Global ETD Search

61	[en] GENERALIZATION OF THE DEEP LEARNING MODEL FOR NATURAL GAS INDICATION IN 2D SEISMIC IMAGE BASED ON THE TRAINING DATASET AND THE OPERATIONAL HYPER PARAMETERS RECOMMENDATION / [pt] GENERALIZAÇÃO DO MODELO DE APRENDIZADO PROFUNDO PARA INDICAÇÃO DE GÁS NATURAL EM DADOS SÍSMICOS 2D COM BASE NO CONJUNTO DE DADOS DE TREINAMENTO E RECOMENDAÇÃO DE HIPERPARÂMETROS OPERACIONAIS LUIS FERNANDO MARIN SEPULVEDA 21 March 2024 (has links) [pt] A interpretação de imagens sísmicas é uma tarefa essencial em diversas áreas das geociências, sendo um método amplamente utilizado na exploração de hidrocarbonetos. Porém, sua interpretação exige um investimento significativo de recursos, e nem sempre é possível obter um resultado satisfatório. A literatura mostra um número crescente de métodos de Deep Learning, DL, para detecção de horizontes, falhas e potenciais reservatórios de hidrocarbonetos, porém, os modelos para detecção de reservatórios de gás apresentam dificuldades de desempenho de generalização, ou seja, o desempenho fica comprometido quando utilizados em imagens sísmicas de novas explorações campanhas. Este problema é especialmente verdadeiro para levantamentos terrestres 2D, onde o processo de aquisição varia e as imagens apresentam muito ruído. Este trabalho apresenta três métodos para melhorar o desempenho de generalização de modelos DL de indicação de gás natural em imagens sísmicas 2D, para esta tarefa são utilizadas abordagens provenientes de Machine Learning, ML e DL. A pesquisa concentra-se na análise de dados para reconhecer padrões nas imagens sísmicas para permitir a seleção de conjuntos de treinamento para o modelo de inferência de gás com base em padrões nas imagens alvo. Esta abordagem permite uma melhor generalização do desempenho sem alterar a arquitetura do modelo DL de inferência de gás ou transformar os traços sísmicos originais. Os experimentos foram realizados utilizando o banco de dados de diferentes campos de exploração localizados na bacia do Parnaíba, no Nordeste do Brasil. Os resultados mostram um aumento de até 39 por cento na indicação correta do gás natural de acordo com a métrica de recall. Esta melhoria varia em cada campo e depende do método proposto utilizado e da existência de padrões representativos dentro do conjunto de treinamento de imagens sísmicas. Estes resultados concluem com uma melhoria no desempenho de generalização do modelo de inferência de gases DL que varia até 21 por cento de acordo com a pontuação F1 e até 15 por cento de acordo com a métrica IoU. Estes resultados demonstram que é possível encontrar padrões dentro das imagens sísmicas usando uma abordagem não supervisionada, e estas podem ser usadas para recomendar o conjunto de treinamento DL de acordo com o padrão na imagem sísmica alvo; Além disso, demonstra que o conjunto de treinamento afeta diretamente o desempenho de generalização do modelo DL para imagens sísmicas. / [en] Interpreting seismic images is an essential task in diverse fields of geosciences, and it s a widely used method in hydrocarbon exploration. However, its interpretation requires a significant investment of resources, and obtaining a satisfactory result is not always possible. The literature shows an increasing number of Deep Learning, DL, methods to detect horizons, faults, and potential hydrocarbon reservoirs, nevertheless, the models to detect gas reservoirs present generalization performance difficulties, i.e., performance is compromised when used in seismic images from new exploration campaigns. This problem is especially true for 2D land surveys where the acquisition process varies, and the images are very noisy. This work presents three methods to improve the generalization performance of DL models of natural gas indication in 2D seismic images, for this task, approaches that come from Machine Learning, ML, and DL are used. The research focuses on data analysis to recognize patterns within the seismic images to enable the selection of training sets for the gas inference model based on patterns in the target images. This approach allows a better generalization of performance without altering the architecture of the gas inference DL model or transforming the original seismic traces. The experiments were carried out using the database of different exploitation fields located in the Parnaíba