Hydrocarbon Field Re-Development as Markov Decision Process

Hydrocarbon field (re-)development requires that a multitude of decisions are made under uncertainty. These decisions include the type and size of surface facilities, location, configuration and number of wells but also which data to acquire. Both types of decisions, which development to choose and which data to acquire, are strongly coupled. The aim of appraisal is to maximize value while minimizing data acquisition costs. These decisions have to be done under uncertainty owing to the inherent uncertainty of the subsurface but also of other costs and economic parameters. Conventional Value Of Information (VOI) evaluations can be used to determine how much can be spend to acquire data. However, VOI is very challenging to calculate for complex sequences of decisions with various costs and including the risk attitude of the decision maker. We are using a fully observable Markov-Decision-Process (MDP) to determine the policy for the sequence and type of measurements and decisions to do. A fully observable MDP is characterised by the states (here: description of the system at a certain point in time), actions (here: measurements and development scenario), transition function (probabilities of transitioning from one state to the next), and rewards (costs for measurements, Expected Monetary Value (EMV) of development options). Solving the MDP gives the optimum policy, sequence of the decisions, the Probability Of Maturation (POM) of a project, the Expected Monetary Value (EMV), the expected loss, the expected appraisal costs, and the Probability of Economic Success (PES). These key performance indicators can then be used to select in a portfolio of projects the ones generating the highest expected reward for the company. Combining the production forecasts from numerical model ensembles with probabilistic capital and operating expenditures and economic parameters allows for quantitative decision making under uncertainty.

Minimizing Lost Circulation Non-Productive Time Using Expected Monetary Value and Decision Tree Analysis

Lost circulation and problems related to drilling present a major challenge for the drilling industry. Each year, billions are spent to treat these problems. There is not a single solution to lost circulation because of the complexity and kind of formations susceptible to this issue. Lost circulation treatment data for the Shuaiba formation (induced fractured formation) were gathered from drilled wells in Southern Iraq (over 2000). Treatments have been grouped according to the volume of mud loss as complete, severe, and partial loss remedies. Detailed costs and probabilities calculations were conducted. The costs of three types of loss treatments (partial, severe, and complete) were handled separately since some treatments of severe, and all treatments of complete losses have to be introducing through open end drill pipe (OEDP). Expected monetary value (EMV) and decision tree analysis (DTA) were utilized to choose the optimal mud loss pathway to treat the lost circulation type. In this study, probability and cost were both considered to select the practical and efficient strategy of stopping mud loss. Too many of the remedy scenarios were investigated. The selection of the optimum strategy for every type of loss was based on the lowest EMV and efficiency. Once both conditions were satisfied, the treatment strategies were selected to treat each type of loss. Treatment strategies were provided for complete, severe, and partial losses as flowcharts that can be utilized as a reference in the field to stop or at least mitigate this troublesome problem. The methods used in this paper have the possibility to be adopted and invested to treat mud loss based on historical data of treatments in any formation worldwide.

Analisa Expected Monetary Value Produksi Kapal Ikan Fiberglass Menggunakan Metode Decision Tree

To make decisions in the production of fiberglass vessels in traditional shipyards in Bengkalis Regency, it is necessary to carry out economic calculations using the Expected Monetary Value (EMV) method related to the production of fiberglass ships and wooden ships using the decision tree method. This is done to determine the chances of the producers succeeding or not with the development of fiberglass ship products, then some forecasting will be conducted on various possibilities that will occur. These possibilities will be formulated with a decision tree model so that producers will be able to decide whether the fiberglass ship product can be continued or only continue by running the old product, which is producing wooden ships. The results of this modeling can later become a reference for producers to look for further solutions if it turns out that after modeling new product results, the fiberglass ship has a greater chance of failure compared to its chances of success. Based on the results of modeling using the decision tree model, it is expected that the opportunity for producers to succeed with their new products, namely fiberglass ships, will be obtained. Keywords: EMV, Fiberglass, Decision Tree, economic

Triangular distribution and PERT method vs. payoff matrix for decision-making support in risk analysis of construction bidding: A case study

Decision-making in construction bidding represents a complex process due to the present risk. Risk or uncertainty cannot be ignored and should be treated as a constituent of decision-making. The paper aims to emphasize the importance of probability theory by comparing insufficiently applicable methods in practical bidding. The triangular distribution and the PERT method belong to three-point estimate techniques, while payoff matrices represent a multi-criteria approach. Also, selected methods belong to quantitative techniques for risk cost analysis. Still, the risk costs determination of the unit costs and the total costs of bids is often based on an intuitive approach. Therefore, compared results of the triangular distribution, PERT method, and payoff matrix techniques (minimin, minimax, expected monetary value, and expected opportunity loss) indicate the significance of risk costs estimating in tendering. The analysis of the results showed some overlaps in risk costs values obtained by the PERT method and expected monetary value technique. Those are due to the specificity of the chosen practical example and cannot be adopted as a rule. This means that selected methods and techniques are very useful for all bid estimation. The paper proved the complexity of decision-making, where the primary goal is to award a contract.

