# SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:

Save this PDF as:

Size: px
Start display at page:

Download "SPEE Recommended Evaluation Practice #6 Definition of Decline Curve Parameters Background:"

## Transcription

1 SPEE Recommended Evaluaton Practce #6 efnton of eclne Curve Parameters Background: The producton hstores of ol and gas wells can be analyzed to estmate reserves and future ol and gas producton rates and to valdate results of complex reservor studes. Because accurate producton data are commonly avalable on most wells, producton data analyses can be wdely appled. eclne curve analyss relates past performance of ol and gas wells to future performance, but t reures modfcaton to account for changes n performance due to operatng condtons or changes n reservor behavor. eclne curves are smply a plot of producton rate versus tme on sem-log, loglog, or specally scaled paper. The most common plot s sem-log. When the logarthm of producng rate s plotted versus lnear tme, a straght lne often results. Ths phenomenon s referred to as exponental declne or constant percent declne. If the data plot as a concave upwards curve, a harmonc or hyperbolc declne model can be used to model the data. The mathematcal euaton defnng exponental declne has two constants, the ntal producton rate and the declne rate. The declne rate s the rate of change of producton wth respect to tme and, for exponental declne, s constant for all tme. There are two ways to defne the declne rate for exponental declne nomnal and effectve. The mathematcal euaton defnng hyperbolc declne has three constants, the ntal producton rate, the ntal declne rate (defned at the same tme as the ntal producton rate), and the hyperbolc exponent. The declne rate s not a constant, but changes wth tme, snce the data plot as a curve on sem-log paper. The hyperbolc exponent s the rate of change of the declne rate wth respect to tme, or the second dervatve of producton rate wth respect to tme. There are three ways to defne the ntal declne rate for hyperbolc declne nomnal, tangent effectve, and secant effectve. Fgure 1 llustrates the dfference between the tangent effectve and secant effectve defntons of ntal declne rate. Computer programs usually use the nomnal form of the euatons nternally whle nput and output are usually n terms of effectve declne. The declne curve euatons n terms of nomnal declne and the euatons used to convert from one form of declne to another are as shown below. Page 1 of 7

2 eclne Curve Euatons (for consstent unts) Nomnal Effectve: Exponental declne ln = t ( - ) e = for a partcular tme perod, usually 1 year Effectve declne as a functon of nomnal declne s: - e = 1- e Nomnal declne as a functon of effectve declne s: = - ln (1- ) e Nomnal Tangent Effectve Secant Effectve Hyperbolc declne b 1 = bt ( - ) e = where and are read from the tangent lne ( - ) es = where and are read from the secant lne Nomnal declne as a functon of tangent effectve declne s: = - ln (1- e ) Nomnal declne as a functon of secant effectve declne s: b ( 1- es ) 1 =, b 0 b Where: = nomnal exponental declne rate, 1/tme = ntal nomnal declne rate (t=0), 1/tme e = ntal effectve declne rate from tangent lne, 1/tme es = ntal effectve declne rate from secant lne, 1/tme Page 2 of 7

3 = nstantaneous producng rate at tme 0, vol/unt tme = nstantaneous producng rate at tme t, vol/unt tme t = tme e = base of natural logarthms (2.718 ) b = hyperbolc exponent (escrbes how the ntal declne rate,, changes wth tme; vares from 0 to 1 usually. When b = 1, the declne s called harmonc. Ths exponent s sometmes referred to n the lterature as n ) scusson: There are varyng opnons over whether the effectve or nomnal declne euaton should be used. Nomnal declne rate can take on any value from negatve nfnty to postve nfnty where negatve numbers ndcate producton rate s ncreasng rather than decreasng. Effectve declne rate cannot exceed 1.0 snce an endng flow rate of zero results n an effectve declne rate of / or 1. Ths lmtaton on effectve declne rate can lead to problems wth wells that are experencng extremely hgh ntal declnes such as massve hydraulc fracs n tght gas reservors or horzontal wells. It s not unusual to see ntal nomnal declne rates on the order of 30 (3000%) n these cases. The tangent effectve declne rate correspondng to a nomnal declne rate of 30 s (thrteen 9 s followed by 06.) Snce double precson numbers n computers are lmted to approxmately 15 decmal dgts of accuracy, t s mpossble to represent any exponental declne rate sgnfcantly n excess of 30 usng tangent effectve declne. Some computer programs only allow 8 or fewer dgts for declne rate. At 8 dgts the maxmum nomnal declne rate that can be represented s approxmately 20 (2000%.) Normally, extremely hgh ntal declne rates are assocated wth hyperbolc declne curves, often wth ntal values of b at or near 2. When b s 1 or greater t s possble to use the secant effectve declne even at extremely hgh declne rates. If b s 2 and the ntal nomnal declne s 100 (10000%) the value of the ntal secant effectve declne rate s %. Ths number s easly represented even n sngle precson. Table 1 and Fgure 2 show the value of tangent effectve declne (whch s ndependent of b ) and secant effectve declne for varous values of b. Page 3 of 7

