搜索结果：Geology

Reconstructing the structural geology and mineral composition of the first few kilometers of the Earth's subsurface from sparse or indirect surface observations remains a long-standing challenge with critical applications in mineral exploration, geohazard assessment, and geotechnical engineering. This inherently ill-posed problem is often addressed by classical geophysical inversion methods, which typically yield a single maximum-likelihood model that fails to capture the full range of plausible geology. The adoption of modern deep learning methods has been limited by the lack of large 3D training datasets. We address this gap with \textit{StructuralGeo}, a geological simulation engine that mimics eons of tectonic, magmatic, and sedimentary processes to generate a virtually limitless supply of realistic synthetic 3D lithological models. Using this dataset, we train both unconditional and conditional generative flow-matching models with a 3D attention U-Net architecture. The resulting foundation model can reconstruct multiple plausible 3D scenarios from surface topography and sparse borehole data, depicting structures such as layers, faults, folds, and dikes. By sampling many recons

Tunnel boring machine (TBM) is a complex engineering system widely used for tunnel construction. In view of the complicated construction environments, it is necessary to predict geology conditions prior to excavation. In recent years, massive operation data of TBM has been recorded, and mining these data can provide important references and useful information for designers and operators of TBM. In this work, a geology prediction approach is proposed based on deep neural network and operation data. It can provide relatively accurate geology prediction results ahead of the tunnel face compared with the other prediction models based on statistical learning methods. The application case study on a tunnel in China shows that the proposed approach can accurately estimate the geological conditions prior to excavation, especially for the short range ahead of training data. This work can be regarded as a good complement to the geophysical prospecting approach during the construction of tunnels, and also highlights the applicability and potential of deep neural networks for other data mining tasks of TBMs.

Nearly 30 years after the discovery of the first exoplanet around a main sequence star, thousands of planets have now been confirmed. These discoveries have completely revolutionized our understanding of planetary systems, revealing types of planets that do not exist in our solar system but are common in extrasolar systems, and a wide range of system architectures. Our solar system is clearly not the default for planetary systems. The community is now moving beyond basic characterization of exoplanets (mass, radius, and orbits) towards a deeper characterization of their atmospheres and even surfaces. With improved observational capabilities there is potential to now probe the geology of rocky exoplanets; this raises the possibility of an analogous revolution in our understanding of rocky planet evolution. However, characterizing the geology or geological processes occurring on rocky exoplanets is a major challenge, even with next generation telescopes. This chapter reviews what we may be able to accomplish with these efforts in the near-term and long-term. In the near-term, the James Webb Space Telescope (JWST) is revealing which rocky planets lose versus retain their atmospheres.

An important problem in geostatistics is to build models of the subsurface of the Earth given physical measurements at sparse spatial locations. Typically, this is done using spatial interpolation methods or by reproducing patterns from a reference image. However, these algorithms fail to produce realistic patterns and do not exhibit the wide range of uncertainty inherent in the prediction of geology. In this paper, we show how semantic inpainting with Generative Adversarial Networks can be used to generate varied realizations of geology which honor physical measurements while matching the expected geological patterns. In contrast to other algorithms, our method scales well with the number of data points and mimics a distribution of patterns as opposed to a single pattern or image. The generated conditional samples are state of the art.

This thesis consists of two parts: the construction of a jointly universal family of graphs, and then an exploration of set-theoretic geology. Firstly we shall construct a model in which $2^{\aleph_{ω_1}}=2^{\aleph_{ω_1+1}}=\aleph_{ω_1+3}$ but there is a jointly universal family of size $\aleph_{ω_1+2}$ of graphs on $\aleph_{ω_1+1}$. We take a supercompact cardinal $κ$ and will use Radin forcing with interleaved collapses to change $κ$ into $\aleph_{ω_1}$. Prior to the Radin forcing we perform a preparatory iteration to add functions from $κ^+$ into Radin names for what will become members of the jointly universal family on $κ^+$. The same technique can be used with any uncountable cardinal in place of $ω_1$. Secondly we explore various topics in set-theoretic geology. We begin by showing that a class Easton support iteration of $\mathrm{Add}(κ,1)$ at $κ$ regular results in a universe that is its own generic mantle. We then consider set forcings $\mathbb{P}$, $\mathbb{Q}$, $\mathbb{R}$ and $\mathbb{S}$ with respective generics $G$, $H$, $I$ and $J$ such that $V[G][I]=V[H][J]$ and show that $V[G]$ and $V[H]$ must have a shared ground via $(|\mathbb{R}|+|\mathbb{S}|)^+$-cc forcing. T

Let us say that a model of $\mathsf{ZF}$ is a symmetric ground if $V$ is a symmetric extension of the model. In this paper, we investigate set-theoretic geology of symmetric grounds. Under a certain assumption, we show that all symmetric grounds of $V$ are uniformly definable. We also show that if $\mathsf{AC}$ is forceable over $V$, then the symmetric grounds are downward directed.

