A Bayesian framework for fracture characterization from surface seismic data

We describe a methodology for quantitatively characterizing the fractured nature of a hydrocarbon or geothermal reservoir from surface seismic data under a Bayesian inference framework. Fractures provide pathways for fluid flow in a reservoir, and hence, knowledge about a reservoir’s fractured nature can be used to enhance production of the reservoir. The fracture properties of interest in this study (to be inferred) are fracture orientation and excess compliance, where each of these properties are assumed to vary spatially over a 2D lateral grid which is assumed to represent the top of a reservoir. The Bayesian framework in which the inference problem is cast has the key benefits of (1) utilization of a prior model that allows geological information to be incorporated, (2) providing a straightforward means of incorporating all measurements (across the 2D spatial grid) into the estimates at each grid point, (3) allowing different types of measurements to be combined under a single inference procedure, and (4) providing a measure of uncertainty in the estimates. The observed data are taken from a 2D array of surface seismic receivers responding to an array of surface sources. Well understood features from the seismic traces are extracted and treated as the observed data, namely the P-wave reflection amplitude variation with acquisition azimuth (amplitude versus azimuth, or AvAz, data) and fracture transfer function (FTF) data. AvAz data are known to be more sensitive to fracture properties when the fracture spacing is significantly smaller than the seismic wavelength, whereas fracture transfer function data are more sensitive to fracture properties when the fracture spacing is on the order of the seismic wavelength. Combining these two measurements has the benefit of allowing inferences to be made about fracture properties over a larger range of fracture spacing than otherwise attainable. Geophysical forward models for the measurements are used to arrive at likelihood models for the data. The prior distribution for the hidden fracture variables is obtained by defining a Markov random field (MRF) over the lateral 2D grid where we wish to obtain fracture properties. The fracture variables are then inferred by application of loopy belief propagation (LBP) to yield approximations for the posterior marginal distributions of the fracture properties, as well as the maximum a posteriori (MAP) and Bayes least squares (BLS) estimates of these properties. Verification of the inference procedure is performed on a synthetic dataset, where the estimates obtained are shown to be at or near ground truth for a large range of fracture spacings

Regularizing velocity differences in time-lapse FWI using gradient mismatch information

We present a method for recovering time-lapse velocity changes using full waveform inversion (FWI). In a preprocessing step we invert for a single intermediate model by simultaneously minimizing the data misfit in the baseline and the monitor surveys. We record the individual FWI gradients corresponding to the baseline and the monitor datasets at each iteration of the inversion. Regions where these gradients consistently have opposing sign are likely to correspond to locations of time-lapse change. This insight is used to generate a spatially varying confidence map for time-lapse change. In a subsequent joint inversion we invert for baseline and monitor models while regularizing the difference between the models with this spatially varying confidence map. Unlike double difference full waveform inversion (DDFWI) we do not require identical source and receiver positions in the baseline and monitor surveys

Hemiculter leucisculus (Basilewsky, 1855) and Alburnus caeruleus Heckel, 1843: New data on their distributions in Iran

This paper provides information on the geographic distributions of two cyprinid species: Hemiculter leucisculus (Basilewsky, 1855) and Alburnus caeruleus Heckel, 1843, in the world and the entire drainage systems in Iran. The new distribution records were taken from Maroon River (Jarrahi River system) and Chardaval River (Karkheh river system), both in Tigris River basin showing wide and narrow distribution ranges of these two cyprinid fishes, respectively. The main introduction sites and distribution range of H. leucisculus is the southern parts of the Caspian Sea basin in Iran from where it has probably been translocated to other Iranian basins along with exotic Chinese carps. Although A. caeruleus is native to Tigris River basin, it had been already recorded only from Gamasiab and Doab rivers in 2009 in Karkheh River system (Tigris) and thus the present study extends its distribution range. In case of alien species, human-mediated fish introductions may increase faunal similarity among primary drainages due to a strong tendency for taxonomic homogenization caused primarily by the widespread introduction of cyprinid fishes. Fish faunal homogenization might be highest in drainages (e.g. Caspian Sea and Tigris basins) subjected to the greatest degree of disturbance associated with human settlement, infrastructure and change in land use. The provided data might be used in conservation program of freshwater fishes of Iran

