scholarly journals Probability elicitation using geostatistics in hydrocarbon exploration

2021 ◽  
Author(s):  
André Luís Morosov ◽  
Reidar Brumer Bratvold
Keyword(s):  
Value Creation ◽  
Decision Process ◽  
Conceptual Models ◽  
Joint Probability ◽  
Decision Makers ◽  
Hydrocarbon Exploration ◽  
Joint Probability Distribution ◽  
Proof Of Concept ◽  
Geological Information ◽  
Decision Supporting

AbstractThe exploratory phase of a hydrocarbon field is a period when decision-supporting information is scarce while the drilling stakes are high. Each new prospect drilled brings more knowledge about the area and might reveal reserves, hence choosing such prospect is essential for value creation. Drilling decisions must be made under uncertainty as the available geological information is limited and probability elicitation from geoscience experts is key in this process. This work proposes a novel use of geostatistics to help experts elicit geological probabilities more objectively, especially useful during the exploratory phase. The approach is simpler, more consistent with geologic knowledge, more comfortable for geoscientists to use and, more comprehensive for decision-makers to follow when compared to traditional methods. It is also flexible by working with any amount and type of information available. The workflow takes as input conceptual models describing the geology and uses geostatistics to generate spatial variability of geological properties in the vicinity of potential drilling prospects. The output is stochastic realizations which are processed into a joint probability distribution (JPD) containing all conditional probabilities of the process. Input models are interactively changed until the JPD satisfactory represents the expert’s beliefs. A 2D, yet realistic, implementation of the workflow is used as a proof of concept, demonstrating that even simple modeling might suffice for decision-making support. Derivative versions of the JPD are created and their effect on the decision process of selecting the drilling sequence is assessed. The findings from the method application suggest ways to define the input parameters by observing how they affect the JPD and the decision process.

scholarly journals Managing uncertainty in flood protection planning with climate projections

2018 ◽  
Vol 22 (4) ◽  
pp. 2511-2526 ◽  
Author(s):  
Beatrice Dittes ◽  
Olga Špačková ◽  
Lukas Schoppa ◽  
Daniel Straub
Keyword(s):  
Joint Probability ◽  
Decision Makers ◽  
Flood Protection ◽  
Joint Probability Distribution ◽  
Climate Projections ◽  
Damage Potential ◽  
Protection Measures ◽  
Practical Applications ◽  
The Impact

Abstract. Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure lifetime, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socioeconomic, e.g., whether the population and with it the damage potential grows or falls; technological, e.g., possible advancements in flood protection; and climatic, e.g., whether extreme discharge will become more frequent or not. This paper focuses on climatic uncertainty. Specifically, we devise methodology to account for uncertainty associated with the use of discharge projections, ultimately leading to planning implications. For planning purposes, we categorize uncertainties as either “visible”, if they can be quantified from available catchment data, or “hidden”, if they cannot be quantified from catchment data and must be estimated, e.g., from the literature. It is vital to consider the “hidden uncertainty”, since in practical applications only a limited amount of information (e.g., a finite projection ensemble) is available. We use a Bayesian approach to quantify the “visible uncertainties” and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection. The results show that hidden uncertainty ought to be considered in planning, but the larger the uncertainty already present, the smaller the impact of adding more. The recommended planning is robust to moderate changes in uncertainty as well as in trend. In contrast, planning without consideration of bias and dependencies in and between uncertainty components leads to strongly suboptimal planning recommendations.

scholarly journals Admissibility in Probabilistic Argumentation

2021 ◽  
Author(s):  
Christel Baier ◽  
Martin Diller ◽  
Clemens Dubslaff ◽  
Sarah Alice Gaggl ◽  
Holger Hermanns ◽  
...  
Keyword(s):  
Joint Probability ◽  
Building Blocks ◽  
Joint Probability Distribution ◽  
Proof Of Concept ◽  
Abstract Argumentation ◽  
Classical Setting ◽  
Probabilistic Setting ◽  
Probabilistic Argumentation ◽  
Conservative Extensions ◽  
Quantitative Treatment

