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Tectonics and Structural Geology

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Minds over Methods: What controls the shape of oceanic ridges?

Minds over Methods: What controls the shape of oceanic ridges?

In this edition of Minds over Methods, Aurore Sibrant, postdoc at Bretagne Occidentale University (France) explains how she studies the shape of oceanic ridges, and which parameters are thought to control this shape. By using laboratory experiments combined with observations from nature, she gives new insights into how spreading rates and lithosphere thickness influence the development of oceanic ridges. 

 

Credit: Aurore Sibrant

What controls the shape of oceanic ridges? Constraints from analogue experiments

Aurore Sibrant, Post-doctoral fellow at Laboratoire Géosciences Océans, Bretagne Occidentale University, France

Mid-oceanic ridges with a total length > 70 000 km, are the locus of the most active and voluminous magmatic activity on Earth. This magmatism directly results from the passive upwelling of the mantle and decompression melting as plates separate along the ridge axis. Plate separation is taken up primarily by magmatic accretion (formation of the oceanic crust), but also by tectonic extension of the lithosphere near the mid-ocean ridge, which modifies the structure of the crust and morphology of the seafloor (Buck et al., 2005). Therefore, the morphology of the ridge is not continuous but dissected by a series of large transform faults (> 100 km) as well as smaller transform faults, overlapping spreading centres and non-transform offsets (Fig. 1). Altogether, those discontinuities form the global shape of mid-ocean ridges. While we understand many of the basic principles that govern ridges, we still lack a general framework for the governing parameters that control segmentation across all spreading rates and induce the global shape of ridges.

Geophysical (Schouten et al., 1985; Phipps Morgan and Chen, 1993; Carbotte and Macdonald, 1994) and model observations (Oldenburg and Brune, 1975, Dauteuil et al., 2002, Püthe and Gerya, 2014) suggest that segmentation of oceanic ridges reflects the effect of spreading rate on the mechanical properties and thermal structure of the lithosphere and on the melt supply to the ridge axis. To understand the conditions that control the large-scale shape of mid-ocean ridges, we perform laboratory experiments. By applying analogue results to observations made on Earth, we obtain new insight into the role of spreading velocity and the mechanical structure of the lithosphere on the shape of oceanic ridges.

 

Laboratory experiments

The analogue experiment is a lab-scale, simplified reproduction of mid-oceanic ridges system. Our set-up yields a tank filled from bottom to top by a viscous fluid (analogous to the asthenosphere) overlain by the experimental “lithosphere” that can adopt various rheologies and a thin surface layer of salted water. This analogue lithosphere is obtained using a suspension of silica nanoparticles which in contact with the salted water emplaced on the surface of the fluid causes formation of a skin or “plate” that grows by diffusion. This process is analogous to the formation of the oceanic lithosphere by cooling (Turcotte and Schubert, 1982). With increasing salinity, the rheology of the skin evolves from viscous to elastic and brittle behaviour (Di Giuseppe et al., 2012; Sibrant and Pauchard, 2016).

The plate is attached to two Plexiglas plates moving perpendicularly apart at a constant velocity. The applied extension nucleates fractures, which rapidly propagate and form a spreading axis. Underlying, less dense, fresh fluid responds by rising along the spreading axis, forming a new skin when it comes into contact with the saline solution. By separately changing the surface water salinity and the velocity of the plate separation, we independently examine the role of spreading velocity and axial lithosphere thickness on the evolution of the experimental ridges.

 

Figure 2. Close up observations of analogue mid-oceanic ridges and schematic interpretation for different spreading velocity. The grey region is a laser profile projected on the surface of the lithosphere: the laser remains straight as long as the surface is flat. Here, the large deviation from the left to centre of the image reveals the valley morphology of the axis. Credit: Aurore Sibrant.

