No description available.

During the reservoir production life reservoir pressure will decline. Also after water breakthrough the fluid column weight will increase as hydrostatic pressure will increase because of increased water and oil mixture density. In this case, reservoir pressure may not be enough to lift up the fluid from bottom to the surface. These reasons decrease or even may cause to stop flowing of fluids from the well. Some techniques must be applied to prevent the production decline. Artificial lift techniques are applied to add energy to the produced fluids. It increases production rate by reducing down-hole pressure and so that by increasing the drawdown. Artificial lift techniques increase production either by pumping the produced fluid from the bottom to the surface or reduce bottom-hole pressure by reducing the fluid column weight as a result of decreased fluid mixture density. Artificial lift is used worldwide in approximately 85% of the wells, thus its impact in overall efficiency and profitability of production operations cannot be overemphasized. The most important problem is how to select optimum artificial lift techniques by taking into consideration the reservoir, well, environmental conditions. Selection of poor technique could cause decrease in efficiency and low profitability. As a result, it will lead to high operating expenses. Several techniques have been developed for selection of optimum artificial lift techniques. Expert Systems (ES) is the most suitable technique used in these selection techniques. Because the use and availability of required parameters is easy. Also in this selection method most of the artificial lift techniques are analyzed rather than other selection techniques. Expert Systems program mainly consist of three modules: (1) Expert Module, (2) Design Module, and (3) Economic Module. By entering required data to the system, program automatically suggests the feasible artificial lift techniques those might be used referring to given data. In this thesis work the artificial lift selection criteria and Expert Systems available in the literature have been studied. A Microsoft Windows based program has been developed to predict suitability of artificial lift methods for a given set of wells and produced fluid parameters. For the selected artificial lift method (i.e. sucker rod pump, ESP, gas lift, hydraulic pump, PCP) the program is able to perform basic calculations for the given data. Different case studies have been performed by running the program with actual data from fields. Well data of Venezuela, Azerbaijan and Iranian oil fields has been used in case studies. The results have been compared with previous studies those have been done on these fields with other selection techniques and current artificial lift techniques are being applied in selected wells. The obtained program results have been overlap with current real field application and previous studies.

Business Process (BP) design reflects managerial needs and may directly influence business performance. A good design could substantially increase managerial performance, while a bad one would be inefficient, lack of flexibility, mess cost effective and eventually miss the business strategy. The widespread of information technology has raised the need to redesign or modify business processes in order to fit the trend of automation and computerization. As a result, business process reengineering (BPR) has gained much attention in 1990s. In recent years, a new paradigm, called Service Science, Management and Engineering (SSME), becomes a new management innovation. Service process design becomes a new science that can be applied to support service innovation and management. Previous research on BPR includes two major directions: one focuses on managerial aspects of business processes, including the planning, implementation, and critical factors of BPR; the other focuses on the design aspects pf business processes with a target of making processes more efficient. For research on process design, most deal with the syntactic structure of the process. They analyze the syntax structure of a process. This can help find design errors such as deadlocks, livelocks, and even infinite loops in a process. Not many studies have investigated whether a process design meets its managerial goals. This research presents a knowledge-based approach to dealing with the managerial issue of whether a process design matches specific managerial goals. This thesis contains a new business process modeling method that allows a business process to be diagnosed by knowledge-based rules. We have defined three managerial goals in process design: effectiveness, efficiency, and flexibility. Each activity in a business process has its goal. Through the analysis of activities and their associated goals, we can determine whether a business process is properly designed. In order to show the feasibility of the proposed approach, we have implemented a JAVA-based prototype expert system and used it to check two sample business processes. The contributions of the study are two-fold. Academically, it proposed a new approach for business process diagnosis, which can help determine whether a process meets its managerial goal. In practice, businesses can use the concepts developed in the thesis to make their business processes more effective by matching activities with intended managerial goals.

