ALBERT

Description: Low-temperature plastic rheology of calcite plays a significant role in the dynamics of Earth's crust. However, it is technically challenging to study plastic rheology at low temperatures because of the high confining pressures required to inhibit fracturing. Micromechanical tests, such as nanoindentation and micropillar compression, can provide insight into plastic rheology under these conditions because, due to the small scale, plastic deformation can be achieved at low temperatures without the need for secondary confinement. In this study, nanoindentation and micropillar compression experiments were performed on oriented grains within a polycrystalline sample of Carrara marble at temperatures ranging from 23 to 175 °C, using a nanoindenter. Indentation hardness is acquired directly from nanoindentation experiments. These data are then used to calculate yield stress as a function of temperature using numerical approaches that model the stress state under the indenter. Indentation data are complemented by uniaxial micropillar compression experiments. Cylindrical micropillars ∼1 and ∼3 μm in diameter were fabricated using a focused ion beam-based micromachining technique. Yield stress in micropillar experiments is determined directly from the applied load and micropillar dimensions. Mechanical data are fit to constitutive flow laws for low-temperature plasticity and compared to extrapolations of similar flow laws from high-temperature experiments. This study also considered the effects of crystallographic orientation on yield stress in calcite. Although there is a clear orientation dependence to plastic yielding, this effect is relatively small in comparison to the influence of temperature.

Description: We use the unsupervised and supervised neural network methods together to predict lithology of a gas hydrate reservoir from downhole data in the Krishna–Godavari (KG) offshore basin, India. In this study, we successfully identify the host litho-units of gas hydrate and show its effects in the identification of lithology using neural network techniques, which is not reported earlier. We use well log data acquired at three holes (10A, 03A and 04A) in 2006 during the first expedition of the Indian National Gas Hydrate Program (NGHP-01). Five different logging while drilling data (e.g. density, neutron porosity, gamma ray, resistivity and sonic) are considered for the mapping of lithology and gas hydrate. In the presence of gas hydrate, the resistivity and sonic velocity of the host sediments increase significantly, whereas density, neutron porosity and gamma ray are negligibly affected. Therefore, we calculate resistivity and sonic velocity for water-saturated sediment (without gas hydrate) theoretically to remove the effects of gas hydrate. At first, we apply the seven unsupervised classification methods (i.e. elbow, dendrogram, K-means, 3-D clustering, principal component analysis, Devies–Bouldin index and self-organizing map) to the data with gas hydrate (e.g. observed) and without gas hydrate (i.e. water-saturated/theoretical) to assess the data dimensionality and the number of clusters/litho-units. Each of the unsupervised schemes has its own pros and cons, and may provide different number of cluster/litho-units; sometimes, it is difficult to interpret from only one method. However, all seven methods provide same number of clusters in our study. Then, we apply the supervised classification method (i.e. Bayesian neural networks optimized by hybrid Monte Carlo searching technique) to the training data to refine the defined litho-units and map them with depth. Our approach identifies four types of litho-units and illustrates that the lithology in this area is dominated by clay (∼64 per cent) with some amount of silty clay, silt and minor sand. Gas hydrate is found in clay, silty clay and silt and not in sand. Results also show that, if gas hydrate is not considered as a separate unit, it is distributed as lithology in its hosts (i.e. clay, silty clay and silt). The method is very stable up to ∼15 per cent of random noise added to the data and results are well matched with the analysis of recovered core data. Identified lithologies at three wells correlate very well with seismic section crossing the wells. Very low permeability (〈0.1 mD) estimated at three wells also indicates the clay-dominated lithology in our study area.

Description: Understanding the wave propagation in fluid-saturated cracked rocks is important for detecting and characterizing cracked reservoirs and fault zones with applications in geomechanics, hydrogeology, exploration geophysics and reservoir engineering. In sedimentary rocks, microscopic-scale pores are usually filled with fluid. One logical means of modelling the essential features of such rocks is to use poroelasticity theory. But previous models of wave propagation in cracked porous medium are either restricted to low frequencies at which effects of the elastic scattering (scattering into fast-P and S waves via mode conversion at the crack faces) are negligible or to the case that the crack-filling fluid is assumed to be incompressible. To overcome these restrictions, we consider the effects of crack fluid compressibility by extending spring condition into poroelasticity and derive exact solutions of the scattering problem of an incident P wave by a circular crack containing compressible fluid in a porous medium. Based on the solutions, we develop two different effective medium models to estimate frequency-dependent effective velocity and attenuation in a fluid-saturated porous rock with a set of aligned cracks. The mixed-boundary value problem reveals that both the wave-induced fluid flow (WIFF) and elastic wave scattering can cause important velocity dispersion and attenuation. The diffusion-type WIFF dominates the velocity change and attenuation for the low frequency range, while the elastic scattering dominates them for the relatively higher frequency range. The dependences of the P-wave velocity on the crack fluid compressibility are different at different frequencies. For the WIFF-dominated frequency range and Rayleigh-scattering frequency range, the P-wave velocity decreases with the crack fluid compressibility. In contrast, for the Mie scattering frequency range, the opposite occurs (the P-wave velocity increases with the crack fluid compressibility).