 

Analogue mid-oceanic ridges

Over a large range of spreading rates and salinities (Sibrant et al., 2018), the morphology of the axis is different in shape. The ridge begins with a straight axis (initial condition). Then during the experiment, mechanical instabilities such as non-transform offset, overlapping spreading centres and transform faults develop (Fig. 2) and cause the spreading axis to have a non-linear geometry (Fig. 3). A key observation is the variation of the shape of the analogue ridges with the spreading rate and salinities. For similar salinity and relative slow spreading rates, each segment is offset by transform faults shaping a large tortuous ridge (i.e. non-linear geometry). In contrast, at a faster spreading rate, the ridge axis is still offset by mechanical instabilities but remains approximately linear.

Figure 3. Ridge axis morphology observed in the experiments and schematic structural interpretations of the ridge axis, transform faults (orange ellipsoids) and non-transform faults (purple ellipsoids). Measurements of lateral deviation (LD) correspond to the length of the arrows. For comparison, white squares represent the size of closeup shows in Fig 2. Credit: Aurore Sibrant.

We can quantify the ridge shape by measuring the total lateral deviation, which is the total accumulated offset of the axis, when the tortuosity amplitude becomes stable. For cases with similar salinities, the results indicate two trends. First, the lateral deviation is high at slow spreading ridges and decreases within increasing spreading rate until reaching a minimum lateral deviation value for a given critical spreading rate (Fig 4A). Then the lateral deviation remains constant despite the increasing spreading rate. Experiments with different salinities also present a transition between tortuous and linear ridges. These two trends reflect how the lithosphere deforms and fails. In the first regime, the axial lithosphere is thick and is predominantly elastic-brittle. In such cases, the plate failures occur from the surface downwards through the development of faults: it is a fault-dominated regime. In contrast, for faster spreading rate or smaller salinities, the axial lithosphere is thin and is predominantly plastic. Laboratory inspection indicates that fractures in plastic material develop from the base of the lithosphere upwards: it is a fluid-intrusion dominated regime.

 

 

Comparison with natural mid-oceanic ridge

In order to have a complete understanding of the mid-oceanic ridge system, it is essential to compare the laboratory results with natural examples. Hence, we measure the lateral deviation of nature oceanic ridges along the Atlantic, Pacific and Indian ridges. The measurements reveal the same two regimes as found in laboratory data. The remaining step consists of finding the appropriate scaling laws to superpose the natural and experiment data. This exercise requires dynamics similarity between analogue model and real-world phenomena which is demonstrated using dimensionless numbers (Sibrant et al., 2018). Particularly, the “axial failure parameter – πF” describes the predominant mechanical behaviour of the lithosphere relative to its thickness. Low-πF accretion is dominated by fractures in a predominantly elastic-brittle lithosphere: the lateral deviation of the ridges is tortuous, while at higher pF, accretion is dominated by intrusion in a predominantly plastic lithosphere: the shape of the mid oceanic ridges is mostly linear (Fig 4B).

 

Figure 4. (A) Lateral deviation values measured in the experiments in function of the spreading rate velocities and salinities. (B) Evolution of the lateral deviation of the ridge axis, normalized by the critical axial thickness (Zc) relative to the axial failure parameter. Dark grey is the laboratory experiments and the colored circles are the Earth data. Adapted from Sibrant et al., 2018.

 

Our experiments give insight into the role of axial failure mode (fault-dominated or intrusion-dominated) on the shape of mid-oceanic ridges. In the future, we want to use this experimental approach to investigate the origin of mechanical instabilities, such as transform faults or overlapping spreading centres. This experimental development and results are a collaborative work between Laboratoire FAST at Université Paris-Saclay and Department of Geological Sciences at the University of Idaho and involves E. Mittelstaedt, A. Davaille, L. Pauchard, A. Aubertin, L. Auffray and R. Pidoux.