Attacking Massive MIMO Cognitive Radio Networks by Optimized Jamming

Massive multiple-input multiple-output (MaMIMO) and cognitive radio networks (CRNs) are two promising technologies for improving spectral efficiency of next-generation wireless communication networks. In this paper, we investigate the problem of physical layer security in the networks that jointly use both technologies, named MaMIMO-CRN. Specifically, to investigate the vulnerability of this network, we design an optimized attacking scenario to MaMIMO-CRNs by a jammer. For having the most adversary effect on the uplink transmission of the legitimate MaMIMO-CRN, we propose an efficient method for power allocation of the jammer. The legitimate network consists of a training and a data transmission phase, and both of these phases are attacked by the jammer using an optimized power split between them. The resulting power allocation problem is non-convex. We thus propose three different efficient methods for solving this problem, and we show that under some assumptions, a closed-form solution can also be obtained. Our results show the vulnerability of the MaMIMO-CRN to an optimized jammer. It is also shown that increasing the number of antennas at the legitimate network does not improve the security of the network

Simultaneous Estimation of Reflectivity and Geologic Texture: Least-Squares Migration with a Hierarchical Bayesian Model

In many geophysical inverse problems, smoothness assumptions on the underlying geology are utilized to mitigate the effects of poor resolution and noise in the data and to improve the quality of the inferred model parameters. Within a Bayesian inference framework, a priori assumptions about the probabilistic structure of the model parameters impose such a smoothness constraint or regularization. We consider the particular problem of inverting seismic data for the subsurface reflectivity of a 2-D medium, where we assume a known velocity field. In particular, we consider a hierarchical Bayesian generalization of the Kirchhoff-based least-squares migration (LSM) problem. We present here a novel methodology for estimation of both the optimal image and regularization parameters in a least-squares migration setting. To do so we utilize a Bayesian statistical framework that treats both the regularization parameters and image parameters as random variables to be inferred from the data. Hence rather than fixing the regularization parameters prior to inverting for the image, we allow the data to dictate where to regularize. In order to construct our prior model of the subsurface and regularization parameters, we define an undirected graphical model (or Markov random field) where vertices represent reflectivity values, and edges between vertices model the degree of correlation (or lack thereof) between the vertices. Estimating optimal values for the vertex parameters gives us an image of the subsurface reflectivity, while estimating optimal edge strengths gives us information about the local “texture” of the image, which, in turn, may tell us something about the underlying geology. Subsequently incorporating this information in the final model produces more clearly visible discontinuities in the final image. The inference framework is verified on a 2-D synthetic dataset, where the hierarchical Bayesian imaging results significantly outperform standard LSM images.Shell International Exploration and Production B.V.; Massachusetts Institute of Technology. Earth Resources Laboratory (Founding Members Consortium

Iterative estimation of reflectivity and image texture: Least-squares migration with an empirical Bayes approach

In many geophysical inverse problems, smoothness assumptions on the underlying geology are used to mitigate the effects of nonuniqueness, poor data coverage, and noise in the data and to improve the quality of the inferred model parameters. Within a Bayesian inference framework, a priori assumptions about the probabilistic structure of the model parameters can impose such a smoothness constraint, analogous to regularization in a deterministic inverse problem. We have considered an empirical Bayes generalization of the Kirchhoff-based least-squares migration (LSM) problem. We have developed a novel methodology for estimation of the reflectivity model and regularization parameters, using a Bayesian statistical framework that treats both of these as random variables to be inferred from the data. Hence, rather than fixing the regularization parameters prior to inverting for the image, we allow the data to dictate where to regularize. Estimating these regularization parameters gives us information about the degree of conditional correlation (or lack thereof) between neighboring image parameters, and, subsequently, incorporating this information in the final model produces more clearly visible discontinuities in the estimated image. The inference framework is verified on 2D synthetic data sets, in which the empirical Bayes imaging results significantly outperform standard LSM images. We note that although we evaluated this method within the context of seismic imaging, it is in fact a general methodology that can be applied to any linear inverse problem in which there are spatially varying correlations in the model parameter space.MIT Energy Initiative (Shell International Exploration and Production B.V.)ERL Founding Member Consortiu

Genesis and soil environmental implications of intact in-situ rhizoliths in dunes of the Badain Jaran Desert, northwestern China

