Risk Analysis in Drilling Investment Decisions

Newendorp, Paul D.; Root, P.J.

doi:10.2118/1932-pa

Cited by 15 publications

(4 citation statements)

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“…1 These examples illustrate the potential value of the option to drill again. Newendorp (1975) clearly recognized this aspect of the exploration problem. Consider his summary of the situation that confronts a wildcatter:…”

Section: Introductionmentioning

confidence: 92%

“…It is customary to evaluate petroleum prospects in terms of three parameters: the probability of success (p), the expected gross profit conditional on success (V), and the cost of the drilling trial (C). 3 Usually, as in Newendorp (1975), Megill (1988), and Lerche and MacKay (1999), the expected reward associated with the trial is set against the cost of conducting that trial to obtain the expected economic value of the prospect: 4…”

Section: Introductionmentioning

confidence: 99%

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Petroleum Prospect Valuation: The Option to Drill Again

Smith¹

2005

The Energy Journal

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Improving energy efficiency can lower the cost of using energy-intensive goods and may create wealth from the energy savings, both of which lead to increased energy use, a "rebound" effect. I present a theoretical framework that parses rebound into economic income and substitution effects. The framework leads to new insights about the magnitude of rebound when goods are not priced at marginal cost and when consumers are imperfect optimizers, as well as the role of technological progress in rebound. I then explore the implications of this framework with illustrative calculations for improved auto fuel economy and lighting efficiency. These suggest that rebound is unlikely to more than offset the savings from energy efficiency investments (known as "backfire"), but rebound likely reduces the net savings by roughly 10% to 40% from these energy efficiency improvements.

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Section: Introductionmentioning

confidence: 92%

Section: Introductionmentioning

confidence: 99%

Petroleum Prospect Valuation: The Option to Drill Again

Smith¹

2005

The Energy Journal

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“…It is noted that a range has to be selected during the division process using a try and error mechanism. The selected range should be such a way that model performance indices such as root mean square error (RMSE) be minimized for each and every node [59,60].…”

Section: Classification and Regression Treementioning

confidence: 99%

Application of various robust techniques to study and evaluate the role of effective parameters on rock fragmentation

Mehrdanesh

Monjezi

Khandelwal

et al. 2021

Engineering with Computers

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In this paper, an attempt has been made to implement various robust techniques to predict rock fragmentation due to blasting in open pit mines using effective parameters. As rock fragmentation prediction is very complex and complicated, and due to that various artificial intelligence-based techniques, such as Artificial neural network (ANN), classification and regression tree (CART) and support vector machines (SVM) were selected for the modeling.To validate and compare the prediction results, conventional multivariate regression analysis was also utilized on the same datasets. Since accuracy and generality of the modeling is Manuscript Click here to access/download;Manuscript;Manuscript1.docx Click here to view linked References dependent on the number of inputs, it was tried to collect enough required information from four different open pit mines of Iran. According to the obtained results, it was revealed that ANN with a determination coefficient of 0.986 is the most precise method of modeling as compared to the other applied techniques. Also, based on the performed sensitivity analysis, it was observed that the most prevailing parameters on the rock fragmentation are rock quality designation, Schmidt hardness value, mean in-situ block size and the minimum effective ones are hole diameter, burden and spacing. The advantage of back propagation neural network technique for using in this study compared to other soft computing methods is that they are able to describe complex and nonlinear multivariable problems in a transparent way. Furthermore, ANN can be used as a first approach, where much knowledge about the influencing parameters are missing.

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“…Como literaturas básicas podem ser citados os livros de Newendorp (1975) e Mian (2002), nos quais são abordados os principais conceitos e metodologias para a análise de risco na exploração e que também são aplicadas nas previsões de produção. Neles são apresentadas, além dos princípios básicos de probabilidade e estatística, análises através de árvore de decisão, simulação pela técnica de Monte Carlo, bem como os conceitos econômicos de valor presente líquido e do valor monetário esperado.…”

Section: Análise De Risco Na Exploração E Produção De Petróleounclassified

Desenvolvimento de campos de gas natural sob incertezas

Costa¹,

Schiozer²

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Gostaria de agradecer a Deus por ter me dado saúde e forças para vencer todos os obstáculos encontrados nesta caminhada.À Petrobras SA, pela liberação e suporte financeiro durante todo o período do mestrado.À Unicamp, pela oportunidade e, aos professores, pelos conhecimentos transmitidos durante o curso.Ao Professor Denis José Schiozer pela paciência e profissionalismo em todos os momentos.Aos colegas Alice, Sônia, Délcio, Michelle e Giselle pelos apoios na biblioteca, na secretaria e na informática.Aos colaboradores do UNISIM, Paulo Drummond, Ana Gaspar, Elaine, Guilherme, pelo apoio, em especial a Eliana Ligero pelo seu profissionalismo, sua disponibilidade em ajudar sempre e pelos conselhos em discussões técnicas.

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Risk Analysis in Drilling Investment Decisions

Cited by 15 publications

References 0 publications

Petroleum Prospect Valuation: The Option to Drill Again

Petroleum Prospect Valuation: The Option to Drill Again

Application of various robust techniques to study and evaluate the role of effective parameters on rock fragmentation

Desenvolvimento de campos de gas natural sob incertezas

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