 

 

References
Buck, W.R., Lavier, L.L., Poliakov, A.N.B., 2005. Modes of faulting at mid-ocean ridges. Nature 434, 719-723.
Schouten, H., Klitgord, K.D., Whitehead, J.A., 1985. Segmentation of mid-ocean ridges. Nature 317, 225-229.
Carbotte, S.M., Macdonald, K. C., 1994. Comparison of seafloor tectonic fabric at intermediate, fast, and super fast spreading ridges: Influence of spreading rate, plate motions, and ridge segmentation on fault patterns. J. Geophys. Res. 99, 13609-13631.
Phipps Morgan, J., Chen, J., 1993. Dependence of ridge-axis morphology on magma supply and spreading rate. Nature 364, 706-708.
Oldenburg, D.W., Brune, J.N., 1975. An explanation for the orthogonality of ocean ridges and transform faults. J. Geophys. Res. 80, 2575-2585.
Dauteuil, O., Bourgeois, O., Mauduit, T., 2002. Lithosphere strength controls oceanic transform zone structure: insights from analogue models. Geophys. J. Int. 150, 706-714.
Püthe, C., Gerya, T., 2014. Dependence of mid-ocean ridge morphology on spreading rate in numerical 3-D models. Gondwana Res. 25, 270-283.
Turcotte, D., Schubert, G., Geodynamics (Cambridge Univ. Press, New York, 1982).
Di Giuseppe, E., Davaille, A., Mittelstaedt, E., Francois, M., 2012. Rheological and mechanical properties of silica colloids: from Newtonian liquid to brittle behavior. Rheologica Acta 51, 451-465.
Sibrant, A.L.R., Pauchard, L., 2016. Effect of the particle interactions on the structuration and mechanical strength of particulate materials. European Physics Lett., 116, 4, 10.1209/0295-5075/116/49002.
Sibrant, A.L.R., Mittelstaedt, E., Davaille, A., Pauchard, L., Aubertin, A., Auffray, L., Pidoux, R., 2018. Accretion mode of oceanic ridges governed by axial mechanical strength. Nature Geoscience 11, 274-279.

 

Minds over Methods: Experimental seismotectonics

Minds over Methods: Experimental seismotectonics

For our next Minds over Methods, we go back into the laboratory, this time for modelling seismotectonics! Michael Rudolf, PhD student at GFZ in Potsdam (Germany), tells us about the different types of analogue models they perform, and how these models contribute to a better understanding of earthquakes along plate boundaries.

 

Credit: Michael Rudolf

Experimental seismotectonics – Seismic cycles and tectonic evolution of plate boundary faults

Michael Rudolf, PhD student at Helmholtz Centre Potsdam – German Research Centre for Geosciences GFZ

The recurrence time of large earthquakes that happen along lithospheric-scale fault zones such as the San Andreas Fault or Chile subduction megathrusts, is very long (≫100 yrs.) compared to human timescales. The scarcity of such events over the instrumental record of around 60 years is unfortunate for a statistically sound analysis of the earthquake time series.

So far, only few megathrust events have been monitored in detail with near-field seismic and geodetic networks. To circumvent this lack of observational data, we at Helmholtz Tectonic Laboratory use analogue modelling to understand plate boundary faulting on multiple time-scales and the implications for seismic hazard. We use models of strike-slip zones and subduction zones, to investigate several aspects of the seismic cycle. Additionally, numerical simulations accompany and complement each experimental setup using experimental parameters.

 

Seismotectonic scale models
In my project, we develop experiments that can model multiple seismic cycles in strike-slip conditions. Our study employs two types of experimental setups both are using the same materials. The first is simpler (ring shear setup) and is able to show the on-fault rupture propagation. The second is geometrically more similar to the natural system, but only the surface deformation is observable.

To model rupture propagation, we introduce deformable sliders in a ring shear apparatus. Two cylindrical shells of ballistic gelatine (Ø20 cm), representing the side walls, rotate against each other, with a thin layer (5 mm) of glass beads (Ø355-400µm) in between representing an annular fault zone. A see-through lid connected to force sensors holds the upper shell in place, whereas the machine rotates the lower shell. Through the transparent lid and upper shell, we directly observe the fault slip. We can vary the normal stress on the fault (<20 kPa) and the loading velocity (0.0005 – 0.5 mm/s).

