A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
Machine learning detects drilling anomalies, reducing accidents and costs.
Directional oil well drilling requires high precision of the wellbore positioning inside the productive area. However, due to specifics of engineering design, sensors that explicitly determine the type of the drilled rock are located farther than 15m from the drilling bit. As a result, the target area runaways can be d…
During the directional drilling, a bit may sometimes go to a nonproductive rock layer due to the gap about 20m between the bit and high-fidelity rock type sensors. The only way to detect the lithotype changes in time is the usage of Measurements While Drilling (MWD) data. However, there are no general mathematical mode…
The paper proves drilled bundles over graphs are virtually special cubulable.
Drilling hyperbolic groups to simplify complex conjectures.
Uniform linear bounds on volume changes in 3D hyperbolic spaces.
Study bounds changes in hyperbolic 3-manifold structures after drilling short geodesics.
Machine learning improves prediction of complex geology ahead of drilling.
Profinite rigidity proven for many hyperbolic manifolds.
In-plane drill rotations are impossible for smooth shells.
In this paper we investigate how the volume of hyperbolic manifolds increases under the process of removing a curve, that is, Dehn drilling. If the curve we remove is a geodesic we are able to show that for a certain family of manifolds the volume increase is bounded above by where is the length of the g…
Characterizes neutral deformation modes of minimal surfaces.
EnLSTM network improves log generation from small datasets.
Study explores kinematics of surfaces under metric restrictions.
Detects project management anti-patterns using code and issue data.
New Einstein metrics found close to almost hyperbolic ones.
Generative adversarial network improves geosteering in fluvial reservoirs.
Effective drilling and filling bounds for hyperbolic 3-manifolds.
Given a hyperbolic 3-manifold M containing an embedded closed geodesic, we estimate the volume of a complete hyperbolic metric on the complement of the geodesic in terms of the geometry of M. As a corollary, we show that the smallest volume orientable hyperbolic 3-manifold has volume >.32 .
We supply a proof of the fact that a hyperbolic 3-manifold with finitely generated fundamental group and with no parabolics is topologically tame. This proves the Marden's conjecture. Our approach is to form an exhaustion of and modify the boundary to make them 2-convex. We use the induced path-metric, wh…
3D convolutional neural networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object. In this paper, we present a 3D-CNN based method to learn distinct local geometric features of interest within an object. In this context, the voxelized representation may not be sufficient to captu…
In this paper we try to establish a connection between a three-dimensional Lotka--Volterra dynamical system and two-dimensional topological surgery. There are many physical phenomena exhibiting two-dimensional topological surgery through a `hole drilling' process. By our connection, such phenomena may be modelled mathe…
3D Convolutional Neural Networks (3D-CNN) have been used for object recognition based on the voxelized shape of an object. However, interpreting the decision making process of these 3D-CNNs is still an infeasible task. In this paper, we present a unique 3D-CNN based Gradient-weighted Class Activation Mapping method (3D…
The main task in oil and gas exploration is to gain an understanding of the distribution and nature of rocks and fluids in the subsurface. Well logs are records of petro-physical data acquired along a borehole, providing direct information about what is in the subsurface. The data collected by logging wells can have si…
New method fractures hyperbolic manifolds using cone singularities.
Bounding geodesic length variation for surface projective structures.
We prove a volume inequality for 3-manifolds having C^0 metrics "bent" along a hypersurface, and satisfying certain curvature pinching conditions. The result makes use of Perelman's work on Ricci flow and geometrization of closed 3-manifolds. Corollaries include a new proof of a conjecture of Bonahon about volumes of c…
The process of exploring and exploiting Oil and Gas (O&G) generates a lot of data that can bring more efficiency to the industry. The opportunities for using data mining techniques in the "digital oil-field" remain largely unexplored or uncharted. With the high rate of data expansion, companies are scrambling to develo…
In this paper we define a new state sum based on the regions defined by tangles on a surface which is an oriented closed surface with a finite number of open holes drilled. From this state sum we obtain an invariant of regular isotopy for the tangles named -invariant. The values of the -invariant are in $\mathbb{…
The objective of this work is to study the applicability of various Machine Learning algorithms for prediction of some rock properties which geoscientists usually define due to special lab analysis. We demonstrate that these special properties can be predicted only basing on routine core analysis (RCA) data. To validat…
The study connects translation length to manifold structure, proving bounds and identifying finite types.
We extend Matveev's complexity of 3-manifolds to PL compact manifolds of arbitrary dimension, and we study its properties. The complexity of a manifold is the minimum number of vertices in a simple spine. We study how this quantity changes under the most common topological operations (handle additions, finite coverings…
Horizontal surgery on pseudo-Anosov flows yields almost equivalent flows.
In this paper we observe that 2-dimensional 0-surgery occurs in natural processes, such as tornado formation and other phenomena reminiscent of hole drilling. Inspired by such phenomena, we introduce new theoretical concepts which enhance the formal definition of 2-dimensional 0-surgery with the observed dynamics. To d…
With recent progress in algorithms and the availability of massive amounts of computation power, application of machine learning techniques is becoming a hot topic in the oil and gas industry. One of the most promising aspects to apply machine learning to the upstream field is the rock facies classification in reservoi…
Veering branched surfaces help construct geodesic flows on curved surfaces.
Using PL-methods, we prove the Marden's conjecture that a hyperbolic 3-manifold with finitely generated fundamental group and with no parabolics are topologically tame. Our approach is to form an exhaustion of and modify the boundary to make them 2-convex. We use the induced path-metric, which makes the s…
Proposes RTL model for sentiment classification and key word detection in online reviews.
We introduce and study some deformations of complete finite-volume hyperbolic four-manifolds that may be interpreted as four-dimensional analogues of Thurston's hyperbolic Dehn filling. We construct in particular an analytic path of complete, finite-volume cone four-manifolds that interpolates between two hyperbo…
The growing capability and accessibility of machine learning has led to its application to many real-world domains and data about people. Despite the benefits algorithmic systems may bring, models can reflect, inject, or exacerbate implicit and explicit societal biases into their outputs, disadvantaging certain demogra…
Deep learning speeds up pressure prediction in carbon storage reservoirs.
Study identifies mental stress in firefighters using heart rate variability data.
Workflow uses deep learning to improve geosteering accuracy in Goliat Field.
The paper provides explicit bilipschitz bounds on Dehn fillings of hyperbolic 3-manifolds.
Topological surgery is a mathematical technique used for creating new manifolds out of known ones. We observe that it occurs in natural phenomena where a sphere of dimension 0 or 1 is selected, forces are applied and the manifold in which they occur changes type. For example, 1-dimensional surgery happens during chromo…
Graphs are a natural abstraction for many problems where nodes represent entities and edges represent a relationship across entities. An important area of research that has emerged over the last decade is the use of graphs as a vehicle for non-linear dimensionality reduction in a manner akin to previous efforts based o…
Develops neural network for directed hypergraphs for node classification.
Develops PageRank for directed hypergraphs using metabolic network.