Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userReconstructing eruptive source parameters from tephra deposit: a numerical approach for medium-sized explosive eruptions
87
0
0.0
(
0
)
Authors
A. Spanu
Ask ChatGPT about the research
No Arabic abstract
Since the seventies, several reconstruction techniques have been proposed, and are currently used, to extrapolate and quantify eruptive parameters from sampled deposit datasets. Discrete numbers of tephra ground loadings or stratigraphic records are usually processed to estimate source eruptive values. Reconstruction techniques like Pyle, Power law and Weibull are adopted as standard to quantify the erupted mass (or volume) whereas Voronoi for reconstructing the granulometry. Reconstructed values can be affected by large uncertainty due to complexities occurring within the atmospheric dispersion and deposition of volcanic particles. Here we want to quantify the sensitivity of reconstruction techniques, and to quantify how much estimated values of mass and grain size differ from emitted and deposited ones. We adopted a numerical approach simulating with a dispersal code a mild explosive event occurring at Mt. Etna, with eruptive parameters similar to those estimated for eruptions occurred in the last decade. Then we created a synthetic deposit by integrating the mass on the ground computed by the model over the computational domain (>50000 km2). Multiple samplings of the simulated deposit are used for generating a large dataset of sampling tests afterwards processed with standard reconstruction techniques. Results are then compared and evaluated through a statistical analysis, based on 2000 sampling tests of 100 samplings points. On average, all the used techniques underestimate deposited and emitted mass. A similar analysis, carried on Voronoi results, shows that information on the total grain size distribution is strongly deteriorated. Here we present a new method allowing an estimate of the deficiency in deposited mass for each simulated class. Finally a sensitivity study on eruptive parameters is presented in order to generalize our results to a wider range of eruptive conditions.
rate research
Read More
The Finite Difference (FD) and the Spectral Boundary Integral (SBI) methods have been used extensively to model spontaneously propagating shear cracks in a variety of engineering and geophysical applications. In this paper, we propose a new modeling approach, in which these two methods are combined through consistent exchange of boundary tractions and displacements. Benefiting from the flexibility of FD and the efficiency of spectral boundary integral (SBI) methods, the proposed hybrid scheme will solve a wide range of problems in a computationally efficient way. We demonstrate the validity of the approach using two examples for dynamic rupture propagation: one in the presence of a low velocity layer and the other in which off-fault plasticity is permitted. We discuss possible potential uses of the hybrid scheme in earthquake cycle simulations as well as an exact absorbing boundary condition
The three-dimensional (3D) geological models are the typical and key data source in the 3D mineral prospecitivity modeling. Identifying prospectivity-informative predictor variables from the 3D geological models is a challenging and tedious task. Motivated by the ability of convolutional neural networks (CNNs) to learn the intrinsic features, in this paper, we present a novel method that leverages CNNs to learn 3D mineral prospectivity from the 3D geological models. By exploiting the learning ability of CNNs, the presented method allows for disentangling complex correlation to the mineralization and thus opens a door to circumvent the tedious work for designing the predictor variables. Specifically, to explore the unstructured 3D geological models with the CNNs whose input should be structured, we develop a 2D CNN framework in which the geometry of geological boundary is compiled and reorganized into multi-channel images and fed into the CNN. This ensures an effective and efficient training of CNNs while allowing the prospective model to approximate the ore-forming process. The presented method is applied to a typical structure-controlled hydrothermal deposit, the Dayingezhuang gold deposit, eastern China, in which the presented method was compared with the prospectivity modeling methods using hand-designed predictor variables. The results demonstrate the presented method capacitates a performance boost of the 3D prospectivity modeling and empowers us to decrease work-load and prospecting risk in prediction of deep-seated orebodies.
We consider a long-wave transversely isotropic (TI) medium equivalent to a series of finely parallel-layered isotropic layers, obtained using the citet{Backus} average. In such a TI equivalent medium, we verify the citet{Berrymanetal} method of indicating fluids and the authors method citep{Adamus}, using anisotropy parameter $varphi$. Both methods are based on detecting variations of the Lame parameter, $lambda$, in a series of thin isotropic layers, and we treat these variations as potential change of the fluid content. To verify these methods, we use Monte Carlo (MC) simulations; for certain range of Lame parameters $lambda$ and $mu$---relevant to particular type of rocks---we generate numerous combinations of these parameters in thin layers and, after the averaging process, we obtain their TI media counterparts. Subsequently, for each of the aforementioned media, we compute $varphi$ and citet{Thomsen} parameters $epsilon$ and $delta$. We exhibit $varphi$, $epsilon$ and $delta$ in a form of cross-plots and distributions that are relevant to chosen range of $lambda$ and $mu$. We repeat that process for various ranges of Lame parameters. Additionally, to support the MC simulations, we consider several numerical examples of growing $lambda$, by using scale factors. As a result of the thorough analysis of the relations among $varphi$, $epsilon$ and $delta$, we find eleven fluid detectors that compose a new fluid detection method. Based on these detectors, we show the quantified pattern of indicating change of the fluid content.
In this work we consider the inverse problem of reconstructing the optical properties of a layered medium from an elastography measurement where optical coherence tomography is used as the imaging method. We hereby model the sample as a linear dielectric medium so that the imaging parameter is given by its electric susceptibility, which is a frequency- and depth-dependent parameter. Additionally to the layered structure (assumed to be valid at least in the small illuminated region), we allow for small scatterers which we consider to be randomly distributed, a situation which seems more realistic compared to purely homogeneous layers. We then show that a unique reconstruction of the susceptibility of the medium (after averaging over the small scatterers) can be achieved from optical coherence tomography measurements for different compression states of the medium.
In this paper, we consider a long-wave equivalent medium to a finely parallel-layered inhomogeneous medium, obtained using the Backus average. Following the work of Postma and Backus, we show explicitly the derivations of the conditions to obtain the equivalent isotropic medium. We demonstrate that there cannot exist a transversely isotropic (TI) equivalent medium with the coefficients $c^{overline{rm TI}}_{1212} eq c^{overline{rm TI}}_{2323}$, $c^{overline{rm TI}}_{1111} = c^{overline{rm TI}}_{3333}$ and $c^{overline{rm TI}}_{1122} = c^{overline{rm TI}}_{1133}$. Moreover, we consider a new parameter, $varphi$, indicating the anisotropy of the equivalent medium, and we show its range and properties. Subsequently, we compare $varphi$ to the Thomsen parameters, emphasizing its usefulness as a supportive parameter showing the anisotropy of the equivalent medium or as an alternative parameter to $delta$. We argue with certain Berryman et al. considerations regarding the properties of the anisotropy parameters $epsilon$ and $delta$. Additionally, we show an alternative way---to the one mentioned by Berryman et al.---of indicating changing fluid content in layered Earth.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
