Fingerprinting stress: stylolite and calcite twinning paleopiezometry revealing the complexity of progressive stress patterns during folding-the case of the Monte Nero anticline in the Apennines, Italy

In this study we show for the first time how quantitative stress estimates can be derived by combining calcite twinning and stylolite roughness stress fingerprinting techniques in a fold-and-thrust belt. First, we present a new method that gives access to stress inversion using tectonic stylolites without access to the stylolite surface and compare results with calcite twin inversion. Second, we use our new approach to present a high-resolution deformation and stress history that affected Meso-Cenozoic limestone strata in the Monte Nero Anticline during its late Miocene-Pliocene growth in the Umbria-Marche Arcuate Ridge (northern Apennines, Italy). In this area an extensive stylolite-joint/vein network developed during layer-parallel shortening (LPS), as well as during and after folding. Stress fingerprinting illustrates how stress in the sedimentary strata did build up prior to folding during LPS. The stress regime oscillated between strike slip and compressional during LPS before ultimately becoming strike slip again during late stage fold tightening. Our case study shows that high-resolution stress fingerprinting is possible and that this novel method can be used to unravel temporal relationships that relate to local variations of regional orogenic stresses. Beyond regional implications, this study validates our approach as a new powerful toolbox to high-resolution stress fingerprinting in basins and orogens combining joint and vein analysis with sedimentary and tectonic stylolite and calcite twin inversion techniques

On the use of machine learning algorithms in the measurement of stellar magnetic fields

Regression methods based in Machine Learning Algorithms (MLA) have become an important tool for data analysis in many different disciplines. In this work, we use MLA in an astrophysical context; our goal is to measure the mean longitudinal magnetic field in stars (H_ eff) from polarized spectra of high resolution, through the inversion of the so-called multi-line profiles. Using synthetic data, we tested the performance of our technique considering different noise levels: In an ideal scenario of noise-free multi-line profiles, the inversion results are excellent; however, the accuracy of the inversions diminish considerably when noise is taken into account. In consequence, we propose a data pre-process in order to reduce the noise impact, which consists in a denoising profile process combined with an iterative inversion methodology. Applying this data pre-process, we have found a considerable improvement of the inversions results, allowing to estimate the errors associated to the measurements of stellar magnetic fields at different noise levels. We have successfully applied our data analysis technique to two different stars, attaining by first time the measurement of H_eff from multi-line profiles beyond the condition of line autosimilarity assumed by other techniques.Comment: Accepted for publication in A&

AMPLITUDE-VERSUS-ANGLE ANALYSIS AND WIDE-ANGLE-INVERSION OF CROSSWELL SEISMIC DATA IN A CARBONATE RESERVOIR

Crosswell data set contains a range of angles limited only by the geometry of the source and receiver configuration, the separation of the boreholes and the depth to the target. However, the wide angles reflections present in crosswell imaging result in amplitude-versus-angle (AVA) features not usually observed in surface data. These features include reflections from angles that are near critical and beyond critical for many of the interfaces; some of these reflections are visible only for a small range of angles, presumably near their critical angle. High-resolution crosswell seismic surveys were conducted over a Silurian (Niagaran) reef at two fields in northern Michigan, Springdale and Coldspring. The Springdale wells extended to much greater depths than the reef, and imaging was conducted from above and from beneath the reef. Combining the results from images obtained from above with those from beneath provides additional information, by exhibiting ranges of angles that are different for the two images, especially for reflectors at shallow depths, and second, by providing additional constraints on the solutions for Zoeppritz equations. Inversion of seismic data for impedance has become a standard part of the workflow for quantitative reservoir characterization. Inversion of crosswell data using either deterministic or geostatistical methods can lead to poor results with phase change beyond the critical angle, however, the simultaneous pre-stack inversion of partial angle stacks may be best conducted with restrictions to angles less than critical. Deterministic inversion is designed to yield only a single model of elastic properties (best-fit), while the geostatistical inversion produces multiple models (realizations) of elastic properties, lithology and reservoir properties. Geostatistical inversion produces results with far more detail than deterministic inversion. The magnitude of difference in details between both types of inversion becomes increasingly pronounced for thinner reservoirs, particularly those beyond the vertical resolution of the seismic. For any interface imaged from above and from beneath, the results AVA characters must result from identical contrasts in elastic properties in the two sets of images, albeit in reverse order. An inversion approach to handle both datasets simultaneously, at pre-critical angles, is demonstrated in this work. The main exploration problem for carbonate reefs is determining the porosity distribution. Images of elastic properties, obtained from deterministic and geostatistical simultaneous inversion of a high-resolution crosswell seismic survey were used to obtain the internal structure and reservoir properties (porosity) of Niagaran Michigan reef. The images obtained are the best of any Niagaran pinnacle reef to date

High resolution image reconstruction with constrained, total-variation minimization

This work is concerned with applying iterative image reconstruction, based on constrained total-variation minimization, to low-intensity X-ray CT systems that have a high sampling rate. Such systems pose a challenge for iterative image reconstruction, because a very fine image grid is needed to realize the resolution inherent in such scanners. These image arrays lead to under-determined imaging models whose inversion is unstable and can result in undesirable artifacts and noise patterns. There are many possibilities to stabilize the imaging model, and this work proposes a method which may have an advantage in terms of algorithm efficiency. The proposed method introduces additional constraints in the optimization problem; these constraints set to zero high spatial frequency components which are beyond the sensing capability of the detector. The method is demonstrated with an actual CT data set and compared with another method based on projection up-sampling.Comment: This manuscript appears in the proceedings of the 2010 IEEE medical imaging conferenc

Spatially coupled inversion of spectro-polarimetric image data I: Method and first results

When inverting solar spectra, image degradation effects that are present in the data are usually approximated or not considered. We develop a data reduction method that takes these issues into account and minimizes the resulting errors. By accounting for the diffraction PSF of the telescope during the inversions, we can produce a self-consistent solution that best fits the observed data, while simultaneously requiring fewer free parameters than conventional approaches. Simulations using realistic MHD data indicate that the method is stable for all resolutions, including those with pixel scales well beyond those that can be resolved with a 0.5m telescope, such as the Hinode SOT. Application of the presented method to reduce full Stokes data from the Hinode spectro-polarimeter results in dramatically increased image contrast and an increase in the resolution of the data to the diffraction limit of the telescope in almost all Stokes and fit parameters. The resulting data allow for detecting and interpreting solar features that have so far only been observed with 1m class ground-based telescopes. The new inversion method allows for accurate fitting of solar spectro-polarimetric imaging data over a large field of view, while simultaneously improving the noise statistics and spatial resolution of the results significantly.Comment: A&A, accepte

Reconstruction of quasi-local numerical effective models from low-resolution measurements

We consider the inverse problem of reconstructing an effective model for a prototypical diffusion process in strongly heterogeneous media based on low-resolution measurements. We rely on recent quasi-local numerical effective models that, in contrast to conventional homogenized models, are provably reliable beyond periodicity assumptions and scale separation. The goal of this work is to show that the identification of the matrix representation of these effective models is possible. Algorithmic aspects of the inversion procedure and its performance are illustrated in a series of numerical experiments