Low oil prices have motivated energy executives to look into cost reduction in their supply chains more seriously. To this end, a new technology that is experimentally considered in hydrocarbon exploration is data mining. There are two major categories of geoscientific problems in which data mining is applied: structural geology and reservoir property-issues. This research overviews these categories by considering a variety of interesting works in each of them. The result is an understanding of the specific geoscientific problems studied in the literature, along with the relative data mining methods. This way, this work tries to lay the ground for a mutual understanding on oil and gas exploration between the data miners and the geoscientists.

This thesis presents insights into the surface compositional heterogeneity and geology of asteroid Vesta. Lithologic mapping using Framing Camera onboard the NASA Dawn spacecraft revealed that the majority of the surface is howarditic in composition (Thangjam et al. 2013). An important outcome of this thesis is identification of olivine-rich exposures for the first time using FC color data (Thangjam et al., 2014). Another significant contribution from this thesis is an innovative three-dimensional approach of spectral analysis that could be used to study surface compositional heterogeneity of Vesta (Thangjam et al., 2016). The three band parameter space with defined polyhedrons is more advanced and robust compared to the generally used two-dimensional spectral analysis i.e., two band parameter space. A revised petrologic evolution model is presented to explain the ongoing problem of missing olivine-rich mantle of Vesta and also the petrogenesis of HED meteorites (howardite, eucrite, diogenite clan of stony achondrites).

NASA's New Horizons spacecraft has revealed the complex geology of Pluto and Charon. Pluto's encounter hemisphere shows ongoing surface geological activity centered on a vast basin containing a thick layer of volatile ices that appears to be involved in convection and advection, with a crater retention age no greater than $\approx$10 Ma. Surrounding terrains show active glacial flow, apparent transport and rotation of large buoyant water-ice crustal blocks, and pitting, likely by sublimation erosion and/or collapse. More enigmatic features include tall mounds with central depressions that are conceivably cryovolcanic, and ridges with complex bladed textures. Pluto also has ancient cratered terrains up to ~4 Ga old that are extensionally fractured and extensively mantled and perhaps eroded by glacial or other processes. Charon does not appear to be currently active, but experienced major extensional tectonism and resurfacing (probably cryovolcanic) nearly 4 billion years ago. Impact crater populations on Pluto and Charon are not consistent with the steepest proposed impactor size-frequency distributions proposed for the Kuiper belt.

In a Forum published in EOS Transactions AGU (2009) entitled "Lies, damned lies and statistics (in Geology)", Vermeesch (2009) claims that "statistical significant is not the same as geological significant", in other words, statistical tests may be misleading. In complete contradiction, we affirm that statistical tests are always informative. We detail the several mistakes of Vermeesch in his initial paper and in his comments to our reply. The present text is developed in the hope that it can serve as an illuminating pedagogical exercise for students and lecturers to learn more about the subtleties, richness and power of the science of statistics.

An overview of the tomographic interpretation method in engineering geophysics is presented, considering the two approaches of the deterministic tomography inversion, developed for rock elasticity analysis, and the probability tomography imaging developed in the domain of potential fields methods. The theoretical basis of both approaches is shortly outlined before showing a laboratory and a field application.

This paper explores how a pluralist view can arise in a natural way out of the day-to-day practice of modern set theory. By contrast, the widely accepted orthodox view is that there is an ultimate universe of sets $V$, and it is in this universe that mathematics takes place. From this view, the purpose of set theory is "learning the truth about $V$." It has become apparent, however, that the phenomenon of independence - those questions left unresolved by the axioms - holds a central place in the investigation. This paper introduces the notion of independence, explores the primary tool ("soundness") for establishing independence results, and shows how a plurality of models arises through the investigation of this phenomenon. Building on a familiar example from Euclidean geometry, a template for independence proofs is established. Applying this template in the domain of set theory leads to a consideration of forcing, the tool par excellence for constructing universes of sets. Fifty years of forcing has resulted in a profusion of universes exhibiting a wide variety of characteristics - a multiverse of set theories. Direct study of this multiverse presents technical challenges due to i

A ground of the universe V is a transitive proper class W subset V, such that W is a model of ZFC and V is obtained by set forcing over W, so that V = W[G] for some W-generic filter G subset P in W . The model V satisfies the ground axiom GA if there are no such W properly contained in V . The model W is a bedrock of V if W is a ground of V and satisfies the ground axiom. The mantle of V is the intersection of all grounds of V . The generic mantle of V is the intersection of all grounds of all set-forcing extensions of V . The generic HOD, written gHOD, is the intersection of all HODs of all set-forcing extensions. The generic HOD is always a model of ZFC, and the generic mantle is always a model of ZF. Every model of ZFC is the mantle and generic mantle of another model of ZFC. We prove this theorem while also controlling the HOD of the final model, as well as the generic HOD. Iteratively taking the mantle penetrates down through the inner mantles to what we call the outer core, what remains when all outer layers of forcing have been stripped away. Many fundamental questions remain open.