The next stage of analogue model, features depth-dependent normal stress and a rheological layering mimicking the strike-slip setting in the uppermost 25-30 km of the lithosphere (see also Mehmet Köküm’s blog post). A gelatine block (30x30cm) compressed in uniaxial setting represents the elastic upper crust under far-field forcing. Embedded in the block is a thin fault filled with quartz glass beads. The ductile lower crust is modelled using viscoelastic silicone oil. The model floats in a tank of dense sugar solution, to guarantee free-slip, stress-free boundaries.

 

Figure 2 – Setup and monitoring technique during an experiment. Several cameras record the displacement field and the ring shear tester records the experimental results. Credit: Michael Rudolf

 

Analogue earthquakes
Both setups generate regular stick-slip cycles including minor creep. Long phases of quiescence, where no slip or very slow creep occurs, alternate with fast slip events sometimes preceded by slow slip events. The moment magnitude of analogue earthquake events is Mw -7 to -5. The cyclic recurrence of slip events is an analogue for the natural seismic cycle of a single-fault system.

 

Figure 3 – Detailed setup and results from the ring shear tester experiments. The upper right image shows a snapshot of an analogue earthquake rupture along the fault zone. The plot shows the recorded shear forces and slip velocities over one hour of experiment. Credit: Michael Rudolf

 

Optical cameras record the slip on the fault and the deformation of the sidewalls. Using digital image correlation techniques, we are able to visualize accurately deformations on the micrometre scale at high spatial and temporal resolution. Accordingly, we can verify that analogue earthquakes behave kinematically very similar to natural earthquakes. They generally nucleate where shear stress is highest, and then propagate radially until the seismogenic width is saturated. In the end, the rupture continues laterally along the fault strike. Our experiments give insight into the role of viscoelastic relaxation, interseismic creep, and slip transients on the recurrence of earthquakes, as well as the control of loading conditions on seismic coupling and rupture dynamics.

 

Figure 4 – Setup and Results for the strike-slip geometry. The surface displacement field is very similar to natural earthquakes. The plot shows that due to technical limitations of this setup, fewer events are recorded but the slip velocities are higher. Credit: Michael Rudolf

 

Future developments
Together with our partners in the Collaborative Research Centre (CRC1114 – Scaling Cascades in Complex Systems) we employ a new mathematical and numerical description of the fault system, to simulate our experiments and get a physical understanding of the empirical friction laws. In the future, we want to use this multiscale spatial and temporal approach to model complex fault networks over many seismic cycles. The experiments serve as benchmarks and cross-validation for the numerical code, which in the future will be using natural parameters to get a better geological and mathematical understanding of earthquake slip phenomena and occurrence patterns in multiscale fault networks.

Minds over Methods: Block modeling of Anatolia

 

How can we use GPS velocities to learn more about present-day plate motions and regional deformation? In this edition of Minds over Methods, one of our own blogmasters Mehmet Köküm shares his former work with you! For his master thesis at Indiana University, he used block modeling to better understand the plate motion and slip rates of Anatolia and surrounding plates.

 

credit: Mehmet Köküm

Using block modeling to constrain present-day deformation of Anatolia and slip rates along the North Anatolian Fault

Mehmet Köküm, researcher at Firat University, Turkey

Until the late 1980’s, geological features such as offset of geomorphological markers were mainly used to determine historical slip rates along faults. Since the mid 1990’s, however, GPS has been widely used since it gives more accurate estimates of present-day slip rates by calculating strain accumulation at the crust. In this work, I use a GPS derived velocity field of Anatolia including data from 1988 to 2005 by Reilinger et al. (2006).

Turkey (Anatolian Plate) is located in the center of the Alpine fold and thrust belt. Due to the closure of different branches of the Neo-Tethys Ocean, main tectonic features of the Anatolian Plate are complicated by interactions between several tectonic plates.  The Arabian plate collides with the African plate in the south and the Eurasian plate in the north while the African plate subducts beneath the Anatolian plate along the Hellenic-Cyprus trench. As a result of these complex tectonic structures, the Anatolian plate displays various tectonic styles simultaneously.

