Drilling Problems Forecast Based on Neural Network

2021 ◽  
Author(s):  
Sergey Olegovich Borozdin ◽  
Anatoly Nikolaevich Dmitrievsky ◽  
Nikolai Alexandrovich Eremin ◽  
Alexey Igorevich Arkhipov ◽  
Alexander Georgievich Sboev ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
High Performance ◽  
Oil And Gas ◽  
Forecast Accuracy ◽  
Distributed Data ◽  
Technological Parameters ◽  
Well Drilling ◽  
Artificial Intelligence Methods ◽  
Data Objects ◽  
Mud Loss

Abstract This paper poses and solves the problem of using artificial intelligence methods for processing big volumes of geodata from geological and technological measurement stations in order to identify and predict complications during well drilling. Big volumes of geodata from the stations of geological and technological measurements during drilling varied from units to tens of terabytes. Digital modernization of the life cycle of well construction using machine learning methods contributes to improving the efficiency of drilling oil and gas wells. The clustering of big volumes of geodata from various sources and types of sensors used to measure parameters during drilling has been carried out. In the process of creating, training and applying software components with artificial neural networks, the specified accuracy of calculations was achieved, hidden and non-obvious patterns were revealed in big volumes of geological, geophysical, technical and technological parameters. To predict the operational results of drilling wells, classification models were developed using artificial intelligence methods. The use of a high-performance computing cluster significantly reduced the time spent on assessing the probability of complications and predicting these probabilities for 7-10 minutes ahead. A hierarchical distributed data warehouse has been formed, containing real-time drilling data in WITSML format using the SQL server (Microsoft). The module for preprocessing and uploading geodata to the WITSML repository uses the Energistics Standards DevKit API and Energistic data objects to work with geodata in the WITSML format. Drilling problems forecast accuracy which has been reached with developed system may significantly reduce non-productive time spent on eliminating of stuck pipe, mud loss and oil and gas influx events.

scholarly journals Application of artificial intelligence methods for identifying and predicting complications in the construction of oil and gas wells: problems and solutions

Georesursy ◽  
2020 ◽  
Vol 22 (3) ◽  
pp. 87-96
Author(s):  
Alexander D. Chernikov ◽  
Nikolay A. Eremin ◽  
Vladimir E. Stolyarov ◽  
Alexander G. Sboev ◽  
Olga K. Semenova-Chashchina ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Oil And Gas ◽  
Multidimensional Data ◽  
Technological Parameters ◽  
Gas Wells ◽  
Well Drilling ◽  
Artificial Intelligence Methods ◽  
Oil And Gas Wells ◽  
Problems And Solutions ◽  
And Training

This paper poses and solves the problem of using artificial intelligence methods for processing large volumes of geodata from geological and technological measurement stations in order to identify and predict complications during well drilling. Digital modernization of the life cycle of wells using artificial intelligence methods, in particular, helps to improve the efficiency of drilling oil and gas wells. In the course of creating and training artificial neural networks, regularities were modeled with a given accuracy, hidden relationships between geological and geophysical, technical and technological parameters were revealed. The clustering of multidimensional data volumes from various types of sensors used to measure parameters during well drilling has been carried out. Artificial intelligence classification models have been developed to predict the operational results of the well construction. The analysis of these issues is carried out, and the main directions for their solution are determined.

USING ARTIFICIAL INTELLIGENCE METHODS TO PREVENT COMPLICATIONS IN WELL CONSTRUCTION

2021 ◽  
Vol 4 (1) ◽  
pp. 132-144
Author(s):  
A.N. Dmitrievsky ◽  
◽  
N.A. Eremin ◽  
A.D. Chernikov ◽  
L.I. Zinatullina ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Oil And Gas ◽  
Automated Systems ◽  
Emergency Situations ◽  
Machine Learning Methods ◽  
Artificial Intelligence Methods ◽  
Well Field ◽  
Oil Water ◽  
Model Oil ◽  
Productive Time

The article discusses the use of automated systems for preventing emergency situa-tions in the process of well construction using artificial intelligence methods to increase the productive time of well construction by reducing the loss of working time to eliminate compli-cations. Key words: problems and complications during drilling, emissions, gas and oil water showings, stuck, artificial neural networks, digitalization, drilling, well, field, oil and gas blockchain, artificial intelligence, machine learning methods, geological and technological research, neural network model, oil and gas construction wells, identification and forecasting of complications, prevention of emergency situations.

scholarly journals Problems of weld overlay of seating surfaces of pipe fitting and solutions

2020 ◽  
Vol 19 (4) ◽  
pp. 349-356
Author(s):  
S. S. Poloskov
Keyword(s):  
High Performance ◽  
Oil And Gas ◽  
Quality Parameters ◽  
Operating Conditions ◽  
Consumable Electrode ◽  
High Tech ◽  
Technological Parameters ◽  
Pipe Fitting ◽  
Weld Overlay ◽  
Advantages And Disadvantages

