Unconventional reservoir systems can best be described as petroleum (oil and/or gas) accumulations which are difficult to be characterized and produced by conventional technologies. In this work we present the development of a systematic procedure to evaluate well performance in unconventional (i.e., low to ultra-low permeability) reservoir systems. The specific tasks achieved in this work include the following: ● Integrated Diagnostics and Analysis of Production Data in Unconventional Reservoirs: We identify the challenges and common pitfalls of production analysis and provide guidelines for the analysis of production data. We provide a comprehensive workflow which consists of model-based production analysis (i.e., rate-transient or model matching approaches) complemented by traditional decline curve analysis to estimate reserves in unconventional reservoirs. In particular, we use analytical solutions (e.g., elliptical flow, horizontal well with multiple fractures solution, etc.) which are applicable to wells produced in unconventional reservoirs. ● Deconvolution: We propose to use deconvolution to identify the correlation between pressure and rate data. For our purposes we modify the B-spline deconvolution algorithm to obtain the constantpressure rate solution using cumulative production and bottomhole pressure data in real time domain. It is shown that constant-pressure rate and constant-rate pressure solutions obtained by deconvolution could identify the correlation between measured rate and pressure data when used in conjunction. ● Series of Rate-Time Relations: We develop three new main rate-time relations and five supplementary rate-time relations which utilize power-law, hyperbolic, stretched exponential, and exponential components to properly model the behavior of a given set of rate-time data. These relations are well-suited for the estimation of ultimate recovery as well as for extrapolating production into the future. While our proposed models can be used for any system, we provide application almost exclusively for wells completed in unconventional reservoirs as a means of providing estimates of time-dependent reserves. We attempt to correlate the rate-time relation model parameters versus model-based production analysis results. As example applications, we present a variety of field examples using production data acquired from tight gas, shale gas reservoir systems.

New elastographic techniques such as poroelastography and viscoelasticity imaging aim at imaging the temporal mechanical behavior of tissues. These techniques usually involve the use of curve fitting methods as applied to noisy data to estimate new elastographic parameters. As of today, however, image quality performance of these new elastographic imaging techniques is still largely unknown due to a paucity of data and the lack of systematic studies that analyze performance limitations of estimators suitable for these novel applications. Furthermore, current elastographic implementations of poroelasticity and viscoelasticity imaging methods are in general too slow and not optimized for clinical applications. In this paper, we propose a new elastographic time constant (TC) estimator, which is based on the use of the Least Square Error (LSE) curve-fitting method and the Levenberg-Marquardt (LM) optimization rule as applied to noisy elastographic data obtained from a tissue under creep compression. The estimator's performance is analyzed using simulations and quantified in terms of accuracy, precision, sensitivity, signal-to-noise ratio (SNR) and speed. Experiments are performed as a proof of principle of the technical applicability of the new estimator on real experimental data. The results of this study demonstrate that the new elastographic estimator described in this thesis can produce highly accurate, sensitive and precise time constant estimates in real-time and at high SNR. In the future, the use of this estimator could allow real-time imaging of the temporal behavior of complex tissues and provide advances in lymphedema and cancer imaging.

With increase of interest in exploiting shale gas/oil reservoirs with multiple stage fractured horizontal wells, complexity of production analysis and reservoir description have also increased. Different methods and models were used throughout the years to analyze these wells, such as using analytical solutions and simulation techniques. The analytical methods are more popular because they are faster and more accurate. The main objective of this paper is to present and demonstrate type curves for production data analysis of shale gas/oil wells using a Dual Porosity model. Production data of horizontally drilled shale gas/oil wells have been matched with developed type curves which vary with effective parameters. Once a good match is obtained, the well dual porosity parameters can be calculated. A computer program was developed for more simplified matching process and more accurate results. As an objective of this thesis, a type curve analytical method was presented with its application to field data. The results show a good match with the synthetic and field cases. The calculated parameters are close to those used on the synthetic models and field cases.

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Eddy current testing is a non-destructive testing method that has usually used for examination of carbon steel tubes. By using a high frequency electromagnetic field on the exciting probe, it is easy to figure out the impedance variation of the coil on impedance plane, and estimate the crack depth by measuring the angle of curve. However, different kind of tubes and electromagnetic properties resulted in different testing. The purpose of this study is to create the two dimensional axial symmetry model of eddy current testing by finite element software package FEMLAB. And it is easy to estimate the crack depth by figuring the impedance plane and evaluation curves by MATLAB. Furthermore, the research analyzed the variation of curves and angles on an impedance plane and tried to reduce testing errors. Over all, the analysis of some influence factors of eddy current testing in the present study not only provides a standard of estimating crack depth more accurately, but also reduces the evaluation errors.