Modeling and Data
Kinematic block modeling of interseismic surface motions has been used in different formats by several authors (e.g., McClusky et al. 2000; Westaway 2000; Barka and Reilingier 1997, 2006). The block modeling approach used here is described by Johnson and Fukuda (2010). In this study we used an elastic block model, which is a traditional block model that assumes no long-term deformation of the blocks. For simplicity, all faults are vertical, plates are considered as blocks and are assumed to be rigid. Block boundaries are defined from historic earthquakes, mapped faults and seismicity. Many of the major structures in Anatolia are well known except for a few submarine structures.

 

Map showing selected block model including of 14 blocks (or plates). Credit: Mehmet Köküm

 

Locking Depth
Locking depths indicate the depth for which a fault is completely locked above and creeping below. Estimates of these locking depths are output of the modeling studies and should correlate with the depth of major earthquakes along related faults. Meade and Hager (2005) suggest that there is a relation between locking depth and fault slip rates. Shallower locking depths correlate with slower slip rate estimates; therefore, GPS velocities near locked faults have slower velocities (Reilinger et al., 2006).

 

Elastic-half-space model showing fault creep at surface, locked (nonslipping) fault at depth, and freely sliding zone at great depth. (source: SFSU CREEP Project)

 

Results
On the basis of the GPS velocity field, the Anatolia and Aegean blocks show counterclockwise motion with respect to the Eurasian plate and the rate of the motion increases towards the west. The locking depth variations of the work are between 20-25 km, which correlates with the focal depths of significant earthquakes. The major fault slip rates are consistent with some of the geological slip rate estimates.

 

Results of the model. Figure shows Anatolian plate motion and slip rate estimates of major faults. Credit: Mehmet Köküm

Minds over Methods: Reconstruction of salt tectonic features

Minds over Methods: Reconstruction of salt tectonic features

What is the influence of salt tectonics on the evolution of sedimentary basins and how can we reconstruct such salt features? Michael Warsitzka, PhD student at the Friedrich Schiller University of Jena, explains which complementary methods he uses to better understand salt structures and their relation to sedimentary basins. Enjoy!

 

Credit: Michael Warsitzka

Reconstruction of salt tectonic features from analogue models and geological cross-sections

Michael Warsitzka, PhD student, Institute of Geosciences, Friedrich Schiller University Jena

Salt tectonics, as a sub-discipline of structural geology, describe deformation structures developing due to the special deformation behaviour of salt (as synonym for a sequence of evaporitic rocks). Salt behaves like a viscous fluid over geological time scales and, therefore, it may flow due to lateral differences in thickness and density of the supra-salt layers. This influences the structural evolution of sedimentary basins, because salt flow can modify the amount of regional subsidence of the basin. Local sinks (“minibasins”) develop in regions from where salt is squeezed out and salt structure uplifts, e.g. diapirs or pillows evolve in regions of salt influx. Unfortunately, temporal changes of salt flow patterns are often difficult to reconstruct owing to enigmatic ductile deformation structures in salt layers. Understanding the evolution of salt-related structures requires either forward modelling techniques (e.g. physically scaled sandbox experiments) or restoration of sedimentary and tectonic structures of the supra-salt strata.

In my PhD thesis, I tried to integrate both, analogue modelling and restoration, to investigate salt structures and related minibasins developed in the realm of extensional basins. The sandbox model is a lab-scale, simplified representative of natural salt-bearing grabens, e.g. the Glückstadt Graben located in the North German Basin (Fig. 1). A viscous silicone putty and dry, granular sand were used to simulate ductile salt and brittle overburden sediments. Cross sections were cut through the model at the end of each experiment to conduct reconstruction of the final experimental structures. The material movements were monitored with a particle tracking velocimetry (PIV) technique at the sidewalls of the experimental box.

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Fig 1: 2D restoration of the supra-salt (post-Permian) strata in the Glückstadt Graben (Northern Germany). Credit: Michael Warsitzka

Using experimental and geological cross sections, structures in the overburden of the ductile layer can be reconstructed, if present-day layer geometries and lithologies of the overburden strata can be identified. From natural clastic and carbonatic sediments we know that they compact with burial, reducing the layer thickness. Therefore, the reconstruction procedure sequentially removes the uppermost layer and layers beneath are decompacted and shifted upwards to a horizontal surface (Fig. 2). The sequence of decompaction and upward shifting is then repeated until the earliest, post-salt stage is reached (Fig. 1). It intends to restore the initial position, shape and thickness of each reconstructed layer.

