Abisoye Babajide Richard de Neufville Michel-Alexandre Cardin

Slides:



Advertisements
Similar presentations
Engineering Economics III. Adjustments We learned how to compute the value of money at different times and under different scenarios. We also learned.
Advertisements

Desktop Business Analytics -- Decision Intelligence l Time Series Forecasting l Risk Analysis l Optimization.
Chapter 9 Project Analysis Chapter Outline
Asset Optimization & Decision Support Services. 1 Overview of Service Program Proprietary service platform that marries 30+ years of Engineering & Subject.
Richard de Neufville © Michael Benouaich Slide 1 of 16 Massachusetts Institute of Technology Engineering System Analysis for Design Valuation with Simulation.
Uncertainty with A Project Analysis. 1.Since the cost behaviors differently occur in two manufacturing systems, new costing systems need to be developed.
Engineering Economic Analysis Canadian Edition
Presenting DFA Results to Decision Makers Spring 2008 Midwest Actuarial Forum.
FINANCE 7. Capital Budgeting (2) Professor André Farber Solvay Business School Université Libre de Bruxelles Fall 2007.
1 Module 1 INTRODUCTION TO DECISION ANALYSIS. 2 Introduction To Decision Analysis Learning Objectives Reasons for studying decision analysis Basic sources.
Planning for Change and Uncertainty ISMT 200G -- March 20, 2007 Dr. Theodore H. K. Clark Associate Professor and Academic Director of MSc in IS Management.
03 July 2015Course Overview1 Energy Project Evaluation RES Course ESP606 Goal: To build up knowledge to so that participants will be able to assess if.
1 Real Options Analysis Office Tower Building Portfolio Presentation Fall 2008 ESD.71 Professor: Richard de Neufville Presented by: Charbel Rizk.
Engineering Systems Analysis for Design Richard de Neufville © Massachusetts Institute of Technology Flaw of Averages Slide 1 of 29 Richard de Neufville.
Opportunity Engineering Harry Larsen The Boeing Company SCEA 2000 Conference.
Engineering Systems Analysis for Design Richard de Neufville  Massachusetts Institute of Technology Use of Simulation Slide 1 of 19 Use of Simulation.
Value of Flexibility an introduction using a spreadsheet analysis of a multi-story parking garage Tao Wang and Richard de Neufville.
Real Options: Does Theory Meet Practice? Professor Alexander J. Triantis.
1 ECGD3110 Systems Engineering & Economy. 2 Lecture 1 Introduction to Engineering Economics.
December 9, 2008 ESD.71 Engineering Systems Analysis for Design Term Project-- Real Option Analysis of Cape Wind Project in Massachusetts Prof. Richard.
Investment Analysis Lecture: 10 Course Code: MBF702.
September 12, 2002CFO Roundtable - Valuing Biotech.
Engineering Economic Analysis Canadian Edition
Engineering Systems Analysis for Design Massachusetts Institute of Technology Richard de Neufville © Hybrid Approach to Valuation Slide 1 of 24 Hybrid.
ESD.70J Engineering Economy Module - Session 21 ESD.70J Engineering Economy Fall 2009 Session Two Michel-Alexandre Cardin – Prof. Richard.
Catalog of Operating Plans: The Quest for the Best ESD.71 Lecture Michel-Alexandre Cardin, PhD Candidate Engineering Systems Division December
Chap 4 Comparing Net Present Value, Decision Trees, and Real Options.
Strategy: Analysis and Practice Slide 1/1 ©The McGraw-Hill Companies, 2005 Chapter 14. Risk, uncertainty and strategy.
Engineering Systems Analysis for Design Massachusetts Institute of Technology Richard de Neufville  Real Options SDMSlide 1 of 31 Richard de Neufville.
Competing For Advantage
12/4/2015 Vijit Mittal (NBS, Gr. Noida) 1 Monte Carlo Simulation,Real Options and Decision Tree.
Engineering Systems Analysis for Design Richard de Neufville  Massachusetts Institute of Technology Use of Simulation Slide 1 of 17 Use of Simulation.
Reservoir Uncertainty Assessment Using Machine Learning Techniques Authors: Jincong He Department of Energy Resources Engineering AbstractIntroduction.
© Rania Hassan; adapted by R. de Neufville Flexibility versus Robustness What’s in a Name?
Valuing Flexibility Using a Catalog of Operating Plans Michel-Alexandre Cardin, PhD Candidate Engineering Systems Division November 12, 2009.
Lecture 03.0 Project analysis Copyright © 2006 by The McGraw-Hill Companies, Inc. All rights reserved McGraw-Hill/Irwin.
ESD.70J Engineering Economy Module - Session 21 ESD.70J Engineering Economy Fall 2010 Session Two Xin Zhang – Prof. Richard de Neufville.
Engineering Systems Analysis for Design Richard de Neufville  Massachusetts Institute of Technology Review for Mid-termSlide 1 of 14 Review of 1st half.
Engineering Systems Analysis for Design Richard de Neufville  Massachusetts Institute of Technology Screening Models Slide 1 of 21 Screening Models Richard.
Richard de Neufville © Michael Benouaich Slide 1 of 16 Massachusetts Institute of Technology Engineering System Analysis for Design Valuation with Simulation.
Integrated Method for Designing Valuable Flexibility In Systems Case Example: Oil Development Project Abisoye Babajide Richard de Neufville Michel-Alexandre.
Capital Budgeting and Risk Pertemuan Matakuliah: A0774/Information Technology Capital Budgeting Tahun: 2009.
The application of quantitative risk analysis (QRA) techniques for well construction in complex reservoirs West Vanguard Snorre cross-section.
Approaches to quantifying uncertainty-related risk There are three approaches to dealing with financial and economic risk in benefit-cost analysis: = expected.
Manufacturing systems Brian Russell. Exam expectations Issues associated with Manufacturing are regularly tested in the written paper. Questions often.
Decision Making Under Uncertainty
Prepared by Katherine Dykes 12/04/2007 ESD 71 – Prof. de Neufville
QUANTITATIVE ANALYSIS
Chapter 12 Implementing strategy through organization
Chapter 10 - Monte Carlo Simulation and the Evaluation of Risk
Chapter 32 Valuing Flexibility Instructors:
Options Concepts Richard de Neufville
Decision Analysis Cases
Flaw of Averages This presentation explains a common problem in the design and evaluation of systems This problem is the pattern of designing and evaluating.
Application Portfolio: Fort Carson Solar Project
Costing and Finance P R Upadhyay.
Garage case: Simulation Example
Chapter 12 Implementing strategy through organization
Lattice Valuation of Flexibility
Evaluating and Choosing Preferred Projects
PARADIGM CHANGE IN SYSTEMS ENGINEERING
ESD.70J Engineering Economy
Analysis of Outcomes What criteria? VARG, concept and construction
PARADIGM CHANGE IN SYSTEMS ENGINEERING
Lattice vs. Decision Analysis
ESD.70J Engineering Economy
Monte Carlo Simulation
Hybrid Approach to Option Valuation
Lattice vs. Decision Analysis
Professeur André Farber
Presentation transcript:

