334 research outputs found
Research Risk Factors in Monitoring Well DrillingβA Case Study Using Machine Learning Methods
This article takes an approach to creating a machine learning model for the oil and gas industry. This task is dedicated to the most up-to-date issues of machine learning and artificial intelligence. One of the goals of this research was to build a model to predict the possible risks arising in the process of drilling wells. Drilling of wells for oil and gas production is a highly complex and expensive part of reservoir development. Thus, together with injury prevention, there is a goal to save cost expenditures on downtime and repair of drilling equipment. Nowadays, companies have begun to look for ways to improve the efficiency of drilling and minimize non-production time with the help of new technologies. To support decisions in a narrow time frame, it is valuable to have an early warning system. Such a decision support system will help an engineer to intervene in the drilling process and prevent high expenses of unproductive time and equipment repair due to a problem. This work describes a comparison of machine learning algorithms for anomaly detection during well drilling. In particular, machine learning algorithms will make it possible to make decisions when determining the geometry of the grid of wellsβthe nature of the relative position of production and injection wells at the production facility. Development systems are most often subdivided into the following: placement of wells along a symmetric grid, and placement of wells along a non-symmetric grid (mainly in rows). The tested models classify drilling problems based on historical data from previously drilled wells. To validate anomaly detection algorithms, we used historical logs of drilling problems for 67 wells at a large brownfield in Siberia, Russia. Wells with problems were selected and analyzed. It should be noted that out of the 67 wells, 20 wells were drilled without expenses for unproductive time. The experiential results illustrate that a model based on gradient boosting can classify the complications in the drilling process better than other models.publishedVersio
Π Π°Π·ΡΠ°Π±ΠΎΡΠΊΠ° ΠΏΡΠΎΠ³ΡΠ°ΠΌΠΌΠ½ΡΡ ΡΡΠ΅Π΄ΡΡΠ² Π΄Π»Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΡ ΠΎΡΠ½ΠΎΠ²Π½ΡΡ ΠΏΠΎΠΊΠ°Π·Π°ΡΠ΅Π»Π΅ΠΉ, Ρ Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΠ·ΡΡΡΠΈΡ ΠΏΠ°ΡΡΠ°ΠΆΠΈΡΠΎΠΏΠΎΡΠΎΠΊ Π°Π²ΡΠΎΠ±ΡΡΠ½ΠΎΠ³ΠΎ ΠΌΠ°ΡΡΡΡΡΠ°
TheΒ workΒ presentsΒ theΒ softwareΒ toolsΒ forΒ calculatingΒ basicΒ indicesΒ ofΒ passengerΒ
trafficΒ onΒ busΒ routes.
Development of a formalism of discrete element method to study mechanical response of geological materials and media at different scales
A general approach to realization of models of elasticity, plasticity and fracture of heterogeneous materials within the framework of particle-based discrete element method is proposed in the paper. The approach is based on constructing many-body forces of particle interaction, which provide response of particle ensemble correctly conforming to the response (including elastic-plastic behavior and fracture) of simulated solids. For correct modeling of inelastic deformation and failure of geological materials and media at "high" structural scales (relative to the scale of grains) an implementation of dilatational Nikolaevsky's model of plasticity of rocks within the framework of mathematical formalism of discrete element method is proposed. Perspectives of multiscale modeling of geological materials from grainrelated scale up to macroscopic scale within the same numerical technique (DEM) are discussed
Trigonal-bipyramidal Anion [Ph2Cl3Sn]- in the Structure of N-[(Diethylphosphoryl)methyl] piperidinium Diphenyltrichlorostannate(IV)
Crystal structure of N-(diethylphosphoryl)methyl-piperidinium diphenyltrichlorostannate(IV), C10H23NO3P+ C12H10Cl3Sn- has been determined, a = 11.416(2), b = 11.582(2), c = 12.491(2) Γ
, α = 69.82(2), β = 81.22(2), γ = 60.73(2)Β°, space group P1̅, 4493 reflections, R(F) = 0.0271, wR(F2) = 0.0712. The structure consists of isolated trigonal-bipyramidal anions and hydrogen-bonded dimers formed by cations. The impact of secondary Snβ
β
β
Cl interactions on the geometry of complex anions is discussed
Kinks in the Hartree approximation
The topological defects of the lambda phi^4 theory, kink and antikink, are
studied in the Hartree approximation. This allows us to discuss quantum effects
on the defects in both stationary and dynamical systems. The kink mass is
calculated for a number of parameters, and compared to classical, one loop and
Monte Carlo results known from the literature. We discuss the thermalization of
the system after a kink antikink collision. A classical result, the existence
of a critical speed, is rederived and shown for the first time in the quantum
theory. We also use kink antikink collisions as a very simple toy model for
heavy ion collisions and discuss the differences and similarities, for example
in the pressure. Finally, using the Hartree Ensemble Approximation allows us to
study kink antikink nucleation starting from a thermal (Bose Einstein)
distribution. In general our results indicate that on a qualitative level there
are few differences with the classical results, but on a quantitative level
there are some import ones.Comment: 20 pages REVTeX 4, 17 Figures. Uses amsmath.sty and subfigure.sty.