In analogue experiments, no decompaction is necessary, because the compressibility of the granular material is insignificant for depths of a few centimetre. Restoration can be directly applied to coloured granular layers revealing detailed layer geometries for each experimental period (Fig. 2a). The PIV technique displays coeval material movement and strain patterns occurring during the subsidence of the experimental minibasins (Fig. 2b). Based on the observation that the experimental structures resemble those reconstructed from the natural example (Glückstadt Graben during the Early Triassic, Fig. 1), it can be inferred that strain patterns observed in the experiments took place in a similar manner during the early stage of extensional basins. This demonstrates the advantage of applying both methods. First, original geometries of basin structures can be determined from the restoration and then reproduced in the model. If the restored geometries are suitably validated by the models, the kinematics observed in the model can be translated back to nature and help to understand the effect of salt flow on the regional subsidence pattern.

Fig 2: Result of an analogue model showing (a) reconstructed sand layers restored from a central cross section, and (b) monitored displacement and strain patterns in the viscous layer above the left basal normal fault. Credit: Michael Warsitzka

Minds over Methods: Sensing Earth’s gravity from space

Minds over Methods: Sensing Earth’s gravity from space

How can we learn more about the Earth’s interior by going into space? This edition of Minds over Methods discusses using satellite data to study the Earth’s lithospere. Anita Thea Saraswati, PhD student at the University of Montpellier, explains how information on the gravity of the Earth is obtained by satellites and how she uses this information to get to know more about the lithosperic structure in subduction zones.

 

Sensing Earth’s gravity from space

Anita Thea Saraswati – PhD student, Géosciences Montpellier

From the basic physics we all know that the value of the gravity is a constant 9.81 meter per second squared. This assumption would be true if the Earth were a smooth nonrotating spherical symmetric body made of uniform element and material. However, because of the Earth’s rotation, internal lateral density variation, and the diversity of the topography (including mountains, valleys, oceans and glaciers), the gravity  varies all over the surface. These tiny changes in gravity due to the mass variations could be a crucial hint for understanding the structure of the Earth, both on the surface and at depth.

The determination of Earth’s gravity field has benefited from various gravity satellite missions that have been launched recently. Among them are the Challenging Minisatellite Payload (CHAMP) (2000-2010), the Gravity Recovery and Climate Experiment (GRACE) (2002-recent), and most recently the Gravity field and steady-state Ocean Circulation Explorer (GOCE) (2009-2013). From these missions, finally a global high quality coverage of Earth’s gravity field became available. (Yay!)

GRACE observation data are very useful for the temporal analysis of changes in gravity. For example to detect the gravity signal before and after a big earthquake, like the Sumatra Mw 9.1 (2004) and Tohoku Mw 9.1 (2011) ones. By analyzing the changes of gravity signal during a certain period of time, it could also be used to detect the drought over a large scale area, which is used in several areas in Africa and Australia.

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Design of GOCE satellite observation. A geoid’s shape is showed on the bottom left. On the top right, the GOCE gravity gradients in six components. (Source : ESA)

 

Meanwhile, GOCE is very suitable for the construction of a static model of Earth’s gravity field. Since this satellite has a very low orbit, ~250 km above mean sea level, it has a better spatial resolution. Its accuracy is also better than the previous missions, up to 1 mGal. GOCE is equipped with a gradiometer, which measures the gravity acceleration in three directions (x, y, and z). Afterwards this information is processed into a gravity-gradient dataset containing six components (XX, XY, XZ, YY, YZ, ZZ).