basin, in northeastern Brazil. The results show an increase of up to 39 percent in the correct indication of natural gas according to the recall metric. This improvement varies in each field and depends on the proposed method used and the existence of representative patterns within the training set of seismic images. These results conclude with an improvement in the generalization performance of the DL gas inference model that varies up to 21 percent according to the F1 score and up to 15 percent according to the IoU metric. These results demonstrate that it is possible to find patterns within the seismic images using an unsupervised approach, and these can be used to recommend the DL training set according to the pattern in the target seismic image; Furthermore, it demonstrates that the training set directly affects the generalization performance of the DL model for seismic images. [pt] AGRUPAMENTO [en] GROUPING [pt] APRENDIZADO PROFUNDO [en] DEEP LEARNING [pt] IMAGEM SISMICA 2D EM TERRA [en] 2D SEISMIC ONSHORE IMAGE [pt] INDICACAO DE GAS [en] GAS INDICATION [en] TRAINING DATASET RECOMMENDATION
62	Study on optimizing French wind farms bat curtailment plans: reducing production losses while protecting bats Leger, Clément January 2024 (has links) This research delves into the complex interplay between wind turbine operations and bat conservation efforts, focusing on mitigating bat mortality caused by wind turbines in France. Despite comprehensive legal safeguards and conservation measures, bat fatalities remain a pressing concern, necessitating innovative solutions to reconcile environmental protection with energy production. The problem statement revolves around the challenge of optimising bat curtailment plans to minimise bat mortality while mitigating energy losses. With over 80% of bat species in France affected by wind turbine collisions, the urgency of this issue is underscored by the significant ecological implications and regulatory imperatives. Despite the existence of curtailment plans, there is a lack of comprehensive understanding regarding their effectiveness and potential trade-offs. This problem warrants a Master’s thesis project due to its multifaceted nature and practical implications. It requires a nuanced understanding of bat behaviours, wind turbine operations, and regulatory frameworks, making it both intellectually stimulating and socially relevant. Previous efforts have largely focused on static curtailment plans, leaving room for exploration of dynamic approaches and optimisation strategies. The methodology employed in this study involves the development of a Power BI tool and key performance indicators (KPIs) to evaluate different curtailment plans. Through comparative analysis, insights are gained into the efficacy of static versus dynamic curtailment plans, as well as the influence of weather conditions, such as rain, on curtailment decisions. Additionally, sensitivityanalysis is conducted to identify the most influential parameters and optimise curtailment plans accordingly. The key results of this study demonstrate the superiority of dynamic curtailment plans in reducing energy losses while maintaining sufficient protection for bat activity (higher than the 90% protection rate required by law) compared to static approaches (50% reduction in losses over an entire curtailment season). Insights gleaned from sensitivity analysis highlight the critical parameters influencing energy losses, informing targeted modifications to curtailment plans. Furthermore, the study underscores the importance of considering continuous variables, such as humidity, and site-specific factors, such as sunrise and sunset times, for more precise conservation strategies. The implications of this research extend beyond academia, informing policy-making and industry practices in wind energy and biodiversity conservation. By optimizing curtailment plans, stakeholders can achieve a balance between environmental protection and renewable energy generation, paving the way for sustainable development. Future research avenues include refining curtailment strategies based on continuous variables and conducting field studies to validate findings across diverse wind farm locations. / Denna forskning utforskar det komplexa samspel mellan vindkraftverkens drift och fladdermusbevarande