Final version, fixed typo in published versio
Intermolecular interactions-photophysical properties relationships in phenanthrene-9,10-dicarbonitrile assemblies
Phenanthrene-9,10-dicarbonitriles show various luminescence behaviour in solution and in the solid state. Aggregation patterns of phenanthrene-9,10-dicarbonitriles govern their luminescent properties in the solid state. Single crystal structures of phenanthrene-9,10-dicarbonitriles showed head-to-tail intraplane (or quasi-intraplane) intermolecular interactions and Ο-stacking patterns with eclipsing of molecules when viewed orthogonal to the stacking plane. The Ο-stacking interactions were detected in the X-ray structures of phenanthrene-9,10-dicarbonitriles and studied by DFT calculations at the M06β2X/6β311++G(d,p) level of theory and topological analysis of the electron density distribution within the framework of QTAIM method. The estimated strength of the Cβ―C contacts responsible for the Ο-stacking interactions is 0.6β1.1 kcal/mol. The orientation of molecules in crystals depends on the substituents in phenanthrene-9,10-dicarbonitriles. Distinct molecular orientation and packing arrangements in crystalline phenanthrene-9,10-dicarbonitriles ensured perturbed electronic communication among the nearest and non-nearest molecules through an interplay of excimer and dipole couplings. As a result, the intermolecular interactions govern the solid state luminescence of molecules
Structural data of phenanthrene-9,10-dicarbonitriles
In this data article, we present the single-crystal XRD data of phenanthrene-9,10-dicarbonitriles. Detailed structure analysis and photophysical properties were discussed in our previous study, "Intermolecular interactions-photophysical properties relationships in phenanthrene-9,10-dicarbonitrile assemblies" (Afanasenko et al., 2020). The data include the intra- and intermolecular bond lengths and angles. (c) 2019 The Author(s). Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/)
Stochastic Production Of Kink-Antikink Pairs In The Presence Of An Oscillating Background
We numerically investigate the production of kink-antikink pairs in a
dimensional field theory subject to white noise and periodic driving.
The twin effects of noise and periodic driving acting in conjunction lead to
considerable enhancement in the kink density compared to the thermal
equilibrium value, for low dissipation coefficients and for a specific range of
frequencies of the oscillating background. The dependence of the kink-density
on the temperature of the heat bath, the amplitude of the oscillating
background and value of the dissipation coefficient is also investigated. An
interesting feature of our result is that kink-antikink production occurs even
though the system always remains in the broken symmetry phase.Comment: Revtex, 21 pages including 7 figures; more references adde
ΠΠ¦ΠΠΠΠ Π‘Π’ΠΠ’ΠΠ‘Π’ΠΠ§ΠΠ‘ΠΠΠ₯ Π₯ΠΠ ΠΠΠ’ΠΠ ΠΠ‘Π’ΠΠ ΠΠΠΠΠ ΠΠ€ΠΠ§ΠΠ‘ΠΠΠ ΠΠΠΠΠ₯Π ΠΠ Π ΠΠΠΠΠΠΠΠΠΠΠ¬ΠΠΠ Π ΠΠΠΠ‘Π’Π ΠΠ¦ΠΠ ΠΠΠΠΠ’Π ΠΠΠΠ ΠΠΠΠ‘ΠΠΠΠΠΠ