This gravity gradient is the first derivative of the gravity acceleration, which provides us better information about the geometry of the earth’s structure than the gravity acceleration itself. For my PhD, I use this gravity gradient dataset to analyze the lithospheric structure of subduction zones. Before treating the GOCE observation data, I am developing a computational code to calculate the gravity and gravity gradient due to the effect of topography, also called the topographic reduction. The observed gravity and gravity gradient values will be reduced by this topography effect in order to get the anomaly signal. This means that only the signal due to other geodynamic phenomena over the observed area (e.g. slab, isostasy, mantle plum, etc.) is left. By doing further processing, we can obtain the lateral variations of the lithospheric structure in the study areas and then investigate the correlation with the occurrence of mega-earthquakes in these subduction zones.

Since there is still some ambiguity about the information that is produced by gravity data only, it is better to combine the use of them with others geophysical or geological measurements, e.g. seismic tomography measurements and magnetic field observations.

 

Global coverage of GOCE gravity gradient (in milliEötvös) in radial direction (ZZ) (Panet, I. et al., 2014)

 

Reference:

Panet, I., Pajot-Métivier, G., Greff-Lefftz, M., Métivier, L., Diament, M. and Mandea, M., 2014. Mapping the mass distribution of Earth/’s mantle using satellite-derived gravity gradients. Nature Geoscience7(2), pp.131-135.

Minds over Methods: studying dike propagation in the lab

Minds over Methods: studying dike propagation in the lab

Have you ever thought of using gelatin in the lab to simulate the brittle-elastic properties of the Earth’s crust? Stefano Urbani, PhD student at the university Roma Tre (Italy), uses it for his analogue experiments, in which he studies the controlling factors on dike propagation in the Earth’s crust. Although we share this topic with our sister division ‘Geochemistry, Mineralogy, Petrology & Volcanology (GMPV)’, we invited Stefano to contribute this post to ‘Minds over Methods’, in order to show you one of the many possibilities of analogue modelling. Enjoy!

 

dscn0024Using analogue models and field observations to study the controlling factors for dike propagation

Stefano Urbani, PhD student at Roma Tre University

The most efficient mechanism of magma transport in the cold lithosphere is flow through fractures in the elastic-brittle host rock. These fractures, or dikes, are commonly addressed as “sheet-like” intrusions as their thickness-length aspect ratio is in the range of 10-2 and 10-4 (fig.3).

Understanding their propagation and emplacement mechanisms is crucial to define how magma is transferred and erupted. Recent rifting events in Dabbahu (Afar, 2005-2010) and Bardarbunga (Iceland, 2014, fig.1) involved lateral dike propagation for tens of kilometers. This is not uncommon: eruptive vents can form far away from the magma chamber and can affect densely populated areas. Lateral dike propagation has also been observed in central volcanoes, like during the Etna 2001 eruption. Despite the fact that eruptive activity was mostly fed by a vertical dike to the summit of the volcano, several dikes propagated laterally from the central conduit and fed secondary eruptive fissures on the southern flank of the volcanic edifice (fig.2). Lateral propagation can hence occur at both local (i.e. central volcanoes) and regional (i.e. rift systems) scale, suggesting a common mechanism behind it.

fig-3mario-cipollini

Fig. 2 Lava flow near a provincial road, a few meters from hotels and souvenir shops, during the 2001 lateral eruption at Etna. Credit: Mario Cipollini

Therefore, it is of primary importance to evaluate the conditions that control dike propagation and/or arrest to try to better evaluate, and eventually reduce, the dike-induced volcanic risk. Our knowledge of magmatic systems is usually limited to surface observations, thus models are useful tools to better understand geological processes that cannot be observed directly. In particular, analogue modelling allows simulating natural processes using scaled materials that reproduce the rheological behavior (i.e ductile or brittle) of crust and mantle. In structural geology and tectonics analogue modelling is often used to understand the nature and mechanism of geological processes in a reasonable spatial and temporal scale.