4 The secant effectve declne rate has the addtonal advantage of beng calculated from two rates read from the smooth lne through the data one rate at tme 0 (whch can be arbtrarly defned) and one rate exactly one year later. Another factor whch must be recognzed s that the producton rate referred to n the above euatons s the nstantaneous rate at a partcular pont n tme. It s not the average rate for a month or the average rate for a year. In cases where the ntal declne rate s hgh the rate at the begnnng of a month may be consderably larger than the average rate durng the month. Any of these methods of defnng the future producton curve wll lead to the correct answer f they are properly appled. The most mportant thng s clear and consstent communcaton between the user and the computer programmer. SPEE Recommended Evaluaton Practce: SPEE recommends that the termnology shown above be used. Further, SPEE recommends that all nput and output be clearly labeled usng the followng names and symbols. Item Nomnal eclne Rate, exponental Intal Nomnal eclne Rate, hyperbolc Effectve eclne Rate, exponental Intal Tangent Effectve eclne Rate, hyperbolc Intal Secant Effectve eclne Rate, hyperbolc Symbo l e e es References: Arps, J.J., (1956). Estmaton of Prmary Ol Reserves. allas: Socety of Petroleum Engneers. Fetkovch, M.J. (1980): eclne Curve Analyss usng Type Curves, J. Pet. Tech., (June 1980) Page 4 of 7

5 Fgure1 eclne Rate efntons for Hyperbolc eclne 100 efnton of eclne Rate Secant Producton Rate, BOP "Actual" ata Tangent Tme, years Page 5 of 7

6 Fgure 2 Effectve eclne Rate as a functon of Nomnal eclne Rate 100% 90% 80% Effectve eclne Rate, 1/tme 70% 60% 50% 40% 30% Tangent Secant, b=0 Secant, b=.5 Secant, b=1 Secant, b=1.5 Secant, b=2 20% 10% 0% 1% 10% 100% 1000% 10000% Nomnal eclne Rate, 1/tme Page 6 of 7

7 Table 1 - Effectve eclne Rate as a functon of Nomnal eclne Rate Nomnal eclne Rate, 1/year Effectve Tangent eclne Rate, 1/year Effectve Secant eclne Rate, 1/year Value of "b" % % % % % % % 2% % % % % % % 3% % % % % % % 4% % % % % % % 5% % % % % % % 6% % % % % % % 7% % % % % % % 8% % % % % % % 9% % % % % % % 10% % % % % % % 20% % % % % % % 30% % % % % % % 40% % % % % % % 50% % % % % % % 60% % % % % % % 70% % % % % % % 80% % % % % % % 90% % % % % % % 100% % % % % % % 200% % % % % % % 300% % % % % % % 400% % % % % % % 500% % % % % % % 600% % % % % % % 700% % % % % % % 800% % % % % % % 900% % % % % % % 1000% % % % % % % 2000% % % % % % % 3000% % % % % % % 4000% % % % % % % 5000% % % % % % % 6000% % % % % % % 7000% % % % % % % 8000% % % % % % % 9000% % % % % % % 10000% % % % % % % Page 7 of 7

### An Alternative Way to Measure Private Equity Performance

An Alternatve Way to Measure Prvate Equty Performance Peter Todd Parlux Investment Technology LLC Summary Internal Rate of Return (IRR) s probably the most common way to measure the performance of prvate

### A Master Time Value of Money Formula. Floyd Vest

A Master Tme Value of Money Formula Floyd Vest For Fnancal Functons on a calculator or computer, Master Tme Value of Money (TVM) Formulas are usually used for the Compound Interest Formula and for Annutes.

### An Evaluation of the Extended Logistic, Simple Logistic, and Gompertz Models for Forecasting Short Lifecycle Products and Services

An Evaluaton of the Extended Logstc, Smple Logstc, and Gompertz Models for Forecastng Short Lfecycle Products and Servces Charles V. Trappey a,1, Hsn-yng Wu b a Professor (Management Scence), Natonal Chao

### ASSESSMENT OF STEAM SUPPLY FOR THE EXPANSION OF GENERATION CAPACITY FROM 140 TO 200 MW, KAMOJANG GEOTHERMAL FIELD, WEST JAVA, INDONESIA

ASSESSMENT OF STEAM SUPPLY FOR THE EXPANSION OF GENERATION CAPACITY FROM 14 TO 2 MW, KAMOJANG GEOTHERMAL FIELD, WEST JAVA, INDONESIA Subr K. Sanyal 1, Ann Robertson-Tat 1, Chrstopher W. Klen 1, Steven

### 1. Measuring association using correlation and regression

How to measure assocaton I: Correlaton. 1. Measurng assocaton usng correlaton and regresson We often would lke to know how one varable, such as a mother's weght, s related to another varable, such as a