Description: Orphan Basin, a massive deepwater rifted basin off the northeastern coast of Newfoundland, was one of the targets of the 2009 SIGNAL (Seismic Investigations off Greenland, Newfoundland and Labrador) experiment to collect refraction/wide-angle reflection (RWAR) data from the Bonavista Platform, through the Orphan Basin, to the Orphan Knoll, and beyond into oceanic crust. Both the data from an earlier RWAR acquisition and the new data were jointly analysed in order to improve on the earlier velocity model and extend its coverage landward and seaward. The resulting velocity model is characterized by an 8–9-km-thick sedimentary package immediately outboard of the Bonavista Platform, which thins toward the Orphan Knoll and beyond. The shallowest modelled sedimentary layer, interpreted as Paleocene and younger post-rift sediments, does not show significant thickness variations and velocities do not exceed 3.3 km s–1. The second modelled sedimentary layer with laterally variable velocities ranging from 2.3 to 5.3 km s–1, interpreted as Late Cretaceous post-rift sediments, is thickest over an interpreted failed rift. The deepest modelled sedimentary layer consists of laterally variable velocities that do not exceed 5.9 km s–1 and is interpreted as possibly Jurassic to Early Cretaceous syn-rift sediments. The crust beneath the Bonavista Platform is subdivided into an upper (5.4–5.9 km s–1), middle (5.9–6.4 km s–1) and lower crust (6.4–6.9 km s–1). The middle crust is modelled as disappearing beneath the seaward limit of the Bonavista Platform at an interpreted failed rift, only to re-appear 100 km further seaward beneath the central Orphan Basin and extend to the seaward limit of the Orphan Knoll, beyond which the crust can be modelled by just an upper (5.0–6.7 km s–1) and a lower (6.7–7.0 km s–1) crustal layer. Towards land, for the first 450 km of the model, velocities generally follow the globally averaged velocity trend for rifted continental crust, albeit with slightly elevated velocities suggestive of magmatic contributions. At the failed rift, within the continental domain, hyperextended crust is modelled, overlying a limited zone of serpentinized mantle. Seaward of Orphan Knoll, the interpretation for the velocity structure is less definitive but an 80-km-wide continent–ocean transition zone consisting of either transitional embryonic oceanic crust or thinned continental crust overlying serpentinized mantle is proposed. Upper mantle velocities as low as 7.7 km s–1 are modelled beneath the interpreted failed continental rift as well as beneath the continent–ocean transition zone, while the rest of the crustal model is underlain by typical mantle velocities of 8 km s–1. Analysis of extension and thinning factors based on the velocity model reveal that the failed rift experienced hyperextension and should have achieved full crustal embrittlement, consistent with localized mantle serpentinization.

Description: Rayleigh-wave dispersion curves from both ambient noise and teleseismic events allow us to provide the first high-resolution 3-D shear wave velocity (VS) model of the crust and upper mantle below the Sardinia–Corsica microplate, an important continental block for understanding the evolution of the central-western Mediterranean. For a wide range of periods (from 3 to ∼30 s), the phase velocities of the study area are systematically higher than those measured within the Italian peninsula, in agreement with a colder geotherm. Relative and absolute variations in the VS allow us to detect a very heterogeneous upper crust down to 8 km, as opposed to a relatively homogeneous middle and lower crust. The isosurface at 4.1 km s−1 is consistent with a rather flat Moho at a depth of 28.0 ± 1.8 km (2σ). The lithospheric mantle is relatively cold, and we constrain the thermal lithosphere–asthenosphere boundary at ∼100 km. We find our estimate consistent with a continental geotherm based on a surface heat flow of 60 mW m−2. Our results suggest that most of the lithosphere endured the complex history of deformation experienced by the study area and imply, in general, that deep tectonic processes do not easily destabilize the deeper portion of the continental lithosphere, despite leaving a clear surface signature.

Description: SUMMARY We present 2-D numerical simulations of convergence at a hyperextended passive margin with exhumed subcontinental mantle. We consider viscoelasto-plastic deformation, heat transfer and thermomechanical coupling by shear heating and associated thermal softening due to temperature dependent viscosity. The simulations show subduction initiation for convergence velocities of 2 cm yr−1, initial Moho temperatures of 525 °C and maximal deviatoric stresses of ca. 800 MPa, around the Moho, prior to localization. Subduction initiates in the region with thinned continental crust and is controlled by a thermally activated ductile shear zone in the mantle lithosphere. The shear zone temperature can be predicted with a recently published analytical expression. The criterion for subduction initiation is a temperature difference of at least 225 °C between predicted temperature and initial Moho temperature. The modelled forced subduction broadly agrees with geological data and reconstructions of subduction during closure of the Piemont-Liguria basin, caused by convergence of the European and Adriatic plates during the Alpine orogeny.

