1996, Downstream changes in alluvial architecture: An exploration of controls on channel-stacking patterns: Journal of Sedimentary Research, v. 66, p Jones, H.L., and Hajek, E.A., 2007, Characterizing avulsion stratigraphy in ancient alluvial deposits: Sedimentary Geology, v. 202, p Leeder, M.R., 1978, A quantitative stratigraphic model for alluvium, with special reference to channel deposit density and interconnectedness, in Miall, A.D., ed., Canadian Soc. Petro. Geologists, Volume Memoir 5: Fluvial Sedimentology, p

7 Mohrig, D., Heller, P.L., Paola, C., and Lyons, W.J., 2000, Interpreting avulsion process from ancient alluvial sequences: Guadalope-Matarranya system (northern Spain) and Wasatch Formation (western Colorado): Geological Society of America Bulletin, v. 112, p Olsen, T., Steel, R., Høgseth, K., and Røe, S.-L., 1995, Sequential architecture in a fluvial succession: Sequence stratigraphy in the Upper Cretaceous Mesaverde Group, Price Canyon, Utah: Journal of Sedimentary Research, v. B65, p Rygel, M.C., and Gibling, M.R., 2006, Natural geomorphic variability recorded in a highaccommodation setting: fluvial architecture of the Pennsylvanian Joggins Formation of Atlantic Canada: Journal of Sedimentary Research, v. 76, p Slingerland, R., and Smith, N.D., 2004, River avulsions and their deposits: Annual Review of Earth and Planetary Sciences, v. 32, p

SUPPLEMENTAL INFORMATION DELFT 3-D MODELING: MODEL DESIGN, SETUP, AND ANALYSIS

GSA DATA REPOSITORY 2014069 Hajek and Edmonds SUPPLEMENTAL INFORMATION DELFT 3-D MODELING: MODEL DESIGN, SETUP, AND ANALYSIS Each experiment starts from the initial condition of a straight channel 10 km