### Lecture 3: Annuity. Study annuities whose payments form a geometric progression or a arithmetic progression.

Lecture 3: Annuty Goals: Learn contnuous annuty and perpetuty. Study annutes whose payments form a geometrc progresson or a arthmetc progresson. Dscuss yeld rates. Introduce Amortzaton Suggested Textbook

### Lecture 3: Force of Interest, Real Interest Rate, Annuity

Lecture 3: Force of Interest, Real Interest Rate, Annuty Goals: Study contnuous compoundng and force of nterest Dscuss real nterest rate Learn annuty-mmedate, and ts present value Study annuty-due, and

### FINANCIAL MATHEMATICS. A Practical Guide for Actuaries. and other Business Professionals

FINANCIAL MATHEMATICS A Practcal Gude for Actuares and other Busness Professonals Second Edton CHRIS RUCKMAN, FSA, MAAA JOE FRANCIS, FSA, MAAA, CFA Study Notes Prepared by Kevn Shand, FSA, FCIA Assstant

### Causal, Explanatory Forecasting. Analysis. Regression Analysis. Simple Linear Regression. Which is Independent? Forecasting

Causal, Explanatory Forecastng Assumes cause-and-effect relatonshp between system nputs and ts output Forecastng wth Regresson Analyss Rchard S. Barr Inputs System Cause + Effect Relatonshp The job of

### On the Optimal Control of a Cascade of Hydro-Electric Power Stations

On the Optmal Control of a Cascade of Hydro-Electrc Power Statons M.C.M. Guedes a, A.F. Rbero a, G.V. Smrnov b and S. Vlela c a Department of Mathematcs, School of Scences, Unversty of Porto, Portugal;

### benefit is 2, paid if the policyholder dies within the year, and probability of death within the year is ).

REVIEW OF RISK MANAGEMENT CONCEPTS LOSS DISTRIBUTIONS AND INSURANCE Loss and nsurance: When someone s subject to the rsk of ncurrng a fnancal loss, the loss s generally modeled usng a random varable or

### Texas Instruments 30X IIS Calculator

Texas Instruments 30X IIS Calculator Keystrokes for the TI-30X IIS are shown for a few topcs n whch keystrokes are unque. Start by readng the Quk Start secton. Then, before begnnng a specfc unt of the

### What is Candidate Sampling

What s Canddate Samplng Say we have a multclass or mult label problem where each tranng example ( x, T ) conssts of a context x a small (mult)set of target classes T out of a large unverse L of possble

### BERNSTEIN POLYNOMIALS

On-Lne Geometrc Modelng Notes BERNSTEIN POLYNOMIALS Kenneth I. Joy Vsualzaton and Graphcs Research Group Department of Computer Scence Unversty of Calforna, Davs Overvew Polynomals are ncredbly useful

### APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT

APPLICATION OF PROBE DATA COLLECTED VIA INFRARED BEACONS TO TRAFFIC MANEGEMENT Toshhko Oda (1), Kochro Iwaoka (2) (1), (2) Infrastructure Systems Busness Unt, Panasonc System Networks Co., Ltd. Saedo-cho

### SIMPLE LINEAR CORRELATION

SIMPLE LINEAR CORRELATION Smple lnear correlaton s a measure of the degree to whch two varables vary together, or a measure of the ntensty of the assocaton between two varables. Correlaton often s abused.

### A Model of Private Equity Fund Compensation

A Model of Prvate Equty Fund Compensaton Wonho Wlson Cho Andrew Metrck Ayako Yasuda KAIST Yale School of Management Unversty of Calforna at Davs June 26, 2011 Abstract: Ths paper analyzes the economcs

### Answer: A). There is a flatter IS curve in the high MPC economy. Original LM LM after increase in M. IS curve for low MPC economy

4.02 Quz Solutons Fall 2004 Multple-Choce Questons (30/00 ponts) Please, crcle the correct answer for each of the followng 0 multple-choce questons. For each queston, only one of the answers s correct.

### Module 2 LOSSLESS IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Module LOSSLESS IMAGE COMPRESSION SYSTEMS Lesson 3 Lossless Compresson: Huffman Codng Instructonal Objectves At the end of ths lesson, the students should be able to:. Defne and measure source entropy..