insatser, med fokus på att mildra fladdermusdödlighet orsakad av vindkraftverk i Frankrike. Trots omfattande lagliga skydd och bevarandeåtgärder förblir fladdermusdödsfall ett påtagligt bekymmer, vilket kräver innovativa lösningar för att förena miljöskydd med energiproduktion. Problemformuleringen kretsar kring utmaningen att optimera fladdermusbegränsningsplaner för att minimera fladdermusdödlighet samtidigt som energiförluster mildras. Med över 80% av fladdermusarterna i Frankrike påverkade av kollisioner med vindkraftverk, understryks brådskan i detta ärende av dess betydande ekologiska konsekvenser och reglerande krav. Trots att begränsningsplaner existerar, finns det en brist på en heltäckande förståelse för deras effektivitet och potentiella avvägningar. Detta problem motiverar ett magisterprojekt på grund av dess mångfacetterade natur och praktiska konsekvenser. Det kräver en nyanserad förståelse för fladdermusars beteenden, vindkraftverks drift och reglerande ramar, vilket gör det både intellektuellt stimulerande och socialt relevant. Tidigare insatser har i stor utsträckning fokuserat på statiska begränsningsplaner och lämnat utrymme för utforskning av dynamiska tillvägagångssätt och optimeringsstrategier. Metoden som används i denna studie innefattar utvecklingen av ett Power BI-verktyg och nyckelprestationsindikatorer för att utvärdera olika begränsningsplaner. Genom jämförande analys får man insikter om effektiviteten hos statiska jämfört med dynamiska begränsningsplaner, samt påverkan av väderförhållanden, såsom regn, på begränsningsbeslut. Dessutom genomförs känslighetsanalys för att identifiera de mest inflytelserika parametrarna och optimera begränsningsplanerna därefter. De viktigaste resultaten av denna studie visar överlägsenheten hos dynamiska begränsningsplaner när det gäller att minska energiförluster samtidigt som tillräckligt skydd för fladdermusaktivitet bibehålls (högre än den 90% skyddsnivå som krävs enligt lag) jämfört med statiska metoder (50% minskning av förluster under en hel begränsningssäsong). Insikter från känslighetsanalysen belyser de kritiska parametrarna som påverkar energiförluster och ger vägledning för målinriktade modifieringar av begränsningsplaner. Dessutom betonar studien vikten av att beakta kontinuerliga variabler, såsom luftfuktighet, och platsspecifika faktorer, såsom soluppgångs- och solnedgångstider, för mer precisa bevarandestrategier. Denna forsknings betydelse sträcker sig bortom akademin och informerar beslutsfattande inom politik och branschpraxis inom vindenergi och biologisk mångfaldsbevarande. Genom att optimera begränsningsplaner kan intressenter uppnå en balans mellan miljöskydd och förnybar energiproduktion, vilket banar väg för hållbar utveckling. Framtida forskningsvägar inkluderar att förädla begränsningsstrategier baserade på kontinuerliga variabler och att genomföra fältstudier för att validera resultat på olika vindkraftsplatser. Engineering and Technology Teknik och teknologier
63	Global comparison of hedge fund regulations Stoll-Davey, Camille January 2008 (has links) The regulation of hedge funds has been at the centre of a global policy debate for much of the past decade. Several factors feature in this debate including the magnitude of current global investments in hedge funds and the potential of hedge funds to both generate wealth and destabilise financial markets. The first part of the thesis describes the nature of hedge funds and locates the work in relation to four elements in existing theory including regulatory competition theory, the concept of differential mobility as identified by Musgrave, Kane’s concept of the regulatory dialectic between regulators and regulatees, and the concept of unique sets of trust and confidence factors that individual jurisdictions convey to the market. It also identifies a series of questions that de-limit the scope of the present work. These include whether there is evidence that regulatory competition occurs in the context of the provision of domicile for hedge funds, what are the factors which account for the current global distribution of hedge fund domicile, what latitude for regulatory competition is available to jurisdictions competing to provide the domicile for hedge funds, how is such latitude shaped by factors intrinsic and extrinsic to the competing jurisdictions, and why do the more powerful onshore jurisdictions competing to provide the domicile for hedge funds not shut down their smaller and weaker competitors? The second part of the thesis examines the regulatory environment for hedge funds in three so-called offshore jurisdictions, specifically the Cayman Islands, Bermuda and the British Virgin Islands, as well as two onshore jurisdictions, specifically the United Kingdom and the United States. The final section presents a series of conclusions and their implications for both regulatory competition theory and policy. 340
