scholarly journals Predictive assessment of the fluid loss properties of thin-layer reservoirs of Vikulovskaya series based on the results of core and well logs

Georesursy ◽  
2021 ◽  
Vol 23 (2) ◽  
pp. 170-178
Author(s):  
Tatyana G. Isakova ◽  
Tatyana F. Diakonova ◽  
Alena D. Nosikova ◽  
Georgy A. Kalmykov ◽  
Alexander V. Akinshin ◽  
...  

The aim of the work is to predict the filtration capacity of reservoirs based on core and well logs data at the stage of petrophysical study of rocks before the start of active development of the object. All the results were obtained from the data of porometric characteristics of rocks on the example of the vikulovskaya series’s deposits of the Krasnoleninsky arch. The patterns of changes in pore sizes and their contribution to the total filtration depending on the lithophysical type of the rock were established on the core plug. A classification of rocks by pore radii is proposed, and a method for assessing the filtration capacity of reservoirs based on well logs data is developed, with the calculation of the share of each layer in the planned perforation interval

2019 ◽  
Vol 9 (22) ◽  
pp. 4871 ◽  
Author(s):  
Quan Liu ◽  
Chen Feng ◽  
Zida Song ◽  
Joseph Louis ◽  
Jian Zhou

Earthmoving is an integral civil engineering operation of significance, and tracking its productivity requires the statistics of loads moved by dump trucks. Since current truck loads’ statistics methods are laborious, costly, and limited in application, this paper presents the framework of a novel, automated, non-contact field earthmoving quantity statistics (FEQS) for projects with large earthmoving demands that use uniform and uncovered trucks. The proposed FEQS framework utilizes field surveillance systems and adopts vision-based deep learning for full/empty-load truck classification as the core work. Since convolutional neural network (CNN) and its transfer learning (TL) forms are popular vision-based deep learning models and numerous in type, a comparison study is conducted to test the framework’s core work feasibility and evaluate the performance of different deep learning models in implementation. The comparison study involved 12 CNN or CNN-TL models in full/empty-load truck classification, and the results revealed that while several provided satisfactory performance, the VGG16-FineTune provided the optimal performance. This proved the core work feasibility of the proposed FEQS framework. Further discussion provides model choice suggestions that CNN-TL models are more feasible than CNN prototypes, and models that adopt different TL methods have advantages in either working accuracy or speed for different tasks.


Talanta ◽  
2021 ◽  
pp. 122460
Author(s):  
Matthias Guggenberger ◽  
Josua T. Oberlerchner ◽  
Heinrich Grausgruber ◽  
Thomas Rosenau ◽  
Stefan Böhmdorfer
Keyword(s):  

Author(s):  
Yu-Ru Lin ◽  
Jr-Yi Wang ◽  
Shun-Cheng Chang ◽  
Kwang-Hwa Chang ◽  
Hung-Chou Chen ◽  
...  

Burn injuries cause disability and functional limitations in daily living. In a 2015 fire explosion in Taiwan, 499 young people sustained burn injuries. The construction of an effective and comprehensive rehabilitation program that enables patients to regain their previous function is imperative. The International Classification of Functioning, Disability, and Health (ICF) includes multiple dimensions that can contribute to meeting this goal. An ICF core set was developed in this study for Taiwanese patients with burns. A consensus process using three rounds of the Delphi technique was employed. A multidisciplinary team of 30 experts from various institutions was formed. The questionnaire used in this study comprised 162 ICF second-level categories relevant to burn injuries. A 5-point Likert scale was used, and participants assigned a weight to the effect of each category on daily activities after burns. The consensus among ratings was assessed using Spearman’s ρ and semi-interquartile range indices. The core set for post-acute SCI was developed from categories that attained a mean score of ≥4.0 in the third round of the Delphi exercise. The core ICF set contained 68 categories. Of these, 19 comprised the component of body functions, 5 comprised body structures, 37 comprised activities and participation, and 7 comprised environmental factors. This preliminary core set offers a comprehensive system for disability assessment and verification following burn injury. The core set provides information for effective rehabilitation strategy setting for patients with burns. Further feasibility and validation studies are required in the future.


2018 ◽  
Vol 5 (6) ◽  
pp. 172445 ◽  
Author(s):  
Lorenzo Napolitano ◽  
Evangelos Evangelou ◽  
Emanuele Pugliese ◽  
Paolo Zeppini ◽  
Graham Room

We analyse the autocatalytic structure of technological networks and evaluate its significance for the dynamics of innovation patenting. To this aim, we define a directed network of technological fields based on the International Patents Classification, in which a source node is connected to a receiver node via a link if patenting activity in the source field anticipates patents in the receiver field in the same region more frequently than we would expect at random. We show that the evolution of the technology network is compatible with the presence of a growing autocatalytic structure, i.e. a portion of the network in which technological fields mutually benefit from being connected to one another. We further show that technological fields in the core of the autocatalytic set display greater fitness, i.e. they tend to appear in a greater number of patents, thus suggesting the presence of positive spillovers as well as positive reinforcement. Finally, we observe that core shifts take place whereby different groups of technology fields alternate within the autocatalytic structure; this points to the importance of recombinant innovation taking place between close as well as distant fields of the hierarchical classification of technological fields.


1992 ◽  
Vol 6 (4) ◽  
pp. 413-428 ◽  
Author(s):  
C.J. Van Oss ◽  
R.F. Giese ◽  
Z. Li ◽  
K. Murphy ◽  
J. Norris ◽  
...  