Evaluation of contaminated sites based on human health and environmental hazards is an essential task for the proper management of the contaminated sites. A large number of contaminated sites have been waiting for remediation all over the World. However, contaminated site remediation is generally a difficult, time consuming and very expensive process. Ranking systems for contaminated sites are useful tools to determine the remedial priority and to manage the available remediation budget in the most efficient way before the costly remedial actions are taken. To be able to have a reliable ranking result, accurate and sufficient amount of data on the nature of contamination and site characteristics are needed, which are usually not available at the early identification phases of contaminated sites, and the available data is mostly limited and vague in nature. If the available data are inaccurate or vague, the corresponding remedial ranking results can be questionable, as well. Most of the current ranking methodologies overlook the vagueness in the parameter values. The main objective of this study is to develop a remedial priority ranking system for contaminated sites by taking vagueness in parameter values into account. Within this context, development of the new Remedial Priority Ranking System, RPRS, aims to define and evaluate the current and possible environmental risks by using sufficiently comprehensive readily available parameters describing the fate and transport of contaminants in the environment and considering vagueness in those parameter values. The consideration of vagueness in parameter values was included in remedial prioritization of contaminated sites by means of fuzzy set theory. A fuzzy expert system was built up for the evaluation of contaminated sites and it was developed in Microsoft Office Excel 2007 platform, with the intention of making the evaluation fast and user friendly. Hypothetical and real case study applications are presented to test ease of use and validity of the results of the developed methodology. Results of case study applications revealed that the developed RPRS can serve as an alternative method for remedial priority ranking of contaminated sites.

No description available.

This research consists of two main parts: development of a rock expert system (RES) as an easy-to-use and effective tool for evaluating rock properties, and modification and utilization of the three-dimensional Particle Flow Code (PFC3D) to analyze rock behavior. Because of different reasons, it is often difficult to obtain the rock property values directly. As an alternative, typical values and empirical correlations are often used to evaluate the rock property values. However, the typical values and empirical correlations come in various forms and are scattered in different sources. It is often difficult, time-consuming or even impossible for an engineer to find appropriate information to estimate the required rock properties. So in the first part of the research, the RES was developed as an easy-to-use and effective tool for evaluating rock properties by conducting detailed review and evaluation of well determined values and empirical correlations of rock properties in the published literature, and developing a central database and data application tools. The study of RES demonstrates the storage of rock property values and correlations is strongly applicable and the web based data application tool is effective to use and easy expandable. Considering its granular nature, the discrete element method (DEM) has been widely adopted to analyze the mechanical behavior of rock. The Particle Flow Code (PFC) is one of the most popular DEM softwares. The basic idea of PFC is to treat rock as an assembly of bonded particles that follow the law of motion and consider the model behavior dominated by the formation and interaction of micro cracks developed within the particle-particle cement (bond). Unlike the continuum methods, PFC can deal with the natural process from micro cracking to macro failure, without predefining a failure criterion for the rock. However, there are still issues related to the application of PFC to analyze different rock problems. For example, so far, most of the studies use PFC2D although many of the problems are three dimensional and should be better simulated with PFC3D. It is also found that the simulations using the default PFC parallel bond model extremely underestimate the ratio of unconfined compressive strength to tensile strength (UCS/T). So in the second part of the research, the important aspects related to the application of PFC3D, including model scale, particle size distribution and contact model, were studied, a new contact model was developed for addressing the limitation of the default PFC3D on obtaining unrealistically low UCS/T ratios, and finally the new contact model was used to investigate rock fracture initiation and propagation.

Approved for public release; distribution is unlimited / Unmanned vehicle technology has matured significantly over the last two decades. This is evidenced by its widespread use in industrial and military applications ranging from deep-ocean exploration to anti-submarine warefare. Indeed, the feasiblity of short-range, special-purpose vehicles (whether aunonomous or remotely operated) is no longer in question. The research efforts have now begun to shift their focus on development of reliable, longer-range, high-endurance and fully autonomous systems. One of the major underlying technologies required to realize this goal is Artificial Intelligence (AI). The latter offers great potential to endow vehicles with the intelligence needed for full autonomy and extended range capability; this involves the increased application of AI technologies to support mission planning and execution, navigation and contingency planning. This thesis addresses two issues associated with the above goal for Autonomous Underwater Vehicles (AUV's). Firstly, a new approach is proposed for path planning in underwater environments that is capable of dealing with uncharted obstacles and which requires significantly less planning time and computer memory. Secondly, it explores the use of expert system technology in the planning of AUV missions.

