Design Of Intelligent Wireless Controller System For Oil Well
ABSTRACT
Most oil pumping units (OPUs) have been using manual control in the oilfield. This existing oil- pumping system has a high power-consuming process and has incapability’s of OPU’s structural health monitoring. Due to the environmental conditions and remote locations of oil sites, it is expensive to physically visit for maintenance and repair. This paper develops a sensor network based intelligent control is proposed for power economy and efficient oil well health monitoring. The system consists of several basic sensors such as voltage sensor, level sensor, MEMS sensor, temperature sensor and gas sensor. The sensed data is given to the ARM controller which processes the oil wells data and it is given to the oil pump control unit which controls the process accordingly. If any abnormality is detected then the fault is informed to the maintenance manager. The malfunction is sent as an SMS to the manager’s mobile via GSM for intervention and maintenance.
TABLE OF CONTENTS
COVER PAGE
TITLE PAGE
APPROVAL PAGE
DEDICATION
ACKNOWELDGEMENT
ABSTRACT
CHAPTER ONE
- INTRODUCTION
- BACKGROUND OF THE STUDY
- STATEMENT OF THE PROBLEM
- AIM OF THE RESEARCH
- OBJECTIVES OF THE RESEARCH
- SCOPE OF THE RESEARCH
- SIGNIFICANCE OF THE RESEARCH WORK
CHAPTER TWO
LITERATURE REVIEW
- INTRODUCTION
- OVERVIEW OF OIL WELL AND CONTROL
- OVERVIEW OF WSN
- WSN APPLICATION IN OIL INDUSTRY
- HISTORICAL BACKGROUND OF THE STUDY
- OVERVIEW OF OIL WELL SENSOR
- THE BENEFIT OF REMOTE WELL MONITORING AND CONTROL
- GENERAL REQUIREMENTS FOR WSN
- RELATED WORKS
- PROPOSED SYSTEM
- RESEARCH CHALLENGES
CHAPTER THREE
METHODOLOGY
- INTRODUCTION
- SYSTEM DESCRIPTION
- DEVELOPMENT OF IS
- DEVELOPMENT OF TLS
CHAPTER FOUR
4.0 ASSEMBLY AND EXPERIMENT RESULTS
4.1 DISCUSSION
CHAPTER FIVE
- CONCLUSION
- REFERENCES
Appendix
CHAPTER ONE
1.0 INTRODUCTION
1.1 BACKGROUND OF THE PROJECT
The oil and gas industrial sector is nowadays inclined towards utilizing smart field technologies for optimizing various operations of upstream, midstream and downstream sectors. The recent advances in Internet of things (IoTs) have promising benefits and advantages over manual wired/wireless systems. Oil and gas wells form an important element of upstream sector. After identifying potential viable fields and drilling of exploratory oil and gas wells, wellhead monitoring is another essential and crucial activity not only for safe operation and productivity but also for extending the production life of these wells.
Wireless Sensor Network (WSN) technology provides a faster, less costly, more flexible and more convenient option to the wired sensor systems. The field of WSN has evolved considerably due to engineering advances in Micro- Electro-Mechanical Systems (MEMS) technology which facilitated the development of smart sensors with reduced size, weight and cost. Advances in the field of internet, communications and information technologies have also contributed to development of WSNs. They project that there will be nearly 24 million wireless- enabled sensors and actuators deployed worldwide by 2016 and WSN technology would have a greater influence on applications. Wireless sensor networks consist of large amounts of wireless sensor nodes, which are compact, light-weighted, and battery-powered devices that can be used in virtually any environment.
Due to the energy constraint of individual sensor nodes, energy conservation becomes one of the major issues in sensor networks. In wireless sensor networks, a large portion of the energy in a node is consumed in wireless communications. The amount of energy consumed in a transmission is proportional to the corresponding communication distance. Therefore, long distance communications between nodes and the base station are usually not encouraged. One way to reduce energy consumption in sensor networks is to adopt a clustering algorithm. A clustering algorithm tries to organize sensor nodes into clusters. Within each cluster, one node is elected as the cluster head. The cluster head is responsible for: 1) collecting data from its cluster members; 2) fusing the data by means of data/decision fusion techniques; and 3) reporting the fused data to the remote base station.
This Intelligent well technology is an oil and gas well optimization completion technology integrated with underground real-time monitoring, data analysis decision-making and remote control of downhole tools. The proposed system proactively reports about the anomalous events for predictive maintenance of the well equipment. The detection and reporting catastrophic failures and destructive events on time will increase production downtime and also oil theft can be easily prevented.
1.2 PROBLEM STATEMENT
The existing oil-pumping systems in the oilfield adopts manual control and this manual operation of the oil pumping unit (OPU) have three major problem: 1) The OPU administrators have to frequently go to the oilfield to check the OPU status and collect its health analysis data. For the sake of the harsh oilfield environment, especially in the winter when it is chilly and snowing overspreading the whole oilfield, it is quite difficult to effectively manage and maintain all OPU manually. 2) Power consumption for OPU is huge during the oil-pumping process. Especially in barren oil wells, power wastage is extremely high because each oil-pumping is not filled under such condition and thus oil production greatly drops even though the OPU pumping stroke remains high. And 3), since an administrator has to take charge of a number of oil wells, an OPU malfunction is difficult to locate and repair in a reasonable time, which causes an oil production drop. To overcome these three problems of the existing manual control system, an intelligent wireless network is proposed for OPU management and oil well health monitoring. This system consists of sensors that monitor the oil pumping unit.
1.3 AIM AND OBJECTIVE OF THE STUDY
The main aim of this work is to wirelessly monitor the oil pumping units (OPUs) in the oilfield using sensors and GSM module. The objectives of the study are:
- To ensure safety
- To ensure efficiency
- To increase productivity
- To apply Internet of things (IoTs) in oil pumping units.
1.4 PURPOSE OF THE STUDY
The purpose of the study is for remote oil well health monitoring and automatic oil-pumping control for oil well.
1.5 SCOPE OF THE STUDY
This intelligent system for oil well composes Sensing module contains a temperature sensor, a gas sensor, a voltage sensor, a current sensor, an oil level sensor. This temperature sensor is employed to measure temperature of the oil well. The gas sensor is used to detect the pipeline leaks in the oil well. The voltage sensor and the current sensor are to measure the instantaneous voltage and the current of power supply, respectively. The level sensor will check the level and send the data to the microcontroller based upon the level it ON and OFF pump. GSM module is used for wireless transmission between third level sensor and intelligent sensor. The block diagram of the work is as shown in fig 1 below:
Fig.1. Block diagram of intelligent wireless controller system
1.6 LIMITATION OF THE STUDY
As we all know that no human effort to achieve a set of goals goes without difficulties, certain constraints were encountered in the course of carrying out this project and they are as follows:-
- Difficulty in information collection: I found it too difficult in laying hands of useful information regarding this work and this course me to visit different libraries and internet for solution.
Difficulty in parts gathering: I found it too difficult when gathering electronics parts used for the design.
1.7 RESEARCH METHODOLOGY
In the course of carrying this study, numerous sources were used which most of them are by visiting libraries, consulting journal and news papers and online research which Google was the major source that was used.
1.8 PROJECT ORGANISATION
The work is organized as follows: chapter one discuses the introductory part of the work, chapter two presents the literature review of the study, chapter three describes the methods applied, chapter four discusses the results of the work, chapter five summarizes the research outcomes and the recommendations.
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