A Mathematical Model and Inflow Control Effect Analysis of Inflow Control Devices Completed Horizontal Well

2016 ◽  
Vol 139 (3) ◽  
Author(s):  
Yongge Liu ◽  
Huiqing Liu ◽  
Jian Hou ◽  
Qing Wang ◽  
Kai Dong
Keyword(s):  
Mathematical Model ◽  
Production Process ◽  
Horizontal Well ◽  
Control Effect ◽  
Control Efficiency ◽  
Sand Control ◽  
Nozzle Size ◽  
Control Devices ◽  
Gravel Packing ◽  
Dynamic Production

The main purpose of this paper is to analyze and compare the influence of nozzle size, uneven gravel packing, packer leakage, and dynamic production process on the inflow control effect. First, a new mathematical model of Inflow control devices (ICDs) completed horizontal well is proposed which has two new features. One feature is that the annulus between the sand control screen and the formation is considered. Therefore, the influence of uneven gravel packing can be simulated by adjusting the permeability distribution along the annulus. The other feature is that it accounts for packer leakage by introducing a new parameter named “leakage factor” into the model. Then, the inflow control efficiency is defined and used to quantitatively characterize the inflow control effect, and the influences of nozzle size, uneven gravel packing, packer leakage, and dynamic production process on inflow control efficiency are analyzed. The results show that the nozzle size and packer leakage have the biggest influence on the inflow control efficiency, and the influence of gravel packing is negligible unless the permeability of the packed gravel along the wellbore is extremely heterogeneous.

Practical Optimization of Industrial Gravel Size in Gravel Packed Well

2011 ◽  
Vol 201-203 ◽  
pp. 383-387
Author(s):  
Jin Gen Deng ◽  
Yu Chen ◽  
Li Hua Wang ◽  
Wen Long Zhao ◽  
Ping Li
Keyword(s):  
Design Method ◽  
Control Measures ◽  
Control Effect ◽  
Gravel Layer ◽  
Gravel Size ◽  
Sand Control ◽  
Gravel Packing ◽  
Gravel Pack ◽  
The Impact ◽  
Computing Method

In the design of gravel packing sand control, the reasonable selection of gravel size is one of the keys to implementing sand control measures successfully. Aiming at the defects of commonly used methods of gravel size design and the characteristic that the gravel used in field operation is actually a mixture of gravel with multiple grain diameters, this paper builds a model of pore structure in gravel layer through researching the gravel pack structure caused by the gravel of two grain diameters mixed under actual packing conditions, calculates and analyzes the pore sizes in gravel layer. Ultimately, based on Saucier method, this paper presents a new gravel size optimization idea for gravel packing sand control with multiple grain diameters mixed, which agrees with the actual situation of industrial gravel, and gives the idea’s computing method. Considering the ideality of the model in this paper, the author has modified the computing method to make it more fit for the actual packing situation. This gravel size design method also gives consideration to the impact of formation sand uniformity on sand control effect, so it have the characteristics of good practicability, wide applicability and more accurate than other conventional methods.

Extended Reach Horizontal Well Development with Downhole Flow Control and Gravel Packing Sand Control: First Pilot in S-Field with Production Success

2018 ◽  
Author(s):  
Dahlila Kamat ◽  
Zairi Kadir ◽  
Prashanth Nair Kumaran ◽  
Ramli Ibrahim ◽  
Mior Yusni Ahmad ◽  
...  
Keyword(s):  
Flow Control ◽  
Horizontal Well ◽  
Sand Control ◽  
Production Success ◽  
Well Development ◽  
Gravel Packing

scholarly journals Reflection of documents in the digital twin of the company and calculation of their impact on human behavior in the simulation model

E-Management ◽  
2021 ◽  
Vol 4 (3) ◽  
pp. 50-60
Author(s):  
M. V. Samosudov
Keyword(s):  
Mathematical Model ◽  
Social System ◽  
Social Systems ◽  
Control Effect ◽  
Economic Space ◽  
Agent Based ◽  
Digital Twin ◽  
The Social ◽  
The Impact ◽  
System Operating

The formation and formation of the Industry 4.0 concept stimulated the discussion of the use of computer technology in various areas of economic activity and, in particular, in the automation of social systems management. The basis of the concept is the inclusion of a virtual image of the social system in the form of a mathematical model or a digital twin of the enterprise in the production and management system. At the same time, it should be noted that today digital twin are created mainly only for technical objects used in the activities of enterprises. The purpose of the article is to demonstrate the possibility of fixing organizational documents as one of the system-forming factors in the digital twin of an enterprise. This circumstance makes it possible, firstly, to more accurately calculate the managerial effects of managers by taking into account the impact of organizational documents on the activities of employees of the enterprise; secondly, to identify conflicts of documents developed by various departments of the company; thirdly, to calculate the content of documents during their development (design), based on the requirements of the situation or a given control effect. This possibility arises due to the use of a comprehensive mathematical model of the social system operating in an active environment. The model is a simulation agent-based model and allows you to calculate the dynamics of the social system in the socio-economic space, which allows its use in decision support systems by managers of any scale and activities to calculate the expected effect of management decisions – the specifics of a particular social system are taken into account by combining the values of the phase variables describing the state of the enterprise. The novelty of the research paper lies in the fact that it shows: the possibility to calculate the influence of organizational documents on the behavior of participants and, consequently, on the result of the social system, as well as the mechanism for converting messages, which are invariants of socio-economic space into information that affects the behavior of participants of relations.

An economic production model with imperfect quality components and probabilistic lead times

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Abdul-Nasser El-Kassar ◽  
Alessio Ishizaka ◽  
Yama Temouri ◽  
Abdullah Al Sagheer ◽  
Daicy Vaz
Keyword(s):  
Mathematical Model ◽  
Production Process ◽  
Production Cycle ◽  
Lead Times ◽  
Screening Process ◽  
Content Type ◽  
Imperfect Quality ◽  
Reorder Point ◽  
Production Run ◽  
Practical Implications

PurposeThis study investigates a production process that requires N kinds of components for the production of a finished product. The producer orders the various kinds of components from different suppliers and receives the orders in lots at the beginning of each production cycle. Similar to situations often encountered in real life, the lead times are random variables with known probability distributions so that a production cycle starts whenever all N kinds of components become available. Each of the lots received at the start of a production run contains both perfect and imperfect quality components. Once all N kinds of components become available, the producer initiates a screening process to detect the imperfect components. The production of the finished product uses only perfect quality components. The imperfect components are removed from inventory whenever the screening process is completed. The percentage of components of perfect quality present in each lot is a random variable with a known probability distribution.Design/methodology/approachThis production process is described and modeled mathematically and the optimal production/ordering policy is derived based on the mathematical model.FindingsThe formulated mathematical model resulted in the determination of the optimal policy consisting of the optimal number of finished items ordered to be produce during each production run, the number of components ordered from each supplier, and the reorder point. The derived closed form expression for the optimal lot size depends on the minimum of the number of perfect quality components in a lot, whereas the reorder point is determined based on the maximum lead time.Practical implicationsThe modeling approach and results of this study provide practical implications that may be beneficial to both production and supply chain managers as well as researchers.Originality/valueThis modeling approach that incorporates decision-making related to the logistics of acquiring the components and accounts for the probabilistic nature of the lead times and quality of components addresses a gap in the logistics/production literature.

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