2017 ◽  
Vol 2017 (1) ◽  
pp. 232-242 ◽  
Author(s):  
Александр Таранов ◽  
Aleksandr Taranov ◽  
Наталья Таранова ◽  
Natalya Taranova

The paper reports the concept of a technological way as an urgent and empirically substantiated continuation of the wellknown theory of long waves in economy. The theory of long waves allows predicting on an empirical level world economic crises and an economic growth on the horizon for 50 years. The genesis of the theory of long waves by means of retrospective author’s classification of theories of long waves in accordance with technological, economic, institutional, administrative and social signs is analyzed. A basic range of authors having formed a modern and urgent theory of long waves which is verified by time and supported by empirical computations is presented by N.D. Kondratiev, G. Mensch, J. Dossy, Ch. Peres, S.Yu. Glaziev. The concept of a technological way being empirically confirmed by the continuation of the theory of long waves was formed by Academician Glaziev. In this concept there are revealed basic statement-laws and also the necessity of methodological approaches in technological, economic, institutional, administrative and sociological fields. The logic of the formation and interaction of technological totality is described thoroughly. The conclusions of technological way existence are drawn. Technological innovations defining the formation of the core of a technological way and revolutionizing a technological structure of economy have obtained a name of a “key factor”. Nanotechnologies are such a factor at present and for the prospect of 50 years. The conclusions of a basic property of a technological way being a self-reproducing integrity are drawn in consequence of which the technical development of economy cannot take place otherwise as by means of a successive change of technological ways.


2015 ◽  
Vol 28 (1) ◽  
pp. 51-76 ◽  
Author(s):  
Bernd Steinbach ◽  
Christian Posthoff

The Boolean Differential Calculus (BDC) significantly extends the Boolean Algebra because not only Boolean values 0 and 1, but also changes of Boolean values or Boolean functions can be described. A Boolean Differential Equation (BDe) is a Boolean equation that includes derivative operations of the Boolean Differential Calculus. This paper aims at the classification of BDEs, the characterization of the respective solutions, algorithms to calculate the solution of a BDe, and selected applications. We will show that not only classes and arbitrary sets of Boolean functions but also lattices of Boolean functions can be expressed by Boolean Differential equations. In order to reach this aim, we give a short introduction into the BDC, emphasize the general difference between the solutions of a Boolean equation and a BDE, explain the core algorithms to solve a BDe that is restricted to all vectorial derivatives of f (x) and optionally contains Boolean variables. We explain formulas for transforming other derivative operations to vectorial derivatives in order to solve more general BDEs. New fields of applications for BDEs are simple and generalized lattices of Boolean functions. We describe the construction, simplification and solution. The basic operations of XBOOLE are sufficient to solve BDEs. We demonstrate how a XBooLe-problem program (PRP) of the freely available XBooLe-Monitor quickly solves some BDes.


Author(s):  
Shatakshi Singh ◽  
Kanika Gautam ◽  
Prachi Singhal ◽  
Sunil Kumar Jangir ◽  
Manish Kumar

The recent development in artificial intelligence is quite astounding in this decade. Especially, machine learning is one of the core subareas of AI. Also, ML field is an incessantly growing along with evolution and becomes a rise in its demand and importance. It transmogrified the way data is extracted, analyzed, and interpreted. Computers are trained to get in a self-training mode so that when new data is fed they can learn, grow, change, and develop themselves without explicit programming. It helps to make useful predictions that can guide better decisions in a real-life situation without human interference. Selection of ML tool is always a challenging task, since choosing an appropriate tool can end up saving time as well as making it faster and easier to provide any solution. This chapter provides a classification of various machine learning tools on the following aspects: for non-programmers, for model deployment, for Computer vision, natural language processing, and audio for reinforcement learning and data mining.


Author(s):  
John H. Doveton

Many years ago, the classification of sedimentary rocks was largely descriptive and relied primarily on petrographic methods for composition and granulometry for particle size. The compositional aspect broadly matches the goals of the previous chapter in estimating mineral content from petrophysical logs. With the development of sedimentology, sedimentary rocks were now considered in terms of the depositional environment in which they originated. Uniformitarianism, the doctrine that the present is the key to the past, linked the formation of sediments in the modern day to their ancient lithified equivalents. Classification was now structured in terms of genesis and formalized in the concept of “facies.” A widely quoted definition of facies was given by Reading (1978) who stated, “A facies should ideally be a distinctive rock that forms under certain conditions of sedimentation reflecting a particular process or environment.” This concept identifies facies as process products which, when lithified in the subsurface, form genetic units that can be correlated with well control to establish the geological architecture of a field. The matching of facies with modern depositional analogs means that dimensional measures, such as shape and lateral extent, can be used to condition reasonable geomodels, particularly when well control is sparse or nonuniform. Most wells are logged rather than cored, so that the identification of facies in cores usually provides only a modicum of information to characterize the architecture of an entire field. Consequently, many studies have been made to predict lithofacies from log measurements in order to augment core observations in the development of a satisfactory geomodel that describes the structure of genetic layers across a field. The term “electrofacies” was introduced by Serra and Abbott (1980) as a way to characterize collective associations of log responses that are linked with geological attributes. They defined electrofacies to be “the set of log responses which characterizes a bed and permits it to be distinguished from the others.” Electrofacies are clearly determined by geology, because physical properties of rocks. The intent of electrofacies identification is generally to match them with lithofacies identified in the core or an outcrop.


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