### Trade Adjustment and Productivity in Large Crises. Online Appendix May 2013. Appendix A: Derivation of Equations for Productivity

Trade Adjustment Productvty n Large Crses Gta Gopnath Department of Economcs Harvard Unversty NBER Brent Neman Booth School of Busness Unversty of Chcago NBER Onlne Appendx May 2013 Appendx A: Dervaton

Summary of Analyss of Premum Labltes for Australan Lnes of Busness Emly Tao Honours Research Paper, The Unversty of Melbourne Emly Tao Acknowledgements I am grateful to the Australan Prudental Regulaton

### Binomial Link Functions. Lori Murray, Phil Munz

Bnomal Lnk Functons Lor Murray, Phl Munz Bnomal Lnk Functons Logt Lnk functon: ( p) p ln 1 p Probt Lnk functon: ( p) 1 ( p) Complentary Log Log functon: ( p) ln( ln(1 p)) Motvatng Example A researcher

### Jet Engine. Figure 1 Jet engine

Jet Engne Prof. Dr. Mustafa Cavcar Anadolu Unversty, School of Cvl Avaton Esksehr, urkey GROSS HRUS INAKE MOMENUM DRAG NE HRUS Fgure 1 Jet engne he thrust for a turboet engne can be derved from Newton

### Support Vector Machines

Support Vector Machnes Max Wellng Department of Computer Scence Unversty of Toronto 10 Kng s College Road Toronto, M5S 3G5 Canada wellng@cs.toronto.edu Abstract Ths s a note to explan support vector machnes.

### The circuit shown on Figure 1 is called the common emitter amplifier circuit. The important subsystems of this circuit are:

polar Juncton Transstor rcuts Voltage and Power Amplfer rcuts ommon mtter Amplfer The crcut shown on Fgure 1 s called the common emtter amplfer crcut. The mportant subsystems of ths crcut are: 1. The basng

### The Development of Web Log Mining Based on Improve-K-Means Clustering Analysis

The Development of Web Log Mnng Based on Improve-K-Means Clusterng Analyss TngZhong Wang * College of Informaton Technology, Luoyang Normal Unversty, Luoyang, 471022, Chna wangtngzhong2@sna.cn Abstract.

### CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK. Sample Stability Protocol

CHOLESTEROL REFERENCE METHOD LABORATORY NETWORK Sample Stablty Protocol Background The Cholesterol Reference Method Laboratory Network (CRMLN) developed certfcaton protocols for total cholesterol, HDL

### Solution: Let i = 10% and d = 5%. By definition, the respective forces of interest on funds A and B are. i 1 + it. S A (t) = d (1 dt) 2 1. = d 1 dt.

Chapter 9 Revew problems 9.1 Interest rate measurement Example 9.1. Fund A accumulates at a smple nterest rate of 10%. Fund B accumulates at a smple dscount rate of 5%. Fnd the pont n tme at whch the forces

### An Overview of Financial Mathematics

An Overvew of Fnancal Mathematcs Wllam Benedct McCartney July 2012 Abstract Ths document s meant to be a quck ntroducton to nterest theory. It s wrtten specfcally for actuaral students preparng to take

### Project Networks With Mixed-Time Constraints

Project Networs Wth Mxed-Tme Constrants L Caccetta and B Wattananon Western Australan Centre of Excellence n Industral Optmsaton (WACEIO) Curtn Unversty of Technology GPO Box U1987 Perth Western Australa

### ) of the Cell class is created containing information about events associated with the cell. Events are added to the Cell instance

Calbraton Method Instances of the Cell class (one nstance for each FMS cell) contan ADC raw data and methods assocated wth each partcular FMS cell. The calbraton method ncludes event selecton (Class Cell

### Analysis of Reactivity Induced Accident for Control Rods Ejection with Loss of Cooling

Analyss of Reactvty Induced Accdent for Control Rods Ejecton wth Loss of Coolng Hend Mohammed El Sayed Saad 1, Hesham Mohammed Mohammed Mansour 2 Wahab 1 1. Nuclear and Radologcal Regulatory Authorty,

### Mathematics of Finance

5 Mathematcs of Fnance 5.1 Smple and Compound Interest 5.2 Future Value of an Annuty 5.3 Present Value of an Annuty;Amortzaton Chapter 5 Revew Extended Applcaton:Tme, Money, and Polynomals Buyng a car

### Chapter 12 Inductors and AC Circuits

hapter Inductors and A rcuts awrence B. ees 6. You may make a sngle copy of ths document for personal use wthout wrtten permsson. Hstory oncepts from prevous physcs and math courses that you wll need for

### Optical Signal-to-Noise Ratio and the Q-Factor in Fiber-Optic Communication Systems

Applcaton ote: FA-9.0. Re.; 04/08 Optcal Sgnal-to-ose Rato and the Q-Factor n Fber-Optc Communcaton Systems Functonal Dagrams Pn Confguratons appear at end of data sheet. Functonal Dagrams contnued at

### Properties of real networks: degree distribution

Propertes of real networks: degree dstrbuton Nodes wth small degrees are most frequent. The fracton of hghly connected nodes decreases, but s not zero. Look closer: use a logarthmc plot. 10 0 10-1 10 0

### Can Auto Liability Insurance Purchases Signal Risk Attitude?

Internatonal Journal of Busness and Economcs, 2011, Vol. 10, No. 2, 159-164 Can Auto Lablty Insurance Purchases Sgnal Rsk Atttude? Chu-Shu L Department of Internatonal Busness, Asa Unversty, Tawan Sheng-Chang