Introduction. A problem of providing the necessary functions of pipe fitting for blockage, control, distribution of the working medium flows under the most adverse operating conditions of oil and gas pipelines associated with abrasive particles, mechanical impurities, hydrogen sulfide, carbon dioxide and organic acids with sulfate-reducing bacteria, is considered.Materials and Methods. High performance properties of seating surfaces of pipe fittings are provided through anticorrosive plating of alloyed and high-alloyed metals based on iron with the addition of chromium, nickel, cobalt and niobium. The basic weld overlay methods are analyzed: metalarc welding, nonconsumable and consumable-electrode weld facing in shielding gases, submerged arc surfacing. Advantages and disadvantages of surfacing methods implemented in recent years are noted: laser, plasma-powder and plasma-arc methods.Research Results. Taking into account the automation capabilities, a high-tech process of robotic anticorrosive surfacing using a consumable electrode with an additional filler metal feed to the front welding puddle for shielding the thermal effect of the arc, is proposed. Industrial application of the proposed technology requires a set of studies related to assessing the effect of technological parameters on the quality of the deposited layers to provide the required operational characteristics of the fitting.Discussion and Conclusion. It is proposed to carry out the above studies using physical and mathematical modeling of the anticorrosive surfacing, which reduces the time and number of experiments. Therefore, the primary task is to develop a mathematical model of the surfacing process with a consumable electrode with an additional filler wire and transverse vibrations of the welding burner. Such a model should virtually reproduce the surfacing process, as well as its thermal cycle followed by calculating the ratio of the structural components of the deposited metal and the substrate metal. The system of equations of the model should be solved by a special computer program. The algorithm presented for solving this class of problems will allow us to make a sound connection of the technological parameters of the surfacing process and the quality parameters of the formation of the deposited layers, to determine the program for their optimization to provide the required operational properties of pipeline fitting.

scholarly journals HETEROGENEO-CATALYTIC SYNTHESIS OF VINYL CHLORIDE AND CHLOROPRENE FROM ACETYLENE

2020 ◽  
Vol 5 (443) ◽  
pp. 6-13
Author(s):  
Akmalaiuly K., ◽  
◽  
Fayzullayev N., ◽  
◽  
◽  
...  
Keyword(s):  
Vinyl Chloride ◽  
High Performance ◽  
Reaction Rate ◽  
Oil And Gas ◽  
Catalyst Concentration ◽  
Raw Materials ◽  
Technological Parameters ◽  
Successful Development ◽  
The Cost ◽  
Process Productivity

For the catalytic hydro chlorination of acetylene in the vapor phase based on local raw materials for the Zola-gel technology, we selected an active and high-performance catalyst (ZnCl2)x*(FeCl3)y*(CuCl2)z and also under the influence of various factors (partial pressure, temperature, ratio of reagent properties, contact time, catalyst concentration) the yield and reaction rate were studied with the participation of the selected catalyst. Based on the results obtained, a kinetic equation was proposed that satisfies the reaction, its adequacy is estimated, and a scheme of the reaction mechanism and the basis on the kinetic model are proposed. Because of studying the influence of the mass transfer coefficient on the process productivity and the influence of other factors, the technological parameters of the catalytic flocculants of vinyl chloride and the chloroprene extraction reactor of acetylene were calculated and the main indicators of the compatibility of technological capabilities of environmental and economic factors were substantiated. The successful development of the production of VC from ethylene was associated with the search for a cheaper hydrocarbon feed than acetylene. Analysis of the structure of the cost price of VC obtained by various methods shows that the acetylene method gives the highest cost, with acetylene accounting for about 90%. However, the world hydrocarbon price environment is constantly changing. In the future, it is possible to increase prices for oil and gas raw materials, the convergence of prices for acetylene and ethylene, and the latter may lose its main advantage in this regard.

МЕТОДЫ ДОСТИЖЕНИЯ МАКСИМАЛЬНОЙ ЭФФЕКТИВНОСТИ ПЛАТФОРМЫ ПРОТОТИПИРОВАНИЯ ВЫСОКОПРОИЗВОДИТЕЛЬНЫХ СИСТЕМ НА КРИСТАЛЛЕ НА ЗАДАЧАХ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

2020 ◽  
Vol 96 (3s) ◽  
pp. 585-588
Author(s):  
С.Е. Фролова ◽  
Е.С. Янакова
Keyword(s):  
Neural Network ◽  
Artificial Intelligence ◽  
Computer Vision ◽  
High Performance ◽  
Systems On Chip ◽  
High Performance Systems ◽  
On Chip ◽  
Network Technologies ◽  
Neural Network Technologies

Предлагаются методы построения платформ прототипирования высокопроизводительных систем на кристалле для задач искусственного интеллекта. Изложены требования к платформам подобного класса и принципы изменения проекта СнК для имплементации в прототип. Рассматриваются методы отладки проектов на платформе прототипирования. Приведены результаты работ алгоритмов компьютерного зрения с использованием нейросетевых технологий на FPGA-прототипе семантических ядер ELcore. Methods have been proposed for building prototyping platforms for high-performance systems-on-chip for artificial intelligence tasks. The requirements for platforms of this class and the principles for changing the design of the SoC for implementation in the prototype have been described as well as methods of debugging projects on the prototyping platform. The results of the work of computer vision algorithms using neural network technologies on the FPGA prototype of the ELcore semantic cores have been presented.

Application of artificial intelligence methods for monsoonal river classification in Selangor river basin, Malaysia

2021 ◽  
Vol 193 (7) ◽  
Author(s):  
Yong Jie Wong ◽  
Yoshihisa Shimizu ◽  
Akinori Kamiya ◽  
Luksanaree Maneechot ◽  
Khagendra Pralhad Bharambe ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
River Basin ◽  
River Classification ◽  
Artificial Intelligence Methods
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