Finite-element modelling of contemporary and palaeo-intraplate stress using ABAQUS™

Dyksterhuis, S.; Albert, Richard A.; Müller, R. Dietmar

doi:10.1016/j.cageo.2004.10.011

Cited by 39 publications

(40 citation statements)

References 21 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Relative values for the Young's moduli (Table 1) of the different materials were calculated on the basis of a ratio to the highest rigidity as determined by Zuber et al [1989]. See Dyksterhuis et al [2005] for further review of modeling methods developed here.…”

Section: Modeling Methodsmentioning

confidence: 99%

Paleostress field evolution of the Australian continent since the Eocene

2005

Self Cite

View full text Add to dashboard Cite

[1] Although the low-order present stress field of most continents is fairly well established, information on paleostress fields is generally sparse. Knowledge of paleostresses is crucial for understanding brittle tectonic reactivation through time. The Indian-Australian plate lends itself well to a reconstruction of paleostresses, as it has undergone enormous changes in plate-driving forces through the Tertiary, and there is a rich record of fault reactivation from sedimentary basins. We reconstruct the plate boundary configuration and age-area distribution of ocean crust around Australia through time to obtain estimates for ridge push, slab pull, and collisional forces acting on the Indian-Australian plate since the Eocene. Other model parameters we explore are the effects of the Australian-Antarctic discordance and the mechanical strength of the Australian continental margin. We apply these constraints to model the orientation of the maximum horizontal compressive stress (S Hmax ) regime for the present, early Miocene, and early Eocene using the commercial software ABAQUS 2 along with the optimization software Nimrod/O. We use an elastic two-dimensional plane stress finite element model with a resolution of $0.2°in both longitude and latitude. Realistic elastic parameters representing different rock types and geologic provinces for the Australian continent have been included to model the stress field of a heterogeneous plate. We show that spatially significant rotations of S Hmax directions can be modeled as a consequence of perturbations of S Hmax in areas of juxtaposed rigid and compliant rheologies. The absence of the collisional Papua New Guinea boundary in the Miocene and reduced ridge push force from the south result in stress directions considerably different from the present. Stress directions over the northern Australian continent in the early Miocene in particular show large disparity with present stress directions. Stress orientations for the Australian plate during the early Eocene are controlled predominantly by ridge push forces arising from spreading in the Wharton Basin in the Indian Ocean and vary substantially with stress directions in the early Miocene and the present because of the drastically different plate geometry and boundary configurations. Fault reactivation histories observed on the northwest shelf of Australia and in the Bass Strait region are consistent with modeled changes in stress directions through time.

show abstract

Section: Modeling Methodsmentioning

confidence: 99%

Paleostress field evolution of the Australian continent since the Eocene

2005

Self Cite

View full text Add to dashboard Cite

show abstract

“…There are several studies on tectonic plate scale stress orientation patterns in 2-D (e.g. Coblentz and Richardson, 1996;Dyksterhuis et al, 2005;Humphreys and Coblentz, 2007;Jarosinski et al, 2006), large-scale (regional) models in 3-D (Buchmann and Connolly, 2007;Hergert and Heidbach, 2011;Parsons, 2006), as well as local (reservoir-scale) 3-D models (e.g. Fischer and Henk, 2013;Heidbach et al, 2013;Henk, 2005;Orlic and Wassing, 2012;Van Wees et al, 2003).…”

Section: Motivationmentioning

confidence: 99%

3-D geomechanical–numerical model of the contemporary crustal stress state in the Alberta Basin (Canada)

Reiter

Heidbach

2014

Solid Earth

View full text Add to dashboard Cite

Abstract. In the context of examining the potential usage of safe and sustainable geothermal energy in the Alberta Basin, whether in deep sediments or crystalline rock, the understanding of the in situ stress state is crucial. It is a key challenge to estimate the 3-D stress state at an arbitrarily chosen point in the crust, based on sparsely distributed in situ stress data.To address this challenge, we present a large-scale 3-D geomechanical-numerical model (700 km×1200 km×80 km) from a large portion of the Alberta Basin, to provide a 3-D continuous quantification of the contemporary stress orientations and stress magnitudes. To calibrate the model, we use a large database of in situ stress orientation (321 S Hmax ) as well as stress magnitude data (981 S V , 1720 S hmin and 2 (+11) S Hmax ) from the Alberta Basin. To find the best-fit model, we vary the material properties and primarily the displacement boundary conditions of the model. This study focusses in detail on the statistical calibration procedure, because of the large amount of available data, the diversity of data types, and the importance of the order of data tests.The best-fit model provides the total 3-D stress tensor for nearly the whole Alberta Basin, and allows estimation of stress orientation and stress magnitudes in advance of any well. First-order implications for the well design and configuration of enhanced geothermal systems are revealed. Systematic deviations of the modelled stress from the in situ data are found for stress orientations in the Peace River and the Bow Island Arch as well as for leak-off test magnitudes.

show abstract

“…The initial WSM database release 1992, in addition to subsequent regional stress studies, also demonstrated that second-order stress patterns with spatial wavelengths of ~500 km can be caused by lithospheric flexure and intraplate lateral density contrasts, such as continental rifting, isostatic compensation, topography, and deglaciation (Gregersen and Basham, 1989;Zoback, 1992;Coblentz and Sandiford, 1994;Coblentz et al, 1998;Hillis and Reynolds, 2000;Zoback and Mooney, 2003;Dyksterhuis et al, 2005;Bird et al, 2006).…”

Section: Introductionmentioning

confidence: 99%