d_grad_dike57_080Field evidence and theoretical models indicate that the direction of dike propagation is controlled by many factors including magma buoyancy and topographic loads. The relative weight of these factors in affecting vertical and lateral propagation of dikes is still unclear and poorly understood. My PhD project focuses on investigating the controlling factors on dike propagation by establishing a hierarchy among them and discriminating the conditions favoring vertical or lateral propagation of magma through dikes. I am applying my results to selected natural cases, like Bardarbunga (Iceland) and Etna (Italy). To achieve this goal, I performed analogue experiments on dike intrusion by injecting dyed water in a plexiglass box filled with pig-skin gelatin. The dyed water and the gelatin act as analogues for the magma and the crust, respectively. Pig-skin gelatin has been commonly used in the past to simulate the brittle crust, since at the high strain rates due to dike emplacement it shows brittle-elastic properties representative of the Earth’s crust. We record all the experiments with several cameras positioned at different angles, taking pictures every 10 seconds. This allows us to make a 3D reconstruction of the dike propagation during the experiment.

In order to have a complete understanding of the dike intrusion process it is essential to compare the laboratory results with natural examples. Hence, we went to the field and studied dikes outcropping in extinct and eroded volcanic areas, with the aim of reconstructing the magma flow direction (Fig. 3). This allows validating and interpreting correctly the observations made during the laboratory simulations of the natural process that we are investigating.

fig-1

Fig. 3 Outcrop of dikes intruding lava flows. Berufjordur eastern Iceland.

 

Minds over Methods: Numerical modelling

Minds over Methods: Numerical modelling

Minds over Methods is the second category of our T&S blog and is created to give you some more insights in the various research methods used in tectonics and structural geology. As a numerical modeller you might wonder sometimes how analogue modellers scale their models to nature, or maybe you would like to know more about how people use the Earth’s magnetic field to study tectonic processes. For each blog we invite an early career scientist to share the advantages and challenges of their method with us. In this way we are able to learn about methods we are not familiar with, which topics you can study using these various methods and maybe even get inspired to use a multi-disciplinary approach! This first edition of Minds over Methods deals with Numerical Modelling and is written by Anouk Beniest, PhD-student at IFP Energies Nouvelles (Paris).

 

Approaching the non-measurable

Anouk Beniest, PhD-student at IFP Energies Nouvelles, Paris

‘So, what is it that you’re investigating?’ It’s a question every scientist receives from time to time. In geosciences, the art of answering this question is to explain the rather abstract projects in normal words to the interested layman. Try this for example: “A long time ago, the South American and African Plate were stuck together, forming a massive continent, called Pangea, for many millions of years. Due to all sorts of forces, the two plates started to break apart and became separated. During this separation hot material from deep down in the earth rose to the surface increasing the temperature of the margins of the two continents. How exactly did this temperature change over time, since the separation until present-day? How did this change affect the basins along continental margins?”

These are legitimate questions and not easy to answer, since we cannot measure temperature at great depth or back in time. In this first post on numerical methods, we will be balancing between geology and geophysics, highlighting the possibilities and limits of numerical modelling.

The migration of ‘temperature’ through the lithosphere is a process that takes time and depends heavily on the scale you look at. Surface processes that affect the surface temperature can be measured and monitored, yielding interesting results on the present-day state and variations of the temperature. The influence of mantle convection cycles and radiogenic heat production are already more difficult to identify, take much more time to evolve and might not even affect the surface processes that much. Going back in time to identify a past thermal state of the earth seems almost impossible. This is where numerical models can be of use, to improve, for example, our understanding on the long-term behaviour of ‘temperature’.

Temperature is a parameter that affects and is affected by a variety of processes. When enough physical principles are combined in a numerical model, we can simulate how the temperature has evolved over time. All kinds of different parameters need to be identified and, most importantly, they need to make sense and apply to the observation or process you try to reproduce. Some of these parameters can be identified in the lab, like the density or conductivity of different rock types. Others need to be extracted from physical or geological observations or even estimated.

Once the parameters have been set, the model will calculate the thermal evolution. It is not an easy task to decide if a simulation approaches the ‘real’ history and if we can answer the questions posed above. We should always realise that thermal model results at best approach the real world. We can learn about the different ways temperature changes over time, but we should always be on the hunt to find measurements and observations that confirm what we have learned from the simulations.

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