64	Kurz- und langfristige Angebotskurven für Rohöl und die Konsequenzen für den Markt Schlothmann, Daniel 20 April 2016 (has links) (PDF) In dieser Arbeit wurden Angebotskurven für 22 bedeutende Ölförderländer ermittelt und anschließend zu globalen Angebotskurven aggregiert. Gemäß den ermittelten Angebotskurven sind nahezu alle gegenwärtig in der Förderphase befindlichen Ölprojekte in den Untersuchungsländern auch beim aktuellen Ölpreis von 35 bis 40 US-$ je Barrel unter Berücksichtigung der kurzfristigen Grenzkosten rentabel. Sollte der Ölpreis jedoch in den kommenden Jahren auf diesem Niveau verharren, wird es bis zum Jahr 2024 zu einem Angebotsengpass auf dem globalen Ölmarkt kommen, da zur Deckung der zukünftigen Nachfrage die Erschließung kostenintensiver, unkonventioneller Lagerstätten und von Lagerstätten in tiefen und sehr tiefen Gewässern notwendig ist. Damit es bis zum Jahr 2024 nicht zu einem solchen Angebotsengpass kommt, ist gemäß des ermittelten langfristigen Marktgleichgewichts ein Ölpreis von mindestens 80 (2014er) US-$ je Barrel notwendig. Ölmarkt Ölangebot Ölpreis Angebotskurven Grenzkosten Ölförderung Ölprojekte konventionelle Ölförderung unkonventionelle Ölförderung Schweröl. Schwerstöl Ölsand Schieferöl Ölschiefer Tight Oil Offshore Onshore Tiefwasser Fördermethoden in-situ mining Tagebau Fracking EOR Enhanced Oil Recovery hydraulic fracturing Exploration Erschließung Förderung OPEC Algerien Angola Ecuador Iran Irak Libyen Nigeria Katar Kuwait Saudi-Arabien Vereinigte Arabische Emirate Venezuela USA Kanada Mexiko Brasilien Großbritannien Norwegen Aserbaidschan Kasachstan Russland China oil market oil supply supply curves marginal costs oil production oil projects conventional oil unconventional oil extra heavy oil oil sands tight oil shale oil oil shale offshore onshore pre-salt in-situ mining hydraulic fracturing EOR enhanced oil recovery exploration development production OPEC Algeria Angola Ecuador Iran Iraq Libya Qatar Kuwait Saudi Arabia United Arab Emirates Venezuela United States Canada Mexico Brazil United Kingdom Norway Azerbaijan Kazakhstan Russia China ddc:330 rvk:QR 534 Welt Erdöllagerstätte Erdölproduktion Fördermenge Erdölangebot Erdölpreis Erdölweltmarkt Grenzkosten Marktgleichgewicht Preissteigerung Erdölbohrung Tagebau Fracking Ölsand Schieferöl
65	Kurz- und langfristige Angebotskurven für Rohöl und die Konsequenzen für den Markt Schlothmann, Daniel 08 March 2016 (has links) In dieser Arbeit wurden Angebotskurven für 22 bedeutende Ölförderländer ermittelt und anschließend zu globalen Angebotskurven aggregiert. Gemäß den ermittelten Angebotskurven sind nahezu alle gegenwärtig in der Förderphase befindlichen Ölprojekte in den Untersuchungsländern auch beim aktuellen Ölpreis von 35 bis 40 US-$ je Barrel unter Berücksichtigung der kurzfristigen Grenzkosten rentabel. Sollte der Ölpreis jedoch in den kommenden Jahren auf diesem Niveau verharren, wird es bis zum Jahr 2024 zu einem Angebotsengpass auf dem globalen Ölmarkt kommen, da zur Deckung der zukünftigen Nachfrage die Erschließung kostenintensiver, unkonventioneller Lagerstätten und von Lagerstätten in tiefen und sehr tiefen Gewässern notwendig ist. Damit es bis zum Jahr 2024 nicht zu einem solchen Angebotsengpass kommt, ist gemäß des ermittelten langfristigen Marktgleichgewichts ein Ölpreis von mindestens 80 (2014er) US-$ je Barrel notwendig.:1. Einleitung 2. Rohöl - Eine naturwissenschaftliche Einführung 3. Charakteristika von Rohölprojekten 4. Historie der Ölindustrie 5. Ökonomik von Rohölprojekten 6. Fallstudien zu den bedeutendsten Förderländern 7. Ermittlung regionaler und globaler Angebotskurven 8. Zusammenfassung info:eu-repo/classification/ddc/330 ddc:330

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