Abstract argumentation is a prominent reasoning framework. It comes with a variety of semantics, and has lately been enhanced by probabilities to enable a quantitative treatment of argumentation. While admissibility is a fundamental notion in the classical setting, it has been merely reflected so far in the probabilistic setting. In this paper, we address the quantitative treatment of argumentation based on probabilistic notions of admissibility in a way that they form fully conservative extensions of classical notions. In particular, our building blocks are not the beliefs regarding single arguments. Instead we start from the fairly natural idea that whatever argumentation semantics is to be considered, semantics systematically induces constraints on the joint probability distribution on the sets of arguments. In some cases there might be many such distributions, even infinitely many ones, in other cases there may be one or none. Standard semantic notions are shown to induce such sets of constraints, and so do their probabilistic extensions. This allows them to be tackled by SMT solvers, as we demonstrate by a proof-of-concept implementation. We present a taxonomy of semantic notions, also in relation to published work, together with a running example illustrating our achievements.

scholarly journals Climate uncertainty in flood protection planning

2017 ◽  
Author(s):  
Beatrice Dittes ◽  
Olga Špačková ◽  
Lukas Schoppa ◽  
Daniel Straub
Keyword(s):  
Joint Probability ◽  
Life Time ◽  
Decision Makers ◽  
Flood Protection ◽  
Joint Probability Distribution ◽  
Damage Potential ◽  
Protection Measures ◽  
Practical Applications ◽  
Historic Record

Abstract. Technical flood protection is a necessary part of integrated strategies to protect riverine settlements from extreme floods. Many technical flood protection measures, such as dikes and protection walls, are costly to adapt after their initial construction. This poses a challenge to decision makers as there is large uncertainty in how the required protection level will change during the measure life time, which is typically many decades long. Flood protection requirements should account for multiple future uncertain factors: socio-economic, e.g. whether the population and with it the damage potential grows or falls; technological, e.g. possible advancements in flood protection; and climatic, e.g. whether extreme discharge will become more frequent or not. We focus here on the planning implications of the uncertainty in extreme discharge. We account for the sequential nature of the decision process, in which the adequacy of the protection is regularly revised in the future based on the discharges that have been observed by that point and that reduce uncertainty. For planning purposes, we categorize uncertainties as either visible, if they can be quantified from available catchment data, or hidden, if they cannot be quantified from catchment data and must be estimated, e.g. from literature. It is vital to consider the hidden uncertainty, since in practical applications only a limited amount of information (e.g. through projections, historic record) is available. We use a Bayesian approach to quantify the visible uncertainties and combine them with an estimate of the hidden uncertainties to learn a joint probability distribution of the parameters of extreme discharge. The methodology is integrated into an optimization framework and applied to a pre-alpine case study to give a quantitative, cost-optimal recommendation on the required amount of flood protection.

The Effects of Decision Time on Perceptions of Decisions and Decision Makers in (Moral) Trade-Off Scenarios

2019 ◽  
Author(s):  
Anna Katharina Spälti ◽  
Mark John Brandt ◽  
Marcel Zeelenberg
Keyword(s):  
Decision Process ◽  
Decision Time ◽  
Decision Makers ◽  
Process Information ◽  
Total N ◽  
Trade Off ◽  
Financial Gain ◽  
Trade Offs ◽  
Sacred Values ◽  
Moral Context

People often have to make trade-offs. We study three types of trade-offs: 1) "secular trade-offs" where no moral or sacred values are at stake, 2) "taboo trade-offs" where sacred values are pitted against financial gain, and 3) "tragic trade-offs" where sacred values are pitted against other sacred values. Previous research (Critcher et al., 2011; Tetlock et al., 2000) demonstrated that tragic and taboo trade-offs are not only evaluated by their outcomes, but are also evaluated based on the time it took to make the choice. We investigate two outstanding questions: 1) whether the effect of decision time differs for evaluations of decisions compared to decision makers and 2) whether moral contexts are unique in their ability to influence character evaluations through decision process information. In two experiments (total N = 1434) we find that decision time affects character evaluations, but not evaluations of the decision itself. There were no significant differences between tragic trade-offs and secular trade-offs, suggesting that the decisions structure may be more important in evaluations than moral context. Additionally, the magnitude of the effect of decision time shows us that decision time, may be of less practical use than expected. We thus urge, to take a closer examination of the processes underlying decision time and its perception.

