Stratigraphic Intervals for Oil and Tar Sand Deposits in the Uinta Basin, Utah

2017 ◽  
Vol 54 (4) ◽  
pp. 227-264
Author(s):  
Ronald Johnson ◽  
Justin Birdwell ◽  
Paul Lillis
Keyword(s):  
Brackish Water ◽  
Source Rocks ◽  
Uinta Basin ◽  
Green River ◽  
Reservoir Rocks ◽  
Stratigraphic Framework ◽  
Two Samples ◽  
The Rich ◽  
And Migration ◽  
Almost All

To better understand oil and bitumen generation and migration in the Paleogene lacustrine source rocks of the Uinta Basin, Utah, analyses of 182 oil samples and tar-impregnated intervals from 82 core holes were incorporated into a well-established stratigraphic framework for the basin. The oil samples are from the U.S. Geological Survey Energy Resources Program Geochemistry Laboratory Database; the tar-impregnated intervals are from core holes drilled at the Sunnyside and P.R. Spring-Hill Creek tar sands deposits. The stratigraphic framework includes transgressive and regressive phases of the early freshwater to near freshwater lacustrine interval of Lake Uinta and the rich and lean zone architecture developed for the later brackish-to-hypersaline stages of the lake. Two types of lacustrine-sourced oil are currently recognized in the Uinta Basin: (1) Green River A oils, with high wax and low β-carotane contents thought to be generated by source rocks in the fresh-to-brackish water lacustrine interval, and (2) much less common Green River B oils, an immature asphaltic oil with high β-carotane content thought to be generated by marginally mature to mature source rocks in the hypersaline lacustrine interval. Almost all oil samples from reservoir rocks in the fresh-to-brackish water interval are Green River A oils; however four samples of Green River A oils were present in the hypersaline interval, which likely indicates vertical migration. In addition, two samples of Green River B oil are from intervals that were assumed to contain only Green River A oil. Tar sand at the P.R. Spring-Hill Creek deposit are restricted to marginal lacustrine and fluvial sandstones deposited during the hypersaline phase of Lake Uinta, suggesting a genetic relationship to Green River B oils. Tar sand at the Sunnyside deposit, in contrast, occur in marginal lacustrine and alluvial sandstones deposited from the early fresh to nearly freshwater phase of Lake Uinta through the hypersaline phase. The Sunnyside deposit occurs in an area with structural dips that range from 7 to 14 degrees, and it is possible that some tar migrated stratigraphically down section.

Stratigraphic Architecture of a Fluvial-lacustrine Basin-fill Succession at Desolation Canyon, Uinta Basin, Utah: Reference to Walthers’ Law and Implications for the Petroleum Industry

2016 ◽  
Vol 53 (1) ◽  
pp. 5-28 ◽  
Author(s):  
Grace Ford ◽  
David Pyles ◽  
Marieke Dechesne
Keyword(s):  
Cross Section ◽  
Oil Shale ◽  
Large Scale ◽  
Green River Formation ◽  
Sand Content ◽  
Fluvial System ◽  
Uinta Basin ◽  
Green River ◽  
Lacustrine Basin ◽  
Basin Fill