### Chapter 31B - Transient Currents and Inductance

Chapter 31B - Transent Currents and Inductance A PowerPont Presentaton by Paul E. Tppens, Professor of Physcs Southern Polytechnc State Unversty 007 Objectves: After completng ths module, you should be

### A system for real-time calculation and monitoring of energy performance and carbon emissions of RET systems and buildings

A system for real-tme calculaton and montorng of energy performance and carbon emssons of RET systems and buldngs Dr PAAIOTIS PHILIMIS Dr ALESSADRO GIUSTI Dr STEPHE GARVI CE Technology Center Democratas

### AS 2553a Mathematics of finance

AS 2553a Mathematcs of fnance Formula sheet November 29, 2010 Ths ocument contans some of the most frequently use formulae that are scusse n the course As a general rule, stuents are responsble for all

### Rapid Estimation Method for Data Capacity and Spectrum Efficiency in Cellular Networks

Rapd Estmaton ethod for Data Capacty and Spectrum Effcency n Cellular Networs C.F. Ball, E. Humburg, K. Ivanov, R. üllner Semens AG, Communcatons oble Networs unch, Germany carsten.ball@semens.com Abstract

### The Application of Fractional Brownian Motion in Option Pricing

Vol. 0, No. (05), pp. 73-8 http://dx.do.org/0.457/jmue.05.0..6 The Applcaton of Fractonal Brownan Moton n Opton Prcng Qng-xn Zhou School of Basc Scence,arbn Unversty of Commerce,arbn zhouqngxn98@6.com

### THE DISTRIBUTION OF LOAN PORTFOLIO VALUE * Oldrich Alfons Vasicek

HE DISRIBUION OF LOAN PORFOLIO VALUE * Oldrch Alfons Vascek he amount of captal necessary to support a portfolo of debt securtes depends on the probablty dstrbuton of the portfolo loss. Consder a portfolo

### A machine vision approach for detecting and inspecting circular parts

A machne vson approach for detectng and nspectng crcular parts Du-Mng Tsa Machne Vson Lab. Department of Industral Engneerng and Management Yuan-Ze Unversty, Chung-L, Tawan, R.O.C. E-mal: edmtsa@saturn.yzu.edu.tw

### total A A reag total A A r eag

hapter 5 Standardzng nalytcal Methods hapter Overvew 5 nalytcal Standards 5B albratng the Sgnal (S total ) 5 Determnng the Senstvty (k ) 5D Lnear Regresson and albraton urves 5E ompensatng for the Reagent

### ECONOMICS OF PLANT ENERGY SAVINGS PROJECTS IN A CHANGING MARKET Douglas C White Emerson Process Management

ECONOMICS OF PLANT ENERGY SAVINGS PROJECTS IN A CHANGING MARKET Douglas C Whte Emerson Process Management Abstract Energy prces have exhbted sgnfcant volatlty n recent years. For example, natural gas prces

### Section 2 Introduction to Statistical Mechanics

Secton 2 Introducton to Statstcal Mechancs 2.1 Introducng entropy 2.1.1 Boltzmann s formula A very mportant thermodynamc concept s that of entropy S. Entropy s a functon of state, lke the nternal energy.

### Optimal Bidding Strategies for Generation Companies in a Day-Ahead Electricity Market with Risk Management Taken into Account

Amercan J. of Engneerng and Appled Scences (): 8-6, 009 ISSN 94-700 009 Scence Publcatons Optmal Bddng Strateges for Generaton Companes n a Day-Ahead Electrcty Market wth Rsk Management Taken nto Account

### Fuzzy Set Approach To Asymmetrical Load Balancing In Distribution Networks

Fuzzy Set Approach To Asymmetrcal Load Balancng n Dstrbuton Networks Goran Majstrovc Energy nsttute Hrvoje Por Zagreb, Croata goran.majstrovc@ehp.hr Slavko Krajcar Faculty of electrcal engneerng and computng

### The Effect of Mean Stress on Damage Predictions for Spectral Loading of Fiberglass Composite Coupons 1

EWEA, Specal Topc Conference 24: The Scence of Makng Torque from the Wnd, Delft, Aprl 9-2, 24, pp. 546-555. The Effect of Mean Stress on Damage Predctons for Spectral Loadng of Fberglass Composte Coupons

### Institute of Informatics, Faculty of Business and Management, Brno University of Technology,Czech Republic

Lagrange Multplers as Quanttatve Indcators n Economcs Ivan Mezník Insttute of Informatcs, Faculty of Busness and Management, Brno Unversty of TechnologCzech Republc Abstract The quanttatve role of Lagrange

### Forecasting the Direction and Strength of Stock Market Movement

Forecastng the Drecton and Strength of Stock Market Movement Jngwe Chen Mng Chen Nan Ye cjngwe@stanford.edu mchen5@stanford.edu nanye@stanford.edu Abstract - Stock market s one of the most complcated systems