Desert rhizoliths are generally found as weathered, broken and scattered samples on dune field surface, but rarely in-situ in their initial states buried under the soil of desert in the Badain Jaran Desert, northwest China. This study offers an assessment of the morphological, mineralogical, and chemical properties of intact and in-situ rhizoliths found in soils of swales and depressions among dune chains. The characteristics of these rare and precious objects were assessed using optical polarizing microscopy, cathodoluminescence, scanning electronic microscopy, radiocarbon dating, and stable isotopic analyses, providing the opportunity for discussion of the rhizolith formation mechanisms and associated environmental conditions. Field and laboratory investigations showed that the in-situ intact rhizoliths were formed only in the places where Artemisia shrubs are living, and the remaining root relicts within rhizoliths belong to this species. The spatial distribution of rhizoliths also suggested that low topographic positions on a landscape provided soil moisture, and redox environments favored rhizolith formation. A semi-closed redox environment in the subsoil at swales and depressions, where water is always present, along with the sandy soil texture, facilitated fast water percolation to deeper depths and condensation. Such a soil environment not only provides water for Artemisia growth, but also for the weathering of minerals such as felspars and calcite from primary carbonates, and for the decomposition of root relicts. Furthermore, harsh climatic conditions, such as strong winds and solar radiation, led to water evaporation through dead root channels and triggered the calcification along the root relicts. The entrapped lithogenic carbonates and to a lesser extent the decomposition of Artemisia roots provided the carbon sources for the rhizoliths formation, while the weathering of soil minerals, particularly feldspars and carbonates, was the main source of Ca. Rhizoliths in the Badain Jaran desert formed relatively quickly, probably over a few soil drying episodes. This led to the entrapment of a large quantity of lithogenic carbonates (more than 90% of carbon) within rhizolith cement. The re-dissolution of the entrapped lithogenic carbonates in rhizolith tubes should be taken into account in the paleoenvironmental interpretation of 14C ages, the latter suggesting that rhizoliths formed during the Holocene (~ 2053 years cal BP, based on root organic relicts). © 2022, The Author(s)

Genesis and soil environmental implications of intact in-situ rhizoliths in dunes of the Badain Jaran Desert, northwestern China

Desert rhizoliths are generally found as weathered, broken and scattered samples on dune field surface, but rarely in-situ in their initial states buried under the soil of desert in the Badain Jaran Desert, northwest China. This study offers an assessment of the morphological, mineralogical, and chemical properties of intact and in-situ rhizoliths found in soils of swales and depressions among dune chains. The characteristics of these rare and precious objects were assessed using optical polarizing microscopy, cathodoluminescence, scanning electronic microscopy, radiocarbon dating, and stable isotopic analyses, providing the opportunity for discussion of the rhizolith formation mechanisms and associated environmental conditions. Field and laboratory investigations showed that the in-situ intact rhizoliths were formed only in the places where Artemisia shrubs are living, and the remaining root relicts within rhizoliths belong to this species. The spatial distribution of rhizoliths also suggested that low topographic positions on a landscape provided soil moisture, and redox environments favored rhizolith formation. A semi-closed redox environment in the subsoil at swales and depressions, where water is always present, along with the sandy soil texture, facilitated fast water percolation to deeper depths and condensation. Such a soil environment not only provides water for Artemisia growth, but also for the weathering of minerals such as felspars and calcite from primary carbonates, and for the decomposition of root relicts. Furthermore, harsh climatic conditions, such as strong winds and solar radiation, led to water evaporation through dead root channels and triggered the calcification along the root relicts. The entrapped lithogenic carbonates and to a lesser extent the decomposition of Artemisia roots provided the carbon sources for the rhizoliths formation, while the weathering of soil minerals, particularly feldspars and carbonates, was the main source of Ca. Rhizoliths in the Badain Jaran desert formed relatively quickly, probably over a few soil drying episodes. This led to the entrapment of a large quantity of lithogenic carbonates (more than 90% of carbon) within rhizolith cement. The re-dissolution of the entrapped lithogenic carbonates in rhizolith tubes should be taken into account in the paleoenvironmental interpretation of 14C ages, the latter suggesting that rhizoliths formed during the Holocene (~ 2053 years cal BP, based on root organic relicts)

Spin and magnetization effects in plasmas

We give a short review of a number of different models for treating magnetization effects in plasmas. In particular, the transition between kinetic models and fluid models is discussed. We also give examples of applications of such theories. Some future aspects are discussed.Comment: 18 pages, 1 figure. To appear in Plasma Physics and Controlled Fusion, Special Issue for the 37th ICPP, Santiago, Chil

From extended phase space dynamics to fluid theory

We derive a fluid theory for spin-1/2 particles starting from an extended kinetic model based on a spin-projected density matrix formalism. The evolution equation for the spin density is found to contain a pressure-like term. We give an example where this term is important by looking at a linear mode previously found in a spin kinetic model.Comment: 4 page