The International Energy Agency (IEA) expects total natural gas output in the EU to decrease from 216 billion cubic meters per year (bcm/year) in 2006 to 90 bcm/year in 2030. For the same period, EU demand for natural gas is forecast to increase rapidly. In 2006 demand for natural gas in the EU amounted to 532 bcm/year. By 2030, it is expected to reach 680 bcm/year. As a consequence, the widening gap between EU production and consumption requires a 90% increase of import volumes between 2006 and 2030. The main sources of imported gas for the EU are Russia and Norway. Between them they accounted for 62% of the EU’s gas imports in 2006. The objective of this thesis is to assess the potential future levels of gas supplies to the EU from its two main suppliers, Norway and Russia. Scenarios for future natural gas production potential for Norway and Russia have been modeled utilizing a bottom-up approach, building field-by-field, and individual modeling has been made for giant and semi- giant gas fields. In order to forecast the production profile for an individual giant natural gas field a Giant Gas Field Model (GGF-model) has been developed. The GGF-model has also been applied to production from an aggregate of fields, such as production from small fields and undiscovered resources. Energy security in the EU is heavily dependent on gas supplies from a relatively small number of giant gas fields. In Norway almost all production originates from 18 fields of which 9 can be considered as giant fields. In Russia 36 giant fields account for essentially all gas production. There is limited potential for increased gas exports from Norway to the EU, and all of the scenarios investigated show Norwegian gas production in decline by 2030. Norwegian pipeline gas exports to the EU may even be, by 2030, 20 bcm/year lower than today’s level. The maximum increase in exports of Russian gas supplies to the EU amount to only 45% by 2030. In real numbers this means a mere increase of about 70 bcm In addition, there are a number of potential downside factors for future Russian gas supplies to the European markets. Consequently, a 90% increase of import volumes to the EU by 2030 will be impossible to achieve. From a European energy security perspective the dependence of pipeline gas imports is not the only energy security problem to be in the limelight, the question of physical availability of overall gas supplies deserves serious attention as well. There is a lively discussion regarding the geopolitical implications of European dependence on imported gas from Russia. However, the results of this thesis suggest that when assessing the future gas demand of the EU it would be of equal importance to be concerned about diminishing availability of global gas supplies.

Partially Observable Markov Decision Process (POMDP) is widely used to model sequential decision making process under uncertainty and incomplete knowledge of the environment. It requires strong computation capability and is thus usually deployed on powerful machine. However, as mobile platforms become more advanced and more popular, the potential has been studied to combine POMDP and mobile in order to provide a broader range of services. And yet a question comes with this trend: how should we implement POMDP on mobile platform so that we can take advantages of mobile features while at the same time avoid being restricted by mobile limitations, such as short battery life, weak CPU, unstable networking connection, and other limited resources. In response to the above question, we first point out that the cases vary by problem nature, accuracy requirements and mobile device models. Rather than pure mathematical analysis, our approach is to run experiments on a mobile device and concentrate on a more specific question: which POMDP implementation is the ``best'' for a particular problem on a particular kind of device. Second, we propose and justify a POMDP implementation criterion mainly based on battery consumption that quantifies ``goodness'' of POMDP implementations in terms of mobile battery depletion rate. Then, we present a mobile battery consumption model that translates CPU and WIFI usage into part of the battery depletion rate in order to greatly accelerate the experiment process. With our mobile battery consumption model, we combine a set of simple benchmark experiments with CPU and WIFI usage data from each POMDP implementation candidate to generate estimated battery depletion rates, as opposed to conducting hours of real battery experiments for each implementation individually. The final result is a ranking of POMDP implementations based on their estimated battery depletion rates. It serves as a guidance for on POMDP implementation selection for mobile developers. We develop a mobile software toolkit to automate the above process. Given basic POMDP problem specifications, a set of POMDP implementation candidates and a simple press on the ``start'' button, the toolkit automatically performs benchmark experiments on the target device on which it is installed, and records CPU and WIFI statistics for each POMDP implementation candidate. It then feeds the data to its embedded mobile battery consumption model and produces an estimated battery depletion rate for each candidate. Finally, the toolkit visualizes the ranking of POMDP implementations for mobile developers' reference. Evaluation is assessed through comparsion between the ranking from estimated battery depletion rate and that from real experimental battery depletion rate. We observe the same ranking out of both, which is also our expectation. What's more, the similarity between estimated battery depletion rate and experimental battery depletion rate measured by cosine-similarity is almost 0.999 where 1 indicates they are exactly the same.

The formation of modern society has been dominated by coal and oil, and together these two fossil fuels account for nearly two thirds of all primary energy used by mankind.  This makes future production a key question for future social development and this thesis attempts to answer whether it is possible to rely on an assumption of ever increasing production of coal and oil. Both coal and oil are finite resources, created over long time scales by geological processes. It is thus impossible to extract more fossil fuels than geologically available. In other words, there are limits to growth imposed by nature. The concept of depletion and exhaustion of recoverable resources is a fundamental question for the future extraction of coal and oil. Historical experience shows that peaking is a well established phenomenon in production of various natural resources. Coal and oil are no exceptions, and historical data shows that easily exploitable resources are exhausted while more challenging deposits are left for the future. For oil, depletion can also be tied directly to the physical laws governing fluid flows in reservoirs. Understanding and predicting behaviour of individual fields, in particularly giant fields, are essential for understanding future production. Based on comprehensive databases with reserve and production data for hundreds of oilfields, typical patterns were found. Alternatively, depletion can manifest itself indirectly through various mechanisms. This has been studied for coal. Over 60% of the global crude oil production is derived from only around 330 giant oilfields, where many of them are becoming increasingly mature. The annual decline in existing oil production has been determined to be around 6% and it is unrealistic that this will be offset by new field developments, additional discoveries or unconventional oil. This implies that the peak of the oil age is here. For coal a similar picture emerges, where 90% of the global coal production originates from only 6 countries. Some of them, such as the USA show signs of increasing maturity and exhaustion of the recoverable amounts. However, there is a greater uncertainty about the recoverable reserves and coal production may yield a global maximum somewhere between 2030 and 2060. This analysis shows that the global production peaks of both oil and coal can be expected comparatively soon. This has significant consequences for the global energy supply and society, economy and environment. The results of this thesis indicate that these challenges should not be taken lightly.

Oil is the black blood that runs through the veins of the modern global energy system. While being the dominant source of energy, oil has also brought wealth and power to the western world. Future supply for oil is unsure or even expected to decrease due to limitations imposed by peak oil. Energy is fundamental to all parts of society. The enormous growth and development of society in the last two-hundred years has been driven by rapid increase in the extraction of fossil fuels. In the foresee-able future, the majority of energy will still come from fossil fuels. Consequently, reliable methods for forecasting their production, especially crude oil, are crucial. Forecasting crude oil production can be done in many different ways, but in order to provide realistic outlooks, one must be mindful of the physical laws that affect extraction of hydrocarbons from a reser-voir. Decline curve analysis is a long established tool for developing future outlooks for oil production from an individual well or an entire oilfield. Depletion has a fundamental role in the extraction of finite resources and is one of the driving mechanisms for oil flows within a reservoir. Depletion rate also can be connected to decline curves. Consequently, depletion analysis is a useful tool for analysis and forecasting crude oil production. Based on comprehensive databases with reserve and production data for hundreds of oil fields, it has been possible to identify typical behaviours and properties. Using a combination of depletion and decline rate analysis gives a better tool for describing future oil production on a field-by-field level. Reliable and reasonable forecasts are essential for planning and nec-essary in order to understand likely future world oil production.