### Multiple-Period Attribution: Residuals and Compounding

Multple-Perod Attrbuton: Resduals and Compoundng Our revewer gave these authors full marks for dealng wth an ssue that performance measurers and vendors often regard as propretary nformaton. In 1994, Dens

### Staff Paper. Farm Savings Accounts: Examining Income Variability, Eligibility, and Benefits. Brent Gloy, Eddy LaDue, and Charles Cuykendall

SP 2005-02 August 2005 Staff Paper Department of Appled Economcs and Management Cornell Unversty, Ithaca, New York 14853-7801 USA Farm Savngs Accounts: Examnng Income Varablty, Elgblty, and Benefts Brent

### Traffic State Estimation in the Traffic Management Center of Berlin

Traffc State Estmaton n the Traffc Management Center of Berln Authors: Peter Vortsch, PTV AG, Stumpfstrasse, D-763 Karlsruhe, Germany phone ++49/72/965/35, emal peter.vortsch@ptv.de Peter Möhl, PTV AG,

### Chapter 4 ECONOMIC DISPATCH AND UNIT COMMITMENT

Chapter 4 ECOOMIC DISATCH AD UIT COMMITMET ITRODUCTIO A power system has several power plants. Each power plant has several generatng unts. At any pont of tme, the total load n the system s met by the

### Calculating the high frequency transmission line parameters of power cables

< ' Calculatng the hgh frequency transmsson lne parameters of power cables Authors: Dr. John Dcknson, Laboratory Servces Manager, N 0 RW E B Communcatons Mr. Peter J. Ncholson, Project Assgnment Manager,

### Monitoring sea level change at Cascais tide gauge

Journal of Coastal Research SI 64 pg - pg ICS211 (Proceedngs) Poland ISSN 749-28 Montorng sea level change at Cascas tde gauge C. Antunes IDL Unversty of Lsbon, Lsbon, 1794-16 Portugal cmantunes@fc.ul.pt

### Ring structure of splines on triangulations

www.oeaw.ac.at Rng structure of splnes on trangulatons N. Vllamzar RICAM-Report 2014-48 www.rcam.oeaw.ac.at RING STRUCTURE OF SPLINES ON TRIANGULATIONS NELLY VILLAMIZAR Introducton For a trangulated regon

### Analysis of Subscription Demand for Pay-TV

Analyss of Subscrpton Demand for Pay-TV Manabu Shshkura * Norhro Kasuga ** Ako Tor *** Abstract In ths paper, we wll conduct an analyss from an emprcal perspectve concernng broadcastng demand behavor and

### Risk Model of Long-Term Production Scheduling in Open Pit Gold Mining

Rsk Model of Long-Term Producton Schedulng n Open Pt Gold Mnng R Halatchev 1 and P Lever 2 ABSTRACT Open pt gold mnng s an mportant sector of the Australan mnng ndustry. It uses large amounts of nvestments,

### Kiel Institute for World Economics Duesternbrooker Weg 120 24105 Kiel (Germany) Kiel Working Paper No. 1120

Kel Insttute for World Economcs Duesternbrooker Weg 45 Kel (Germany) Kel Workng Paper No. Path Dependences n enture Captal Markets by Andrea Schertler July The responsblty for the contents of the workng

### PRIVATE SCHOOL CHOICE: THE EFFECTS OF RELIGIOUS AFFILIATION AND PARTICIPATION

PRIVATE SCHOOL CHOICE: THE EFFECTS OF RELIIOUS AFFILIATION AND PARTICIPATION Danny Cohen-Zada Department of Economcs, Ben-uron Unversty, Beer-Sheva 84105, Israel Wllam Sander Department of Economcs, DePaul

### A Novel Methodology of Working Capital Management for Large. Public Constructions by Using Fuzzy S-curve Regression

Novel Methodology of Workng Captal Management for Large Publc Constructons by Usng Fuzzy S-curve Regresson Cheng-Wu Chen, Morrs H. L. Wang and Tng-Ya Hseh Department of Cvl Engneerng, Natonal Central Unversty,

### Effect of a spectrum of relaxation times on the capillary thinning of a filament of elastic liquid

J. Non-Newtonan Flud Mech., 72 (1997) 31 53 Effect of a spectrum of relaxaton tmes on the capllary thnnng of a flament of elastc lqud V.M. Entov a, E.J. Hnch b, * a Laboratory of Appled Contnuum Mechancs,

### CHAPTER 14 MORE ABOUT REGRESSION

CHAPTER 14 MORE ABOUT REGRESSION We learned n Chapter 5 that often a straght lne descrbes the pattern of a relatonshp between two quanttatve varables. For nstance, n Example 5.1 we explored the relatonshp

### A hybrid global optimization algorithm based on parallel chaos optimization and outlook algorithm

Avalable onlne www.ocpr.com Journal of Chemcal and Pharmaceutcal Research, 2014, 6(7):1884-1889 Research Artcle ISSN : 0975-7384 CODEN(USA) : JCPRC5 A hybrd global optmzaton algorthm based on parallel

### Marginal Benefit Incidence Analysis Using a Single Cross-section of Data. Mohamed Ihsan Ajwad and Quentin Wodon 1. World Bank.