Abisoye Babajide Richard de Neufville Michel-Alexandre Cardin Integrated Method for Designing Valuable Flexibility In Systems Case Example: Oil Development Project Abisoye Babajide Richard de Neufville Michel-Alexandre Cardin September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin Purpose of Case To present and illustrate by example … Integrated method for designing … Flexibility (to expand, change function, or otherwise alter) “In” System (as part of technology) September 2008 © 2008 Babajide, de Neufville, Cardin

Conceptual Take-Aways from Case Traditional design based on fixed assumptions (or ‘requirements’) Evaluation of this design is unrealistic – including uncertainties gives different values – often very different Inserting proper flexibility can increase performance – often very much September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin The Case Oil recovery in Gulf of Mexico “shallow water” ~ 100 m Real case: numbers disguised for company confidentiality Two fields: “Sample” and “Rother” Reservoirs ‘fractured’ – that is, they consist of several smaller pools that each require wells to suck out oil September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin Case Characteristics September 2008 © 2008 Babajide, de Neufville, Cardin

Background to Design Process Initial exploration well was promising Later test wells confirmed promise – but gave different results Each test well expensive (cost depends – tens if not hundreds of millions) So few test wells – value of more not great, due to geological uncertainties Design starts from uncertain oil quantity September 2008 © 2008 Babajide, de Neufville, Cardin

Probability Mass Functions (PMFs) Note: “Most likely” scenarios are 150 and 100 September 2008 © 2008 Babajide, de Neufville, Cardin

Traditional Design Process An oil platform is a very complex system Analysis requires great skill, complex “Oil and Gas Models” needing days to run Time-consuming, expensive for a single set of assumptions Analysis focuses on simple scenario: “Most likely” assessment of oil Price of oil set by top management September 2008 © 2008 Babajide, de Neufville, Cardin

Deterministic Valuation Values of fields, based upon “most likely” assumption September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin Project looks good However: Is this assessment realistic? No! Properly including uncertainties gives different values Jensen’s Inequality – discussion later Can we do better? Yes! Use Flexibility to deal proactively with uncertainties September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin Analysis Method Four Steps: 1. Use traditional analysis as base case 2. Include uncertainties in base case: Exhaustive analysis or Simulation Consider distribution of possibilities (VARG) 3. Identify likely sources of flexibility 4. Value these possibilities – and confirm for detailed engineering analysis September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin Steps 1 and 2 Step 1: Done Step 2: Develop probability distributions Apply to design from traditional process Display consequence for outcomes (VARG) These done next September 2008 © 2008 Babajide, de Neufville, Cardin

© 2008 Babajide, de Neufville, Cardin Combined PMF September 2008 © 2008 Babajide, de Neufville, Cardin

Inflexible Design with Uncertainty Combined fields September 2008 © 2008 Babajide, de Neufville, Cardin

VARG for Inflexible Design Value-at-Risk-and-Gain – Cumulative Distribution of Values Note: Expected NPV ~23M very different from base case ~21M! September 2008 © 2008 Babajide, de Neufville, Cardin

Step 3 – Identify Sources of Flexibility Several Methods Available Topic of Research, best procedures not defined - presumably depend on system Detailed presentation later For now, recognize that base design does not enable exploitation of biggest possible fields Flexibility: More Direct Access, Sub-Sea wells September 2008 © 2008 Babajide, de Neufville, Cardin

Step 4 – Value Flexibilities Repeat evaluation of base case design using the variants with flexibility Find Expected Net Present Values (ENPV) … Also Maxima and Minima Compare along several dimensions Define best combinations of flexibilities Validate in detailed engineering design September 2008 © 2008 Babajide, de Neufville, Cardin

Flexible Combined Fields September 2008 © 2008 Babajide, de Neufville, Cardin

VARGs: Inflexible vs. Flexible September 2008 © 2008 Babajide, de Neufville, Cardin

Comparison of Economic Metrics CAPEX is the initial investment, the “capital expenditure” Note: In general, no alternative best on all measures. Several criteria important to decision-makers, they need to make judgment about trade-offs. September 2008 © 2008 Babajide, de Neufville, Cardin

Benefit-Cost of Flexibility Note: Absolute and Relative Value of Flexibility depends on situation September 2008 © 2008 Babajide, de Neufville, Cardin