The feature of group buying is that the price will go down as the accumulated orders are increasing. However, consumers will not know the final price until the end. As a result, consumers can only make decision based on the final price forecast of group buying. The final price forecast might be different depending on different pricing strategies of group-buying models and if there are competitions from posted-price stores. The purpose of this research is to understand how consumers¡¦ internal reference price and final price prediction of group buying would be influenced when facing different price curves in different market competition environment. The difference between the internal reference price and final price prediction of group-buying indicates the consumers¡¦ transaction utility. In addition, if consumers¡¦ perceived transaction utilities affect their intentions and behavior of joining group buying is another research purpose. In this research, there are three different pricing strategies, decreasing, neutral, and increasing based on the initial price, discount size and final price. For the market competition environment, it manipulated by if there are other posted-price stores to be chosen or not. The research result indicates that increasing price curve, which has higher final price, make consumers¡¦ final price prediction of group buying higher than the others under the best condition. On the other hand, it indicates that decreasing price curve, which has higher initial price, make consumers¡¦ final price prediction of group buying higher than the others under the worst condition. Consumers¡¦ internal reference prices are mainly influenced by market price information. When there are other posted-price stores to be chosen, consumers¡¦ internal reference price are higher averagely. In addition, the higher consumers¡¦ perceived transaction utilities are, the higher consumers¡¦ intentions to join group buying are. Finally, it shows consumers¡¦ intentions to join group buying have significant effect on their actual behavior.

The disadvantage of FDTD method is that it needs a long simulation time, and it is difficult to simulate a complex circuit. The methods to improve the efficiency in FDTD simulation are increase in width of time step, enlargement in space grid and extrapolation of late time records. In this paper, we predict the late time record in FDTD simulation by applying Prony¡¦s method, and save the computation time of FDTD simulation. The cost of computation time of Prony¡¦s method is low, and it has a good result that applying Prony¡¦s method at predicting a waveform which resonates with period. In this paper, we try to make a rule for finding training start point and width of training period in Prony¡¦s method. The result of prediction with a short period of time records under the rule is accurate and reliable

For a company to strengthen competitive advantage, they had to put in whatever method they can from time to time, for example, from product innovation, strategic innovation to seek for differentiation. There is also no exceptional for Taiwanese manufacturer. Due to the fact that most Taiwanese manufacturers are small and medium scales company, in addition they are OEM supplier, therefore at initial stage, it is very difficult to pursue differentiation from marketing and product research and development innovation. Under limited resources situation, how to aims at their own strength to select the strategy for differentiation is an issue for Taiwanese manufacturer to consider very thoroughly. This article took small electrical appliances industry as an example and from the business model application standpoint, we discovered that most Taiwanese manufacturers has taken Tapered vertical integration as the main business model to sustain its competitive advantage. Especially when they started on mainland investment, due to the land obtains easily and the cheaper labor force...etc, this vertical integration model application can further be implemented. Taking Value Chain theory and the Smile Curve as a basis for this study, and obtains the most effective vertical integration model is focus on "The Production Vertical Integration". This business model has led a few manufacturers obtain cost advantage in different level. As a case study we take Tsann Kuen Enterprise Co., Ltd as an example, to learn how this company has taken this vertical integration as an approach and developed to become the first Taiwanese manufacturer listed in China stock market. In addition, to learn how it became the top three of the largest small electrical appliances supplier. Finally, from the case study, we will propose a future development approach and suggestion for the Taiwanese small electrical appliances industry. Key Word: Vertical Integration, Smile Curve, Value Chain

Many ecologists are struggling to quantify the species richness in a particular landscape or region. The number of species increases with sample area. Species-area relationship is often used to estimate species richness of a particular region. This study used species-log (area) curves, corrected with Jaccard¡¦s coefficients for within-vegetation type heterogeneity, to estimate species richness and to describe vascular plant species composition in Taiwan Forestry research Institute Tai-Ma-Lee Experimental Forest. In the study area, the author recorded 748 plant species, including 98 endemic species, 21 rare species and 36 naturalized species. There are estimation of 701 species (95¢H CI¡×651~758 species) in the 583-ha natural forest area, 819 species (95¢H CI¡×744~889 species) in the 291-ha plantation area, 560 species (95¢H CI¡×508~641 species) in 8.1-ha forest road. As plantation area is not well-sampled, the total species number in the 947-ha study area could not be estimated. When use 0.1 Modified-Whittaker sampling techniques to assess plant diversity, it is possible to use elevation division, instead of vegetation type, to estimate species richness.

In the age of Knowledge-based Economy, knowledge will become the main motive power of economic growth. Patent, as one of the indicators of intellectual properties, is suitable for measuring the competition potential, technology capabilities, and innovation performance of corporations. In the model of mass production and fast manufacturing, the price of goods decrease acutely and getting the Taiwanese corporations into the low margin age. How to make the most of intellectual properties and patents to increase the additional value is the key to success. Taiwanese companies had starting to apply for patents in many countries, but the licensing fee and litigation are still in high level. That express that the qualities and quantities of the patents are still not enough to cover the technologies and products of Taiwanese companies. This study takes computer heat dissipation industry for example, and using the patent analysis, Logistic curve, and patent strategy matrix to discuss the patent application and patent strategy. The research result shows that the computer heat dissipation industry is in the mature stage, the degree of patent is crowded, and the rate of change is slow. Most of the Taiwanese companies are small scale and not good at inventing in the most advanced technologies. Especially in this mature industry, this study suggest Taiwanese corporations should take licensing, avoiding existing patents, and improvement development as basic patent strategies. Not to apply lots of patents in small scope to suit each other, but should establish patent alliance or co-development, even join or make the industry standard to earn competition advantages.