Margnal Beneft Incdence Analyss Usng a Sngle Cross-secton of Data Mohamed Ihsan Ajwad and uentn Wodon World Bank August 200 Abstract In a recent paper, Lanjouw and Ravallon proposed an attractve and smple

### Recurrence. 1 Definitions and main statements

Recurrence 1 Defntons and man statements Let X n, n = 0, 1, 2,... be a MC wth the state space S = (1, 2,...), transton probabltes p j = P {X n+1 = j X n = }, and the transton matrx P = (p j ),j S def.

### IMPACT ANALYSIS OF A CELLULAR PHONE

4 th ASA & μeta Internatonal Conference IMPACT AALYSIS OF A CELLULAR PHOE We Lu, 2 Hongy L Bejng FEAonlne Engneerng Co.,Ltd. Bejng, Chna ABSTRACT Drop test smulaton plays an mportant role n nvestgatng

### The Choice of Direct Dealing or Electronic Brokerage in Foreign Exchange Trading

The Choce of Drect Dealng or Electronc Brokerage n Foregn Exchange Tradng Mchael Melvn & Ln Wen Arzona State Unversty Introducton Electronc Brokerage n Foregn Exchange Start from a base of zero n 1992

### Optimal Customized Pricing in Competitive Settings

Optmal Customzed Prcng n Compettve Settngs Vshal Agrawal Industral & Systems Engneerng, Georga Insttute of Technology, Atlanta, Georga 30332 vshalagrawal@gatech.edu Mark Ferguson College of Management,

### Characterization of Assembly. Variation Analysis Methods. A Thesis. Presented to the. Department of Mechanical Engineering. Brigham Young University

Characterzaton of Assembly Varaton Analyss Methods A Thess Presented to the Department of Mechancal Engneerng Brgham Young Unversty In Partal Fulfllment of the Requrements for the Degree Master of Scence

### Comparison of Control Strategies for Shunt Active Power Filter under Different Load Conditions

Comparson of Control Strateges for Shunt Actve Power Flter under Dfferent Load Condtons Sanjay C. Patel 1, Tushar A. Patel 2 Lecturer, Electrcal Department, Government Polytechnc, alsad, Gujarat, Inda

### Fragility Based Rehabilitation Decision Analysis

.171. Fraglty Based Rehabltaton Decson Analyss Cagdas Kafal Graduate Student, School of Cvl and Envronmental Engneerng, Cornell Unversty Research Supervsor: rcea Grgoru, Professor Summary A method s presented

### 7.5. Present Value of an Annuity. Investigate

7.5 Present Value of an Annuty Owen and Anna are approachng retrement and are puttng ther fnances n order. They have worked hard and nvested ther earnngs so that they now have a large amount of money on

### IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS

IDENTIFICATION AND CORRECTION OF A COMMON ERROR IN GENERAL ANNUITY CALCULATIONS Chrs Deeley* Last revsed: September 22, 200 * Chrs Deeley s a Senor Lecturer n the School of Accountng, Charles Sturt Unversty,

### Application of Quasi Monte Carlo methods and Global Sensitivity Analysis in finance

Applcaton of Quas Monte Carlo methods and Global Senstvty Analyss n fnance Serge Kucherenko, Nlay Shah Imperal College London, UK skucherenko@mperalacuk Daro Czraky Barclays Captal DaroCzraky@barclayscaptalcom

### Customer Lifetime Value Modeling and Its Use for Customer Retention Planning

Customer Lfetme Value Modelng and Its Use for Customer Retenton Plannng Saharon Rosset Enat Neumann Ur Eck Nurt Vatnk Yzhak Idan Amdocs Ltd. 8 Hapnna St. Ra anana 43, Israel {saharonr, enatn, ureck, nurtv,

### Intra-year Cash Flow Patterns: A Simple Solution for an Unnecessary Appraisal Error

Intra-year Cash Flow Patterns: A Smple Soluton for an Unnecessary Apprasal Error By C. Donald Wggns (Professor of Accountng and Fnance, the Unversty of North Florda), B. Perry Woodsde (Assocate Professor

### Design and Development of a Security Evaluation Platform Based on International Standards

Internatonal Journal of Informatcs Socety, VOL.5, NO.2 (203) 7-80 7 Desgn and Development of a Securty Evaluaton Platform Based on Internatonal Standards Yuj Takahash and Yoshm Teshgawara Graduate School

### The Choice of Direct Dealing or Electronic Brokerage in Foreign Exchange Trading

The Choce of Drect Dealng or Electronc Brokerage n Foregn Exchange Tradng Mchael Melvn Arzona State Unversty & Ln Wen Unversty of Redlands MARKET PARTICIPANTS: Customers End-users Multnatonal frms Central

