2002
DOI: 10.2172/815454
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3-D Reservoir and Stochastic Fracture Network Modeling for Enhanced Oil Recovery, Circle Ridge Phosphoria/Tensleep Reservoir, Wind River Reservation, Arapaho and Shoshone Tribes, Wyoming

Abstract: This report describes the results made in fulfillment of contract DE-FG26-00BC15190, "3-D Reservoir and Stochastic Fracture Network Modeling for Enhanced Oil Recovery, Circle Ridge Phosphoria/Tensleep Reservoir, Wind River Reservation, Arapaho and Shoshone Tribes, Wyoming". The goal of this project is to improve the recovery of oil from the Tensleep and Phosphoria Formations in Circle Ridge Oilfield, located on the Wind River Reservation in Wyoming, through an innovative integration of matrix characterization,… Show more

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Cited by 5 publications
(2 citation statements)
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“…Gilbertson (2006) estimated fracture aspect ratio for the Tensleep Sandstone using a value for mean fracture length of 50 m (164 ft) reported by LaPointe et al (2002). Gilbertson (2006) reported a geometric mean fracture height of 17.53 m (57.5 ft) and used the mean length reported by LaPointe et al (2002) to obtain an aspect ratio of 0.35. In this study, we estimate aspect ratio using mean height (3.04 m [10 ft]) and mean length (9.1 m [30 ft]) to obtain an aspect ratio of 0.33.…”
Section: Aspect Ratiomentioning
confidence: 99%
“…Gilbertson (2006) estimated fracture aspect ratio for the Tensleep Sandstone using a value for mean fracture length of 50 m (164 ft) reported by LaPointe et al (2002). Gilbertson (2006) reported a geometric mean fracture height of 17.53 m (57.5 ft) and used the mean length reported by LaPointe et al (2002) to obtain an aspect ratio of 0.35. In this study, we estimate aspect ratio using mean height (3.04 m [10 ft]) and mean length (9.1 m [30 ft]) to obtain an aspect ratio of 0.33.…”
Section: Aspect Ratiomentioning
confidence: 99%
“…However, fault zones and fracture networks often bear an inherent small-scale complexity close to the seismic resolution, so that it is difficult to resolve them directly from the data. For this purpose, various options for attribute analyses e.g., coherence, curvature, RMS amplitude and instantaneous frequencies, ant-tracking analysis, spectral decomposition using wavelet transform, impedance inversion and crossplots (Gazar et al, 2011;Suo et al, 2012;Pussak et al, 2014;Marfurt, 2018;Ziesch et al, 2019;Bauer et al, 2020;Wadas and von Hartmann, 2022;Wadas et al, 2023) and numerical modelling, such as 3-D palinspastic reconstruction (LaPointe et al, 2002), exist to better explore the sub-seismic scale of fracture networks (Krawczyk et al, 2015).…”
Section: Introductionmentioning
confidence: 99%