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\title{Integrated Rfid Model for Optimal Selection of Drilling Projects}
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             \author[1]{Dr. Maki K.  Rashid}

             \affil[1]{  Sultan Qaboos University}

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\date{\small \em Received: 15 August 2011 Accepted: 14 September 2011 Published: 25 September 2011}

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\begin{abstract}
        


This work presents a model resolving data shortage  problems  when  facing  investment   decisions  in  selecting  drilling  projects  based  on  availability  of  equipments  and  drilling  facilities.   This  is  accomplished  by  enabling  an  environment  for  automatic  information  exchange  using  the  technology of Radio Frequency Identification (RFID) integrated  with assessments  for projects net profit  values.  Incorporating the  information  technology  tools  facilitates  the  components selection and  improves information retrieval efficiency for such missions  especially  during  projects  evaluation  and   drilling operation  phase.  Also,  a  fuzzy  model  is  presented  and convoyed  with  an  optimization   technique  to  take  into consideration  the  risk  of  possible  variation  in  oil  prices  and production cost.  All these components are integrated by using information system design tools. 

\end{abstract}


\keywords{Fuzzy Logic, Intelligent Systems, RFID, Project Managemen}

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\let\tabcellsep& 	 	 		 \par
he industrial obligation of Oil \& Gas organizations to oil supply market produced highly competitive companies with a growing trend towards more renovation successively to attain higher output and easier entrance to worldwide marketplaces. One of the elements in adding more value to a company is by accomplishing faster than others. It is the essence of the innovation process, and, important for many business leaders in today's industries. Appreciating the added value that technology can carry to an organization is fundamental to justify financial investment and ultimately the successful adoption of any emerging technology. Without innovation a company will soon get hit by its competitors. The innovation in Oil \& Gas is often linked with process improvements.\par
In the current business environment, process improvements are often supported by technology or ITinfrastructure \hyperref[b0]{[1]}. To be innovative one does not need to invent a new technology but can use existing technology by various profitable ways. As new technologies are constantly being developed, this provides opportunities for companies to increase efficiency of their processes.\par
In this work innovative know-how like Radio Frequency Identification (RFID) technology is utilized in the selection of drilling projects set based on equipments availability to maximize net profit value. Such methodology is based on assigning resources Author : Mechanical and Industrial Engineering Sultan Qaboos University Muscat, Sultanate of Oman E-mail: maki@squ.edu.om only to those alternatives within a given constraint that ensure greater outcomes.\par
The implementation of Radio Frequency Identification (RFID) in project selection requires techniques for integrating data that relate field requirements to the concept of tracing and pursuing the available drilling string components and other facilities to optimize the selection process of drilling projects. Drilling expenditure includes all costs that are associated with drilling and equipping a well, including surface equipments. This work discusses methods for deploying tactics using RFID technology by deploying a systematic integration of drilling cost with project selection process and field drilling activities. The work proposes an optimization technique for selecting oil well drilling projects integrated with RFID technology by linking available drilling equipments to the assigned geologically detected locations to maximize economic value and assure equipments records for assessment during drilling operations.\par
One of the key elements of project management is the reliable gathering of information. Radio frequency identification (RFID) technique covers the remote gathering of information stored on a tag using wireless communications \hyperref[b1]{[2]}. Such information is arranged in a database for future communication in a network system. In general the RFID system comprises responder (tag), transmitter and antenna or coil. The incorporation of a computer memory chip on the tag posses a limited information storage capacity depending on available memory size. The identification device that combines the transmitter and coil is named reader. The information is read by generating an electromagnetic wave having the capability of reading information seized on a tag fastened to a device or equipment or might have a writing talent of such information. Decentralized information is the key target of the RFID tools by making the data obtainable wherever the device or equipment exist using data handling software as shown in Fig.  {\ref 1}. In the implementation of the RFID technology the aspects of cost, surrounding medium, codes and standards, RFID system preference, database management, system integration and safety should all be taken into consideration. Even though the data are mostly communicated between data bases but one of the main advantages of RFID is its talent reading through harsh surroundings in a reasonable short time as required in T few applications using techniques overcoming wireless communication deficiencies. Over the last years, improvements in RFID technologies, such as increased data storage capabilities, reduced tag prices, and improved robustness of tags, have made RFID-based applications increasingly appealing to a wide range of industries.\par
The drill string components in oil well drilling are exposed to severe loads and heavy wear under ruthless circumstances. It is well known that considerable costs might be associated with the failure of drill pipe during drilling operations. Therefore, a substantial economic advantage can be gained through predictive and preventive maintenance, maximizing operations efficiency, and, a better logistics strategy. The use of RFID technology with database management will improve efficiency and help to find automatically the most suitable piece of the drill string that is necessary for a specific operation by selecting the right components from racks of similar looking pipes. Using attached or embedded RFID tags allows operators, drilling companies, and drilling equipment leasing companies to map out equipment sites \hyperref[b2]{[3]} and record environmental and operation severity that experienced as shown in the layout of Fig.  {\ref 1}. This is done by keeping an electronic record for previous working environments like how long the tools have been used, including temperature, chemicals, pressure and depth of drilling. Such tracking integrated with codes and standards can help tool users to keep away from disasters, such as a tragic drill string failure or breakage underground, or injuries to drilling workers. Also, this technique generates a database to ensure the availability of the proper drilling components to guarantee the efficient use of these components in drilling projects within the required time frame to maximize profit.\par