### A GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION

A GENERAL APPROACH FOR SECURITY MONITORING AND PREVENTIVE CONTROL OF NETWORKS WITH LARGE WIND POWER PRODUCTION Helena Vasconcelos INESC Porto hvasconcelos@nescportopt J N Fdalgo INESC Porto and FEUP jfdalgo@nescportopt

### To manage leave, meeting institutional requirements and treating individual staff members fairly and consistently.

Corporate Polces & Procedures Human Resources - Document CPP216 Leave Management Frst Produced: Current Verson: Past Revsons: Revew Cycle: Apples From: 09/09/09 26/10/12 09/09/09 3 years Immedately Authorsaton:

### A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION. Michael E. Kuhl Radhamés A. Tolentino-Peña

Proceedngs of the 2008 Wnter Smulaton Conference S. J. Mason, R. R. Hll, L. Mönch, O. Rose, T. Jefferson, J. W. Fowler eds. A DYNAMIC CRASHING METHOD FOR PROJECT MANAGEMENT USING SIMULATION-BASED OPTIMIZATION

### SPECIALIZED DAY TRADING - A NEW VIEW ON AN OLD GAME

August 7 - August 12, 2006 n Baden-Baden, Germany SPECIALIZED DAY TRADING - A NEW VIEW ON AN OLD GAME Vladmr Šmovć 1, and Vladmr Šmovć 2, PhD 1 Faculty of Electrcal Engneerng and Computng, Unska 3, 10000

### Management Quality, Financial and Investment Policies, and. Asymmetric Information

Management Qualty, Fnancal and Investment Polces, and Asymmetrc Informaton Thomas J. Chemmanur * Imants Paegls ** and Karen Smonyan *** Current verson: December 2007 * Professor of Fnance, Carroll School

### Traffic-light a stress test for life insurance provisions

MEMORANDUM Date 006-09-7 Authors Bengt von Bahr, Göran Ronge Traffc-lght a stress test for lfe nsurance provsons Fnansnspetonen P.O. Box 6750 SE-113 85 Stocholm [Sveavägen 167] Tel +46 8 787 80 00 Fax

### Politecnico di Torino. Porto Institutional Repository

Poltecnco d Torno Porto Insttutonal Repostory [Artcle] A cost-effectve cloud computng framework for acceleratng multmeda communcaton smulatons Orgnal Ctaton: D. Angel, E. Masala (2012). A cost-effectve

### Estimating the Effect of the Red Card in Soccer

Estmatng the Effect of the Red Card n Soccer When to Commt an Offense n Exchange for Preventng a Goal Opportunty Jan Vecer, Frantsek Koprva, Tomoyuk Ichba, Columba Unversty, Department of Statstcs, New

### Actuator forces in CFD: RANS and LES modeling in OpenFOAM

Home Search Collectons Journals About Contact us My IOPscence Actuator forces n CFD: RANS and LES modelng n OpenFOAM Ths content has been downloaded from IOPscence. Please scroll down to see the full text.

### Power-of-Two Policies for Single- Warehouse Multi-Retailer Inventory Systems with Order Frequency Discounts

Power-of-wo Polces for Sngle- Warehouse Mult-Retaler Inventory Systems wth Order Frequency Dscounts José A. Ventura Pennsylvana State Unversty (USA) Yale. Herer echnon Israel Insttute of echnology (Israel)

### A) 3.1 B) 3.3 C) 3.5 D) 3.7 E) 3.9 Solution.

ACTS 408 Instructor: Natala A. Humphreys SOLUTION TO HOMEWOR 4 Secton 7: Annutes whose payments follow a geometrc progresson. Secton 8: Annutes whose payments follow an arthmetc progresson. Problem Suppose

### On the pricing of illiquid options with Black-Scholes formula

7 th InternatonalScentfcConferenceManagngandModellngofFnancalRsks Ostrava VŠB-TU Ostrava, Faculty of Economcs, Department of Fnance 8 th 9 th September2014 On the prcng of llqud optons wth Black-Scholes

### 8 Algorithm for Binary Searching in Trees

8 Algorthm for Bnary Searchng n Trees In ths secton we present our algorthm for bnary searchng n trees. A crucal observaton employed by the algorthm s that ths problem can be effcently solved when the

Bandwdth Packng E. G. Coman, Jr. and A. L. Stolyar Bell Labs, Lucent Technologes Murray Hll, NJ 07974 fegc,stolyarg@research.bell-labs.com Abstract We model a server that allocates varyng amounts of bandwdth

### POLYSA: A Polynomial Algorithm for Non-binary Constraint Satisfaction Problems with and

POLYSA: A Polynomal Algorthm for Non-bnary Constrant Satsfacton Problems wth and Mguel A. Saldo, Federco Barber Dpto. Sstemas Informátcos y Computacón Unversdad Poltécnca de Valenca, Camno de Vera s/n