A continuous window into the fluvial-lacustrine basin-fill succession of the Uinta Basin is exposed along a 48-mile (77-kilometer) transect up the modern Green River from Three Fords to Sand Wash in Desolation Canyon, Utah. In ascending order the stratigraphic units are: 1) Flagstaff Limestone, 2) lower Wasatch member of the Wasatch Formation, 3) middle Wasatch member of the Wasatch Formation, 4) upper Wasatch member of the Wasatch Formation, 5) Uteland Butte member of the lower Green River Formation, 6) lower Green River Formation, 7) Renegade Tongue of the lower Green River Formation, 8) middle Green River Formation, and 9) the Mahogany oil shale zone marking the boundary between the middle and upper Green River Formations. This article uses regional field mapping, geologic maps, photographs, and descriptions of the stratigraphic unit including: 1) bounding surfaces, 2) key upward stratigraphic characteristics within the unit, and 3) longitudinal changes along the river transect. This information is used to create a north-south cross section through the basin-fill succession and a detailed geologic map of Desolation Canyon. The cross section documents stratigraphic relationships previously unreported and contrasts with earlier interpretations in two ways: 1) abrupt upward shifts in the stratigraphy documented herein, contrast with the gradual interfingering relationships proposed by Ryder et al., (1976) and Fouch et al., (1994), 2) we document fluvial deposits of the lower and middle Wasatch to be distinct and more widespread than previously recognized. In addition, we document that the Uteland Butte member of the lower Green River Formation was deposited in a lacustrine environment in Desolation Canyon. Two large-scale (member-scale) upward patterns are noted: Waltherian, and non-Waltherian. The upward successions in Waltherian progressions record progradation or retrogradation of a linked fluvial-lacustrine system across the area; whereas the upward successions in non-Waltherian progressions record large-scale changes in the depositional system that are not related to progradation or retrogradation of the ancient lacustrine shoreline. Four Waltherian progressions are noted: 1) the Flagstaff Limestone to lower Wasatch Formation member records the upward transition from lacustrine to fluvial—or shallowing-upward succession; 2) the upper Wasatch to Uteland Butte records the upward transition from fluvial to lacustrine—or a deepening upward succession; 3) the Uteland Butte to Renegade Tongue records the upward transition from lacustrine to fluvial—a shallowing-upward succession; and 4) the Renegade Tongue to Mahogany oil shale interval records the upward transition from fluvial to lacustrine—a deepening upward succession. The two non-Waltherian progressions in the study area are: 1) the lower to middle Wasatch, which records the abrupt shift from low to high net-sand content fluvial system, and 2) the middle to upper Wasatch, which records the abrupt shift from high to intermediate net-sand content fluvial system.

Sequence stratigraphy of source and reservoir rocks in the Upper Permian and Jurassic of Jameson Land, East Greenland

1998 ◽  
pp. 43-54 ◽  
Author(s):  
Lars Stemmerik ◽  
Gregers Dam ◽  
Nanna Noe-Nygaard ◽  
Stefan Piasecki ◽  
Finn Surlyk
Keyword(s):  
Sequence Stratigraphy ◽  
Middle Jurassic ◽  
Sedimentary Basins ◽  
Upper Jurassic ◽  
Oil Field ◽  
Source Rocks ◽  
Upper Permian ◽  
Shallow Marine ◽  
East Greenland ◽  
Reservoir Rocks