In many cases, groundwater flow in an unconfined aquifer can be simplified to a one-dimensional Sturm-Liouville model of the form: \begin{equation*} x''(t)+λx(t)=h(t)+\varepsilon f(x(t)),\hspace{.1in}t\in(0,π) \end{equation*} subject to non-local boundary conditions \begin{equation*} x(0)=h_1+\varepsilonη_1(x)\text{ and } x(π)=h_2+\varepsilonη_2(x). \end{equation*} In this paper, we study the existence of solutions to the above Sturm-Liouville problem under the assumption that $\varepsilon$ is a small parameter. Our method will be analytical, utilizing the implicit function theorem and its generalizations.

Europa has been conf irmed to have a multilayered structure and complex geological condition in last two decades whose detail and cause of formation remains unclear.In this work,we start from analyzing the mechanism of tidal ef fect on satellite's surface and discuss if interaction like tidal locking and orbital resonance play an important role in tidal ef fect including heating,underground convection and eruption.During discussion we propose the main factors affecting Europa's tidal heat and the formation mechanism of typical shallow geological features,and provide theoretical support for further exploration.

Geological processes determine the distribution of resources such as critical minerals, water, and geothermal energy. However, direct observation of geology is often prevented by surface cover such as overburden or vegetation. In such cases, remote and in-situ surveys are frequently conducted to collect physical measurements of the earth indicative of the geology. Developing a geological segmentation based on these measurements is challenging since individual datasets can differ in properties (e.g. units, dynamic ranges, textures) and because the data does not uniquely constrain the geology. Further, as the number of datasets grows the information to constrain geology increases while simultaneously becoming harder to make sense of. Inspired by the concept of superpixels, we propose a deep-learning based approach to segment rasterized survey data into regions with similar characteristics. We demonstrate its use for semi-automated geoscientific mapping with datasets arising from independent sensors and with diverse properties. In addition, we introduce a new loss function for superpixels including a novel regularization parameter penalizing image segmentation with non-connected compo

Deschamps and Mottez (hereafter DM) argue that the Gauss-Matuyama terrestrial magnetic field reversal may have left a vanishing main dipole moment to the field for a time of order 10,000 years. They say this may have allowed an enhanced cosmic ray flux, boosting the effect we proposed in Melott and Thomas (2019). We point out that the bulk of the cosmic ray flux from a nearby supernova should be too energetic, up to a million times more energetic than the limits of deflection by the terrestrial magnetic field. In fact, only those highly energetic ones will directly reach the troposphere, relevant for cloud-to-ground lightning. From Cosmic Explosions to Terrestrial Fires?: A Discussion. F. Deschamps and F. Mottez. J. Geology 128, online ahead of print. (2020) From Cosmic Explosions to Terrestrial Fires?: A Reply A.L. Melott and B.C. Thomas. J. Geology 128, online ahead of print. (2020) From cosmic explosions to terrestrial fires? (A.L. Melott and B.C. Thomas) Journal of Geology, 127, 475-481 10.1086/703418 (2019) [arXiv:1903.01501]

Recent advances in interdisciplinary fields as diverse as astrophysics, cosmogeophysics, nuclear geology, etc. have led to interesting developments in the non-organic theory of the genesis of petroleum. This theory, which holds that petroleum is of an abiogenic primordial origin, provides an explanation for certain features of petroleum geology that are hard to explain within the standard organic framework. If the non-organic theory is correct, then hydrocarbon reserves would be enormous and almost inexhaustable.

Google Earth is a huge source of interesting illustrations of various natural phenomena. It can represent a valuable tool for science education, not only for teaching geography and geology, but also physics. Here we suggest that Google Earth can be used for introducing in an attractive way the physics of waves.

Multiple lines of evidence point to one or more moderately nearby supernovae, with the strongest signal ~2.6 Ma. We build on previous work to argue for the likelihood of cosmic ray ionization of the atmosphere and electron cascades leading to more frequent lightning, and therefore an increase in nitrate deposition and in wildfires. The potential exists for a large increase in the pre-human nitrate flux onto the surface, which has previously been argued to lead to CO2 drawdown and cooling of the climate. Evidence for increased wildfires exists in an increase in soot and carbon deposits over the relevant period. The wildfires would have contributed to the transition from forest to savanna in northeast Africa, long argued to have been a factor in the evolution of hominin bipedalism.