PEMILIHAN PENINGKATAN KAPASITAS PRODUKSI TERBAIK PADA CV. AIDRAT (AMSI) SUNAN DRAJAT LAMONGAN

CV Aidrat Amsi was a business engaged in the production of Amdk that produce Products in the form of Galon, Bottle, and Glass. In CV product. Aidrat Amsi often comes with excess demand that does not match the amount of production. So the company is not able to meet the demand of its customers.The aim of this study was to analyze the best alternative to increase product capacity at CV Aidrat Amasi Sunan Drajat Lamongan. The results of the study showed that CV Aidrat Amsi consisted of the best three alternatives, those are gallon machine purchasing, glass, and bottle. This study also suggested that the selection of gallon machine purchasing was the best alternative due to the having the highest EMV (Expected Monetary Value).

MODELING RISKS IN REAL ESTATE DEVELOPMENT PROJECTS: A CASE FOR EGYPT

Risk analysis is a vital step in the succession of construction projects. However, no adequate researches have been conducted to assess, and quantify risk events in real estate projects in developing countries, and particularly in Egypt.This research recommends Fuzzy Quantitative Risk Assessment Model to quantify risk factors participated in real estate development projects. Model is composed of two components: 1) Fuzzy Fault Tree (FT) that determines root causes of each risk, probability of its occurrence, and probability of mitigation strategies failure; and 2) Fuzzy Event Tree (ET) that calculates crisp value of Expected Monetary Value (EMV) of allowance of mitigation of the identified risks. Causes of risk are determined through literature review and interviews with experts in field. Risk probability occurrence is determined using five linguistic terms, defined either triangular or trapezoidal membership functions which are developed using modified horizontal approach and an interpolation technique. Two-step Delphi technique is used to achieve consensus on the root causes and logical representation of the Fault Tree. Fuzzy importance analysis is performed to rank different root causes for identified risks according to their criticality to probability of occurrence. A Case Study is presented to evaluate results obtained from model, in terms of Expected Monetary Value (EMV), and fuzzy probability of failure for each risk participated in case study.

ESTIMASI RESIKO PENGEMBANGAN SISTEM INFORMASI MENGGUNAKAN PENDEKATAN EXPECTED MONETARY VALUE (EVM)

[Id]Manajemen resiko merupakan bidang penting pada manajemen proyek secara keseluruhan, dan manajemen proyek sistem informasi secara khusus. Melalui manajemen resiko yang baik, pimpinan dan stakeholder proyek berharap bahwa resiko terhadap kegagalan proyek dapat diminimalisir dengan usaha yang rasional. Manajemen resiko sendiri meliputi banyak kegiatan, salah satunya adalah analisis dan perencanaan mitigasi resiko. Aspek penting pada analisis dan perencanaan mitigasi resiko yaitu melakukan penilaian atau estimasi atas resiko untuk menentukan prioritas serta dampak setiap mitigasi yang diambil. Pada umumnya, hal yang paling mudah diterima stakeholder dalam menyajikan resiko adalah menghitung biaya akibat resiko tersebut. Untuk melakukan perhitungan biaya untuk memitigasi resiko, dapat digunakan salah satu pendekatan yaitu Expected Monetary Value (EVM). Melalui pendekatan EVM, dapat ditentukan pilihan tindakan mitigasi yang paling optimal, dengan estimasi biaya paling minimal[En] Risk management is an important area of overall project management, and information systems project management in particular. Through good risk management, project leaders and stakeholders expect that the risks to project failure can be minimized by rational efforts. Risk management itself includes many activities, one of which is risk mitigation analysis and planning. An important aspect of risk mitigation analysis and planning is to assess or estimate the risks to determine the priorities and impacts of each mitigation. In general, the easiest thing a stakeholder receives in presenting risk is to calculate the cost of the risk. To perform cost calculation to mitigate risk, one of the approaches is Expected Monetary Value (EVM). Through the EVM approach, the most optimal mitigation options can be determined, with the least cost estimate