The operation conditions for the tagged drill string components, i.e. drilling pipes, tools and surface equipments, require RFID tags including antenna and perhaps sensors that are designed to withstand the harsh conditions in oil and gas operations environments to allow both onshore and offshore asset tracking during down hole and subsea drilling operations. The RFID tags are needed to meet and exceed extreme acidity, pressures, and, temperatures typical experienced in oil and gas exploration environments in order to generate a reliable track using database management for the drilling components.\par
RFID tags can also help in achieving high degree of inventory accuracy represented by the degree of consistency between physical and logical inventory. The RFID tag and the automated process for data acquisition should minimize data entry delays and errors, increasing the accuracy and reliability of the information and the ability to plug and play with the existing enterprise resource planning (ERP) systems used by the operators. By using the RFID the human intervention in inventory management can be almost entirely eliminated and accurate levels of inventory are maintained. Furthermore, with RFID it is likely to determine the exact place of the material in the supply chain in real time. Latest advancements in technology have enabled the usage of RFID with tracking devices like GPS to give an accurate pinpoint the location of where inventory is located through the communication with the corresponding databases in the case of masked objects.\par
The traditional available means for selecting a set of oil well drilling projects to maximize profit are not ingrained computer integrated tools. In this work a database management system enhanced by RFID technology is proposed to help clients to choose the optimum available set of equipments to perform well drilling operations. The implemented optimization model takes into consideration the equipment availability, capacities, and, economic value that satisfies the work goals. This can be achieved by recovering and analyzing the available handy information from database saving considerable amount of time and satisfy the economic gain from the resources. The most favorable blend and sequence of recommending projects to achieve the organization overall targets are primarily initiated by determining the existing available equipments. Drilling equipments are the most valuable and most costly resource in this work. Their accessibility is limited and its allocation is an intricate matter. The problem of assigning equipments of various capacities for different drilling projects is discussed in \hyperref[b3]{[4]} Assuming is the equipment requirement of project ( i ) during month ( W ) and is the available equipment of class ( c ), then, the monthly constraints on equipment of class ( c ) at month ( W ) can be written as:\par
The other constrains for the multiple choice can be written as:\par
The NPV for drilling entail drilling cost assessment. Time efficient drilling of an oil well is a matter of expertise and know-how, procedural activities, quality, and, safety restrictions that are all connected to the course of action. Drilling objectives are frequently at discrepancy and depend on interrelated factors that might vary with respect to occasion, place, and personnel. It is a subject of significant market uncertainty. Drilling paces are often controlled by aspects that are not managed competently and lacking data documentation. In many circumstances, the origins of abnormality are multifaceted, occur simultaneously, and being short of effective solutions. Formerly there are diverse methods have been offered to evaluate drilling cost and complexity. Comprehending the drilling process requires isolation of various factors disturbing drilling and to measure their interaction with other factors \hyperref[b4]{[5]}. There are many factors and events pointing in the direction of time and cost for drilling a well. Factors can be classified as either apparent or not visible. The quantifiable issues incorporate the corporal characteristics, geology, and drill constraints of the well, while the unseen factors, such as operator experience and wellbore quality, can be represented by surrogate variables. Issues such as well planning and execution, group harmonization, leadership, and project management talents will also bang drilling achievement. However, there is no way to identify all the characteristics of drilling that might be important, but many characteristics of the process can be observed, and in practice it is necessary to consider only a set of factors that adequately represent drilling conditions \hyperref[b5]{[6]}.\par
The Joint Association Survey (JAS) and, the Mechanical Risk Index (MRI) are accepted techniques used for drilling cost and complexity assessments that founded in 1954 and 1980 respectively. The JAS estimates drilling cost using survey data and quadratic regression models constructed from four descriptor variables (API 2002). The risk index of MRI utilizes six principal variables and fourteen qualitative pointers to differentiate wellbore complexity \hyperref[b6]{[7]}. MRI is not of our concern in this work and the drilling cost (Y) \hyperref[b5]{[6]} is:  (i, j =1,?,5, i < j) are evaluated for each geographic region and only statistically significant variables are maintained in the final model.(2) (3)H M/H M M/L L H M RL R R R M/H M RL R R R M M RL RL R R M/L EL M RL R R L E EL M RL R\par