Description: Seismic reflection images of mass-transport deposits often show apparently chaotic, disorded or low-reflectivity internal seismic facies. The lack of laterally coherent reflections can prevent horizon-based interpretation of internal structure. This study instead inverts for geostatistical parameters which characterize the internal heterogeneity of mass-transport deposits from depth-domain seismic reflection images. A Bayesian Markov Chain Monte Carlo inversion is performed to estimate posterior probability distributions for each geostatistical parameter. If the internal heterogeneity approximates an anisotropic von Kármán random medium these parameters can describe the structural fabric of the imaged mass-transport deposit in terms of lateral and vertical dominant scale lengths and the Hurst number (roughness). To improve the discrimination between vertical and lateral dominant scale lengths an estimate of the vertical dominant scale length from a borehole is used as a prior in the inversion. The method is first demonstrated on a synthetic multichannel seismic reflection image. The vertical and lateral dominant scale lengths are estimated with lower uncertainty when data from a synthetic borehole data are included. We then apply the method to a real data example from Nankai Trough, offshore Japan, where a large mass-transport deposit is imaged in a seismic profile and penetrated by a borehole. The results of the inversion show a downslope shortening in lateral scale length, consistent with progressive down-slope disaggregation of the mass-flow during transport. The dominant scale lengths can be used as a proxy for strain history, which can improve understanding of post-failure dynamics and emplacement of subacqueous mass-movements, important for constraining the geohazard potential from future slope failure.

Description: Traditionally, reservoir elastic parameters inversion suffers from the overburden multiple scattering and transmission imprint in the local input data used for the target-oriented inversion. In this paper, we present a full-wavefield approach, called reservoir-oriented joint migration inversion (JMI-res), to estimate the high-resolution reservoir elastic parameters from surface seismic data. As a first step in JMI-res, we reconstruct the fully redatumed data (local impulse responses) at a suitable depth above the reservoir from the surface seismic data, while correctly accounting for the overburden interal multiples and transmission losses. Next, we apply a localized elastic full waveform inversion on the estimated impulse responses to get the elastic parameters. We show that JMI-res thus provides much more reliable local target impulse responses, thus yielding high-resolution elastic parameters, compared to a standard redatuming procedure based on time reversal of data. Moreover, by using this kind of approach we avoid the need to apply a full elastic full waveform inversion-type process for the whole subsurface, as within JMI-res elastic full waveform inversion is only restricted to the reservoir target domain.

Description: Acoustic emission (AE) is a widely used technology to study source mechanisms and material properties during high-pressure rock failure experiments. It is important to understand the physical quantities that acoustic emission sensors measure, as well as the response of these sensors as a function of frequency. This study calibrates the newly built AE system in the MIT Rock Physics Laboratory using a ball-bouncing system. Full waveforms of multibounce events due to ball drops are used to infer the transfer function of lead zirconate titanate (PZT) sensors in high pressure environments. Uncertainty in the sensor transfer functions is quantified using a waveform-based Bayesian approach. The quantification of in situ sensor transfer functions makes it possible to apply full waveform analysis for acoustic emissions at high pressures.

Description: The potential of full-waveform inversion (FWI) to recover high-resolution velocity models of the subsurface has been demonstrated in the last decades with its application to field data. But in certain geological scenarios, conventional FWI using the acoustic wave equation fails in recovering accurate models due to the presence of strong elastic effects, as the acoustic wave equation only accounts for compressional waves. This becomes more critical when dealing with land data sets, in which elastic effects are generated at the source and recorded directly by the receivers. In marine settings, in which sources and receivers are typically within the water layer, elastic effects are weaker but can be observed most easily as double mode conversions and through their effect on P-wave amplitudes. Ignoring these elastic effects can have a detrimental impact on the accuracy of the recovered velocity models, even in marine data sets. Ideally, the elastic wave equation should be used to model wave propagation, and FWI should aim to recover anisotropic models of velocity for P waves (vp) and S waves (vs). However, routine three-dimensional elastic FWI is still commercially impractical due to the elevated computational cost of modelling elastic wave propagation in regions with low S-wave velocity near the seabed. Moreover, elastic FWI using local optimization methods suffers from cross-talk between different inverted parameters. This generally leads to incorrect estimation of subsurface models, requiring an estimate of vp/vs that is rarely known beforehand. Here we illustrate how neglecting elasticity during FWI for a marine field data set that contains especially strong elastic heterogeneities can lead to an incorrect estimation of the P-wave velocity model. We then demonstrate a practical approach to mitigate elastic effects in 3-D yielding improved estimates, consisting of using a global inversion algorithm to estimate a model of vp/vs, employing matching filters to remove elastic effects from the field data, and performing acoustic FWI of the resulting data set. The quality of the recovered models is assessed by exploring the continuity of the events in the migrated sections and the fit of the latter with the recovered velocity model.