The Option Value of Refracturing Oil Wells: Implementation in a Binomial Lattice

SPE Journal ◽  
2019 ◽  
Vol 24 (04) ◽  
pp. 1903-1911 ◽  
Author(s):  
Babak Jafarizadeh ◽  
Reidar B. Bratvold
Keyword(s):  
Decision Process ◽  
Economic Effect ◽  
Visual Basic ◽  
Cash Flows ◽  
Oil Wells ◽  
Current Level ◽  
Option Value ◽  
Visual Basic For Applications ◽  
Markov Decision ◽  
Binomial Lattice

Summary The steep production decline of unconventional oil wells means that positive cash flows only last for a short while. The operator must then decide whether to continue, abandon, or hydraulically refracture the well. The decision of when to refracture the reservoir has an economic effect on the value of a well, especially with the uncertain oil prices of the future. In this paper, we develop a flexible Markov-decision process that assumes that the optimal refracture or abandonment time depends on the stochastic mean-reverting behavior of prices (described in a binomial lattice) and the then-current level of production. The Excel Visual Basic for Applications (VBA) implementation of the algorithm accompanies this paper.

DEVELOPMENT OF AUTOMATED EVALUATION OF POSITIONING ACCURACY FOR SPECIALIZED NETWORKS’ POINTS IN TRILATERATION NETWORKS

2020 ◽  
Author(s):  
Мурат Газизович Мустафин ◽  
Глеб Андреевич Фролов
Keyword(s):  
Coordinate System ◽  
Visual Basic ◽  
Microsoft Excel ◽  
Positioning Accuracy ◽  
Automated Evaluation ◽  
Visual Basic For Applications ◽  
Multiple Configurations

В данной работе рассмотрен принцип работы созданного алгоритма, позволяющего автоматически определять среднюю квадратическую погрешность планового положения пунктов сетей трилатерации и представлены результаты автоматизации данного процесса при различных конфигурациях сети, с использованием пакетов Microsoft Excel, Visual Basic for Applications. This paper presents automatic solution for evaluating accuracy of positioning for specialized networks’ points in a plane coordinate system. The paper presents results of automation of this process through analysis of multiple configurations of trilateral networks using Microsoft Excel, Visual Basic for Applications.

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.

scholarly journals Dynamic Task Migration Combining Energy Efficiency and Load Balancing Optimization in Three-Tier UAV-Enabled Mobile Edge Computing System

Electronics ◽  
2021 ◽  
Vol 10 (2) ◽  
pp. 190
Author(s):  
Wu Ouyang ◽  
Zhigang Chen ◽  
Jia Wu ◽  
Genghua Yu ◽  
Heng Zhang
Keyword(s):  
Energy Consumption ◽  
Load Balancing ◽  
Markov Decision Process ◽  
Decision Process ◽  
Base Station ◽  
Edge Computing ◽  
Mobile Edge Computing ◽  
Task Migration ◽  
Migration Strategy ◽  
Markov Decision

As transportation becomes more convenient and efficient, users move faster and faster. When a user leaves the service range of the original edge server, the original edge server needs to migrate the tasks offloaded by the user to other edge servers. An effective task migration strategy needs to fully consider the location of users, the load status of edge servers, and energy consumption, which make designing an effective task migration strategy a challenge. In this paper, we innovatively proposed a mobile edge computing (MEC) system architecture consisting of multiple smart mobile devices (SMDs), multiple unmanned aerial vehicle (UAV), and a base station (BS). Moreover, we establish the model of the Markov decision process with unknown rewards (MDPUR) based on the traditional Markov decision process (MDP), which comprehensively considers the three aspects of the migration distance, the residual energy status of the UAVs, and the load status of the UAVs. Based on the MDPUR model, we propose a advantage-based value iteration (ABVI) algorithm to obtain the effective task migration strategy, which can help the UAV group to achieve load balancing and reduce the total energy consumption of the UAV group under the premise of ensuring user service quality. Finally, the results of simulation experiments show that the ABVI algorithm is effective. In particular, the ABVI algorithm has better performance than the traditional value iterative algorithm. And in a dynamic environment, the ABVI algorithm is also very robust.

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