The Fuzzy concept is intrinsic in many problems of knowledge interpretation, and multifaceted assessment processes often cope with universal concepts and linguistic expressions, which are normally vague in nature. In this work the fuzzy relation that links NPV for drilling project to market oil prices and oil production cost is launched by set up a modifier or multiplier to NPV which can be considered as a risk factor \hyperref[b7]{[8]}. An NPV multiplier is introduced in fuzzy model as a function of two variables. First is the normalized oil prices (NOP) characterized by present oil market price divided by average oil price. Second is the normalized oil production cost (NPC) which stands for oil well production cost divided by the average oil production cost. Average and history of oil prices is discussed in  {\ref [9 \& 10]}. Models for the average production costs that correspond to the addition of all engineering costs related to the discovery, development, and production from oil field divided by the amount of oil that is anticipated to be picked up from the field over its life span as provided by \hyperref[b10]{[11]}. Algorithm based on fuzzy modeling is utilized to extract rules that relate the NPV modifier as output to the inputs represented by the normalized oil prices and the normalized oil production cost. For inputs five linguistic values are used, namely L=''Low'', M/L=''Medium to low'', M=''Medium'', M/H=''Medium to High'' and H=''High''. For output the five linguistic values are: R="Reduce", RL="Reduce Little", Mid="Middle", El="Enlarge Little", E="Enlarge". The algorithm considers each input and output variables to be equally divided by symmetric membership functions of triangular type, and the algorithm uses the tnorm max to select the degree to which two fuzzy sets match. The output of each fuzzy inference system is derived using the standard Zadeh-Mamdani's min-max gravity reasoning method \hyperref[b11]{[12]}. The rules in the fuzzy model have the following form: For the inputs, j) 5 ( B is z THEN A is x and ... A is x and A is x IF : R ) i ( ) i ( m m ) i ( 2 2 ) i ( 1 1 ) i (\par
x will be the normalized oil prices (NOP) and, the normalized oil production cost (NPC) obtained from the price and cost models respectively, and z will be the NPV modifier. Symbols ) i ( j A represent the fuzzy sets, and, ) i ( B are the rules conclusion of the fuzzy system. The inference operation and the defuzzification formula of the fuzzy algorithm are described in various literatures, \hyperref[b11]{[12]} and \hyperref[b12]{[13]}. A number of calculations and fine-tuning are pursued using previous data to obtain the final membership functions and the rule-base for the NPV modifier as given in table 1and Fig. \hyperref[fig_3]{2}. Maximizing the performance of RFID technology in oilfields requires the use of an intelligent technique integrated with a transportable and fixed wireless communications network that enables a dispersed information system as in Fig.  {\ref 3}. Such systems enhance the decision making process by remote selection of oil and gas field data and set a preference to optimize results. In this work ORACLE is used as an information system design tool for data design and correlation as in Fig.  {\ref 4}. Oracle is the most common program in database management.\par
The RFID chips can be prepared and shaped to be attached to various field products. Moving field products into inventory, shifted to different sites, examined, or dispatched, a related RFID as information capturing tool can trace the RFID ID numbers and connect these ID numerals to specific actions executed on that part. The captured information is stored and handled by a set of relational databases. Specifically, four databases are designed for managing the selection process namely drilling project information, cost information, component management, and, field information. These different spots of data storage offer the essential information to force the work progress train to exercise different applications. Updating or retrieving data from database in ORACLE requires interface software to organize the data transaction from database in processing unit. The interface software has identified a set of industry policies and rulings that direct suitable stream of data flow processed by different schemes \hyperref[b5]{(6)} Choosing which drilling projects must be selected from a pool of candidate projects can be a demanding mission. The complexity comes up in addition to the information integration is by restricting the availability of equipments and facilities. Also specifying competing goals of cost minimization and maximizing the net present value of the selected projects. The selection is ended more complex because certain factors, such as costs, and, prices are uncertain. The calculation flow chart for the decision-making process incorporating these parameters is shown in Fig.  {\ref 5}. Showing final calculations will not add new concepts or draw general conclusions that can be used in future work. Each set of projects have their own characteristics and have to be investigated independently but the methodology of evaluation remains unchanged as specified in the flowchart of Fig.  {\ref 5}.\par
By encoding project money assessments and required drilling facilities in an integrated optimization mock-up, a more well-organized distribution of reserves can be accomplished. It is particularly significant under the condition of limited financial resources, facilities, and, insufficient information. Automation reduces the identification and selection time, and decreases manual errors for drilling equipments. The process discussed in this work enables development of an integrated selection process for drilling projects enhanced by the RFID technology. A considerable amount of time for retrieving information is saved since it involves searching and validating from multiple fields and documents. The optimal method of selecting the most profitable oil well drilling projects under limited available resources has been presented using mathematical modeling. Problem formulation lets managers and decision makers to openly include risk elements, such as variations in costs, prices, and, tradeoffs that must be made in funding drilling projects Unification of information system design with operation research and RFID technology in oil well drilling offered opportunities in better resource management activities in term of tracking, optimization, utilization, maintenance, and, operation efficiency.\begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-2.png}
\caption{\label{fig_0}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-3.png}
\caption{\label{fig_1}Where = total well}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-4.png}
\caption{\label{fig_2}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{2}\includegraphics[]{image-5.png}
\caption{\label{fig_3}Fig. 2 :}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-6.png}
\caption{\label{figure6}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{}\includegraphics[]{image-7.png}
\caption{\label{figure7}}\end{figure}
 \begin{figure}[htbp]
\noindent\textbf{1} \par 
\begin{longtable}{}
\end{longtable} \par
 
\caption{\label{tab_0}Table 1 : The rule base for modifier NPC\textbackslash NOP}\end{figure}
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