This thesis draws on techniques from Management Science and Artificial Intelligence to explore organisational aspects of asset management in electricity transmission enterprises. In this research, factors that influence policies and practices of asset management within electricity transmission enterprises have been identified, in order to examine their interaction and how they impact the policies, practices and performance of transmission businesses. It has been found that, while there is extensive literature on the economics of transmission regulation and pricing, there is little published research linking the engineering and financial aspects of transmission asset management at a management policy level. To remedy this situation, this investigation has drawn on a wide range of literature, together with expert interviews and personal knowledge of the electricity industry, to construct a conceptual model of asset management with broad applicability across transmission enterprises in different parts of the world. A concise representation of the model has been formulated using a Causal Loop Diagram (CLD). To investigate the interactions between factors of influence it is necessary to implement the model and validate it against known outcomes. However, because of the nature of the data (a mix of numeric and non-numeric data, imprecise, incomplete and often approximate) and complexity and imprecision in the definition of relationships between elements, this problem is intractable to modelling by traditional engineering methodologies. The solution has been to utilise techniques from other disciplines. Two implementations have been explored: a multi-level fuzzy rule-based model and a system dynamics model; they offer different but complementary insights into transmission asset management. Each model shows potential for use by transmission businesses for strategic-level decision support. The research demonstrates the key impact of routine maintenance effectiveness on the condition and performance of transmission system assets. However, performance of the transmission network, is not only related to equipment performance, but is a function of system design and operational aspects, such as loading and load factor. Type and supportiveness of regulation, together with the objectives and corporate culture of the transmission organisation also play roles in promoting various strategies for asset management. The cumulative effect of all these drivers is to produce differences in asset management policies and practices, discernable between individual companies and at a regional level, where similar conditions have applied historically and today.

<p>E-business provides important opportunities of trade for businesses, and the supporting business system must handle this environment efficiently. One current trend in business systems is to move business logic, such as business processes and business rules, out from the application logic and into separate support systems. The reason to make this separation is to increase the agility of the business, to make the system able to change more rapidly when the business situation changes.</p><p>This report focus on business rules enforced in business rule engines. Specific interest is on how such rule engines meet the requirements of the e-business domain. The report presents an overview of business rule engines. Five general categories of characteristics are proposed. The proposed characteristics are then used in a comparison of three business rule engines.</p>

Σκοπός της παρούσας εργασίας ήταν η δημιουργία ενός ευφυούς συστήματος για τη διάγνωση νοσημάτων του προστάτη αδένα με βάση σημεία και συμπτώματα που διαπιστώνονται σε έναν ασθενή όπως καταγράφονται κατά την κλινική του εξέταση. Τα βασικά σημεία της εργασίας είναι τα εξής: αρχικά παράγεται το μοντέλο της διαγνωστικής στρατηγικής που ακολουθείται για τη διάγνωση των συγκεκριμένων παθήσεων και στη συνέχεια γίνεται εκμαίευση της διαγνωστικής γνώσης από ειδικούς ή/και από εμπειρικά δεδομένα. Η διαδικασία και η γνώση αναπαρίστανται με χρήση υβριδικών μεθόδων αναπαράστασης και με τη χρήση ασάφειας ή/και αβεβαιότητας, η οποία είναι εγγενής σε τέτοια διαγνωστικά συστήματα. Το σύστημα αναπτύχθηκε με τέτοια εργαλεία που δίνουν την δυνατότητα στέγασής του σε ιστότοπο ώστε να χρησιμοποιηθεί ως ειδικός συμβουλευτικός οδηγός από ενδιαφερομένους μη ειδικούς ιατρούς & από ασθενείς καθώς και από φοιτητές υγειονομικών σχολών για εκπαιδευτική χρήση. Το σύστημα περιέχει γνώση εμπειρογνωμόνων σε συνδυασμό με στοιχεία πλούσιας βιβλιογραφικής αναζήτησης και μελέτης. Τέλος πραγματοποιήθηκε επικύρωση των αποτελεσμάτων μέσα από μια τυχαιοποιημένη κλινική έρευνα. Η υλοποίηση του συστήματος μας στηρίζεται σε ένα ειδικό κέλυφος δημιουργίας ευφυών συστημάτων και σε εργαλεία μεθόδων μηχανικής μάθησης. Επίσης, υλοποιούνται δύο εκδοχές (Hirofilos Ι & ΙΙ) και γίνεται σύγκριση των απο-τελεσμάτων. Αναγνωρίστηκε η σαφής υπεροχή του Hirofilos ΙΙ που αναπτυχθηκε με σύστημα μηχανικής εκμάθησης και με δυνατότητα διαχρονικής αναβάθμισης. / During making this project our concern was the creation of a new expert system for diagnosis prostate disease depending on the clinical status of a patient as these are identified during medical examination. The main points were as follows: First has been constructed a diagnosis process model which was followed by the diagnosis for the most common prostate diseases. Secondly was implemented extracting of the medical knowledge based on specialists or/and experimental data. The whole process and the medical Knowledge will be developed using hybrid methods of representation and having the partcipation of such saying fuzziness or inaccuracy, that is innate in that kind of intelligent decision-support. The new intelligent system is already accommodated on a hospital server and is used as a decision-support system, as well as an e-learning platform for medical students. For the implementation of the new system have been used an expert system shell and knowledge engineering tools.