NOTE: This article was published in a former series of GEUS Bulletin. Please use the original series name when citing this article, for example: Stemmerik, L., Dam, G., Noe-Nygaard, N., Piasecki, S., & Surlyk, F. (1998). Sequence stratigraphy of source and reservoir rocks in the Upper Permian and Jurassic of Jameson Land, East Greenland. Geology of Greenland Survey Bulletin, 180, 43-54. https://doi.org/10.34194/ggub.v180.5085 _______________ Approximately half of the hydrocarbons discovered in the North Atlantic petroleum provinces are found in sandstones of latest Triassic – Jurassic age with the Middle Jurassic Brent Group, and its correlatives, being the economically most important reservoir unit accounting for approximately 25% of the reserves. Hydrocarbons in these reservoirs are generated mainly from the Upper Jurassic Kimmeridge Clay and its correlatives with additional contributions from Middle Jurassic coal, Lower Jurassic marine shales and Devonian lacustrine shales. Equivalents to these deeply buried rocks crop out in the well-exposed sedimentary basins of East Greenland where more detailed studies are possible and these basins are frequently used for analogue studies (Fig. 1). Investigations in East Greenland have documented four major organic-rich shale units which are potential source rocks for hydrocarbons. They include marine shales of the Upper Permian Ravnefjeld Formation (Fig. 2), the Middle Jurassic Sortehat Formation and the Upper Jurassic Hareelv Formation (Fig. 4) and lacustrine shales of the uppermost Triassic – lowermost Jurassic Kap Stewart Group (Fig. 3; Surlyk et al. 1986b; Dam & Christiansen 1990; Christiansen et al. 1992, 1993; Dam et al. 1995; Krabbe 1996). Potential reservoir units include Upper Permian shallow marine platform and build-up carbonates of the Wegener Halvø Formation, lacustrine sandstones of the Rhaetian–Sinemurian Kap Stewart Group and marine sandstones of the Pliensbachian–Aalenian Neill Klinter Group, the Upper Bajocian – Callovian Pelion Formation and Upper Oxfordian – Kimmeridgian Hareelv Formation (Figs 2–4; Christiansen et al. 1992). The Jurassic sandstones of Jameson Land are well known as excellent analogues for hydrocarbon reservoirs in the northern North Sea and offshore mid-Norway. The best documented examples are the turbidite sands of the Hareelv Formation as an analogue for the Magnus oil field and the many Paleogene oil and gas fields, the shallow marine Pelion Formation as an analogue for the Brent Group in the Viking Graben and correlative Garn Group of the Norwegian Shelf, the Neill Klinter Group as an analogue for the Tilje, Ror, Ile and Not Formations and the Kap Stewart Group for the Åre Formation (Surlyk 1987, 1991; Dam & Surlyk 1995; Dam et al. 1995; Surlyk & Noe-Nygaard 1995; Engkilde & Surlyk in press). The presence of pre-Late Jurassic source rocks in Jameson Land suggests the presence of correlative source rocks offshore mid-Norway where the Upper Jurassic source rocks are not sufficiently deeply buried to generate hydrocarbons. The Upper Permian Ravnefjeld Formation in particular provides a useful source rock analogue both there and in more distant areas such as the Barents Sea. The present paper is a summary of a research project supported by the Danish Ministry of Environment and Energy (Piasecki et al. 1994). The aim of the project is to improve our understanding of the distribution of source and reservoir rocks by the application of sequence stratigraphy to the basin analysis. We have focused on the Upper Permian and uppermost Triassic– Jurassic successions where the presence of source and reservoir rocks are well documented from previous studies. Field work during the summer of 1993 included biostratigraphic, sedimentological and sequence stratigraphic studies of selected time slices and was supplemented by drilling of 11 shallow cores (Piasecki et al. 1994). The results so far arising from this work are collected in Piasecki et al. (1997), and the present summary highlights the petroleum-related implications.

CLIMATIC CONTROL ON FLUVIAL-DELTAIC SYSTEMS OF THE LACUSTRINE GREEN RIVER FORMATION, UINTA BASIN, UTAH

2017 ◽  
Author(s):  
Lauren P. Birgenheier ◽  
◽  
Ryan D. Gall ◽  
Ellen M. Rosencrans ◽  
Michael D. Vanden Berg
Keyword(s):  
Green River Formation ◽  
Uinta Basin ◽  
Green River ◽  
Climatic Control

scholarly journals Modelling spreading of an infection using time series by a novel family of models; fitting the time series of the confirmed cases of COVID-19 in China

2020 ◽  
Vol 9 (s1) ◽  
Author(s):  
Babak Jamshidi ◽  
Shahriar Jamshidi Zargaran ◽  
Mansour Rezaei
Keyword(s):  
Infectious Disease ◽  
Time Series ◽  
Communicable Disease ◽  
Time Series Models ◽  
Cumulative Number ◽  
The Novel ◽  
New Family ◽  
Two Samples ◽  
Almost All ◽  
Number Of Individuals

AbstractIntroductionTime series models are one of the frequently used methods to describe the pattern of spreading an epidemic.MethodsWe presented a new family of time series models able to represent the cumulative number of individuals that contracted an infectious disease from the start to the end of the first wave of spreading. This family is flexible enough to model the propagation of almost all infectious diseases. After a general discussion on competent time series to model the outbreak of a communicable disease, we introduced the new family through one of its examples.ResultsWe estimated the parameters of two samples of the novel family to model the spreading of COVID-19 in China.DiscussionOur model does not work well when the decreasing trend of the rate of growth is absent because it is the main presumption of the model. In addition, since the information on the initial days is of the utmost importance for this model, one of the challenges about this model is modifying it to get qualified to model datasets that lack the information on the first days.

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