Electromyographic noise is one of the most common noises in electrocardiogram. In case of several electrocardiogram leads, electromyographic noise affects each lead to different extent. It can be taken into account when developing algorithms for multilead electrocardiogram record processing. However, in the existing literature, there is no information about the relationship of electromyographic noise in various ECG leads and their joint probability distribution. The purpose of this paper is to study statistical characteristics of electromyographic noise in ECG signal, from which the electromyographic noise is extracted. The paper proposes a method for extracting electromyographic noise from electrocardiogram signal, based on a polynomial approximation of electrocardiogram signal fragments in sliding window with overlapping fragment subsequent weight averaging. Using this method, fragments of electromyographic noise are extracted from multichannel electrocardiogram records. Based on the obtained data, a joint probability distribution function of electromyographic noise in two adjacent leads is selected, and the correlation relationships between the electromyographic noise in various ECG leads are investigated. The results show that the joint probability distribution function of electromyographic noise in two adjacent leads in the first approximation can be described using bivariate normal distribution. In addition, between the samples of electromyographic noise from two adjacent leads quite strong correlation relationships can be observed.ΠΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΏΠΎΠΌΠ΅Ρ
Π° ΡΠ²Π»ΡΠ΅ΡΡΡ ΠΎΠ΄Π½ΠΎΠΉ ΠΈΠ· ΡΠ°ΠΌΡΡ
ΡΠ°ΡΠΏΡΠΎΡΡΡΠ°Π½Π΅Π½Π½ΡΡ
ΠΏΠΎΠΌΠ΅Ρ
, ΠΏΡΠΈΡΡΡΡΡΠ²ΡΡΡΠΈΡ
Π² ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π΅. Π ΡΠ»ΡΡΠ°Π΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΈΡ
ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π° ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠ°Ρ ΠΏΠΎΠΌΠ΅Ρ
Π° Π² ΡΠ°Π·Π½ΠΎΠΉ ΡΡΠ΅ΠΏΠ΅Π½ΠΈ ΠΎΠΊΠ°Π·ΡΠ²Π°Π΅Ρ Π²Π»ΠΈΡΠ½ΠΈΠ΅ Π½Π° ΠΊΠ°ΠΆΠ΄ΠΎΠ΅ ΠΈΠ· ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΠΉ. ΠΡΠΎ Π²Π»ΠΈΡΠ½ΠΈΠ΅ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΡΡΡΠ΅Π½ΠΎ ΠΏΡΠΈ ΠΏΠΎΡΡΡΠΎΠ΅Π½ΠΈΠΈ Π°Π»Π³ΠΎΡΠΈΡΠΌΠΎΠ² ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΠΈ ΠΌΠ½ΠΎΠ³ΠΎΠΊΠ°Π½Π°Π»ΡΠ½ΡΡ
Π·Π°ΠΏΠΈΡΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π°. ΠΠ΄Π½Π°ΠΊΠΎ Π² ΡΡΡΠ΅ΡΡΠ²ΡΡΡΠ΅ΠΉ Π»ΠΈΡΠ΅ΡΠ°ΡΡΡΠ΅ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΎΡΠ½ΠΎ ΠΏΠΎΠ»Π½ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ Π°Π½Π°Π»ΠΈΠ· Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·Π΅ΠΉ ΠΎΡΡΡΠ΅ΡΠΎΠ² ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΡΡ
ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π°. Π¦Π΅Π»Ρ ΡΠ°Π±ΠΎΡΡ β ΡΠΌΠΏΠΈΡΠΈΡΠ΅ΡΠΊΠΎΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΠ΅ ΡΡΠ°ΡΠΈΡΡΠΈΡΠ΅ΡΠΊΠΈΡ
Ρ
Π°ΡΠ°ΠΊΡΠ΅ΡΠΈΡΡΠΈΠΊ ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ, Π²ΡΠ΄Π΅Π»Π΅Π½Π½ΠΎΠΉ ΠΈΠ· Π·Π°ΡΡΠΌΠ»Π΅Π½Π½ΡΡ
ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠΎΠ² ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π°. ΠΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ ΠΌΠ΅ΡΠΎΠ΄ Π²ΡΠ΄Π΅Π»Π΅Π½ΠΈΡ ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ ΠΈΠ· Π·Π°ΠΏΠΈΡΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π°. ΠΠ΅ΡΠΎΠ΄ ΠΎΡΠ½ΠΎΠ²Π°Π½ Π½Π° ΠΏΠΎΠ»ΠΈΠ½ΠΎΠΌΠΈΠ°Π»ΡΠ½ΠΎΠΉ Π°ΠΏΠΏΡΠΎΠΊΡΠΈΠΌΠ°ΡΠΈΠΈ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠΎΠ² ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π° Π² ΡΠΊΠΎΠ»ΡΠ·ΡΡΠ΅ΠΌ ΠΎΠΊΠ½Π΅ Ρ ΠΏΠΎΡΠ»Π΅Π΄ΡΡΡΠΈΠΌ Π²Π΅ΡΠΎΠ²ΡΠΌ ΡΡΡΠ΅Π΄Π½Π΅Π½ΠΈΠ΅ΠΌ ΠΏΠ΅ΡΠ΅ΠΊΡΡΠ²Π°ΡΡΠΈΡ
ΡΡ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠΎΠ². Π‘ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ΠΌ Π΄Π°Π½Π½ΠΎΠ³ΠΎ ΠΌΠ΅ΡΠΎΠ΄Π° ΠΈΠ· ΠΌΠ½ΠΎΠ³ΠΎΠΊΠ°Π½Π°Π»ΡΠ½ΡΡ
Π·Π°ΠΏΠΈΡΠ΅ΠΉ ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π° Π±ΡΠ»ΠΈ Π²ΡΠ΄Π΅Π»Π΅Π½Ρ ΡΡΠ°Π³ΠΌΠ΅Π½ΡΡ ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ. ΠΠ° ΠΎΡΠ½ΠΎΠ²Π΅ Π²ΡΠ΄Π΅Π»Π΅Π½Π½ΡΡ
ΡΡΠ°Π³ΠΌΠ΅Π½ΡΠΎΠ² ΠΏΠΎΠ΄ΠΎΠ±ΡΠ°Π½ΠΎ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΎΡΡΡΠ΅ΡΠΎΠ² ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ Π² Π΄Π²ΡΡ
ΡΠΌΠ΅ΠΆΠ½ΡΡ
ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΡΡ
, Π° ΡΠ°ΠΊΠΆΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½Ρ ΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½ΡΠ΅ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·ΠΈ ΠΌΠ΅ΠΆΠ΄Ρ ΠΎΡΡΡΠ΅ΡΠ°ΠΌΠΈ ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ Π² ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΡΡ
ΡΠ»Π΅ΠΊΡΡΠΎΠΊΠ°ΡΠ΄ΠΈΠΎΡΠΈΠ³Π½Π°Π»Π°. Π ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠ΅ ΡΡΡΠ°Π½ΠΎΠ²Π»Π΅Π½ΠΎ, ΡΡΠΎ ΡΠΎΠ²ΠΌΠ΅ΡΡΠ½ΠΎΠ΅ ΡΠ°ΡΠΏΡΠ΅Π΄Π΅Π»Π΅Π½ΠΈΠ΅ ΠΎΡΡΡΠ΅ΡΠΎΠ² ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ Π² Π΄Π²ΡΡ
ΡΠΌΠ΅ΠΆΠ½ΡΡ
ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΡΡ
Π² ΠΏΠ΅ΡΠ²ΠΎΠΌ ΠΏΡΠΈΠ±Π»ΠΈΠΆΠ΅Π½ΠΈΠΈ ΠΌΠΎΠΆΠ΅Ρ Π±ΡΡΡ ΠΎΠΏΠΈΡΠ°Π½ΠΎ Ρ ΠΏΠΎΠΌΠΎΡΡΡ Π΄Π²ΡΠΌΠ΅ΡΠ½ΠΎΠ³ΠΎ Π½ΠΎΡΠΌΠ°Π»ΡΠ½ΠΎΠ³ΠΎ Π·Π°ΠΊΠΎΠ½Π°. ΠΡΠΎΠΌΠ΅ ΡΠΎΠ³ΠΎ, ΠΌΠ΅ΠΆΠ΄Ρ ΠΎΡΡΡΠ΅ΡΠ°ΠΌΠΈ ΠΌΠΈΠΎΠ³ΡΠ°ΡΠΈΡΠ΅ΡΠΊΠΎΠΉ ΠΏΠΎΠΌΠ΅Ρ
ΠΈ ΠΈΠ· Π΄Π²ΡΡ
ΡΠΌΠ΅ΠΆΠ½ΡΡ
ΠΎΡΠ²Π΅Π΄Π΅Π½ΠΈΠΉ ΠΌΠΎΠ³ΡΡ Π½Π°Π±Π»ΡΠ΄Π°ΡΡΡΡ Π΄ΠΎΠ²ΠΎΠ»ΡΠ½ΠΎ ΡΠΈΠ»ΡΠ½ΡΠ΅ ΠΊΠΎΡΡΠ΅Π»ΡΡΠΈΠΎΠ½Π½ΡΠ΅ Π²Π·Π°ΠΈΠΌΠΎΡΠ²ΡΠ·ΠΈ
Cover letter
Acromegaly is a neuroendocrine disorder with multiple comorbidities. In this article, we present a patient with long-term active acromegaly, without clinical remission after repeated neurosurgery and long-term treatment with somatostatin analogue. After the first neurosurgical treatment, cyclic ovarian function improved. Taken together with progressing metabolic disorders, it led to clinical manifestation of adenomyosis, which presented by algomenorrhea, menometrorrhagia and severe anemia. Due to clinical manifestation and extent of the disease, the patient underwent hysterectomy. Histologically we observed adenomyosis II with 2/3 myometrialpenetration. This clinical case highlights the importance of gynecological assessment among patients with acromegaly of late reproductive and premenopausal period
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