scholarly journals Development of a Shipment Policy for Collection Centers

Mathematics ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 1385
Author(s):  
Irais Mora-Ochomogo ◽  
Marco Serrato ◽  
Jaime Mora-Vargas ◽  
Raha Akhavan-Tabatabaei
Keyword(s):  
Climate Change ◽  
Natural Disasters ◽  
Markov Decision Process ◽  
Decision Process ◽  
Necessary Conditions ◽  
Decision Makers ◽  
Humanitarian Organizations ◽  
The World ◽  
Markov Decision ◽  
Unsatisfied Demand

Natural disasters represent a latent threat for every country in the world. Due to climate change and other factors, statistics show that they continue to be on the rise. This situation presents a challenge for the communities and the humanitarian organizations to be better prepared and react faster to natural disasters. In some countries, in-kind donations represent a high percentage of the supply for the operations, which presents additional challenges. This research proposes a Markov Decision Process (MDP) model to resemble operations in collection centers, where in-kind donations are received, sorted, packed, and sent to the affected areas. The decision addressed is when to send a shipment considering the uncertainty of the donations’ supply and the demand, as well as the logistics costs and the penalty of unsatisfied demand. As a result of the MDP a Monotone Optimal Non-Decreasing Policy (MONDP) is proposed, which provides valuable insights for decision-makers within this field. Moreover, the necessary conditions to prove the existence of such MONDP are presented.

The hidden power of language

2020 ◽  
Vol 11 (1) ◽  
pp. 187-206
Author(s):  
Philipp Hummel ◽  
Jacob Hörisch
Keyword(s):  
Decision Making ◽  
Value Creation ◽  
Cost Reduction ◽  
Social Consequences ◽  
Decision Makers ◽  
Social Aspects ◽  
Social Aspect ◽  
Content Type ◽  
Current Accounting ◽  
Cost Reductions

Purpose Stakeholder theory research identifies changes in language as one possible mechanism to overcome the deficiencies of current accounting practices with regard to social aspects. This study aims to examine the effects of the terms used for specific accounts on company internal decision-making, drawing on the example of “value creation accounting”. Design/methodology/approach The study uses a survey based-experiment to analyze the effects of terms used for specific accounts on decision-making, with a focus on social aspects (in particular expenditures for staff) in cost reduction and expenditure decisions. Findings The findings indicate that wordings, which more closely relate to value creation than to costs, decrease cost reductions and increase the priority ascribed to the social aspect of reducing staff costs in times of financial shortage. The effects of terms used on cost reductions are stronger among female decision makers. Practical implications The analysis suggests that conventional accounting language best suits organizations that aim at incentivizing decision makers to primarily cut costs. By contrast, if an organization follows an approach that puts importance on social aspects in times of financial shortage and on not doing too sharp cost reductions, value creation-oriented language is the more effective approach. Social implications The study suggests that the specific terminology used for accounts should be chosen more carefully and with awareness for the possible effects on cost reduction decisions as well as on social consequences. Originality/value This study contributes to a better understanding of the relevance of language in accounting. It suggests that the terms used for accounts should be chosen purposefully because of their far-reaching potential consequences for stakeholders as well as for the organization.

scholarly journals Fusion Cubes

2013 ◽  
Vol 9 (2) ◽  
pp. 66-88 ◽  
Author(s):  
Alberto Abelló ◽  
Jérôme Darmont ◽  
Lorena Etcheverry ◽  
Matteo Golfarelli ◽  
Jose-Norberto Mazón ◽  
...  
Keyword(s):  
Business Intelligence ◽  
Decision Process ◽  
Decision Makers ◽  
Related Research ◽  
Service Business ◽  
Short Lifespan ◽  
Research Challenges ◽  
Self Service ◽  
Core Idea ◽  
And Storage

Self-service business intelligence is about enabling non-expert users to make well-informed decisions by enriching the decision process with situational data, i.e., data that have a narrow focus on a specific business problem and, typically, a short lifespan for a small group of users. Often, these data are not owned and controlled by the decision maker; their search, extraction, integration, and storage for reuse or sharing should be accomplished by decision makers without any intervention by designers or programmers. The goal of this paper is to present the framework we envision to support self-service business intelligence and the related research challenges; the underlying core idea is the notion of fusion cubes, i.e., multidimensional cubes that can be dynamically extended both in their schema and their instances, and in which situational data and metadata are associated with quality and provenance annotations.

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