Cost Engineering Natural Gas plant

8/9/2019 Cost Engineering Natural Gas plant

1/34

Developments of Natural Gas Markets

T M C

XVII Gas Convention, AVPG, Caracas, Venezuela, May 23 - 25th, 2006 Page 0

ASOCIACION VENEZOLANA DE PROCESADORES DE GAS

XVII CONVENCIN INTERNACIONAL DEL GAS23 al 25 de mayo de 2006

Caracas, Venezuela

VVIIRRTTUUAALLPPLLAANNTTAAPPPPRROOAACCHHTTOODDEESSIIGGNN,,

EENNGGIINNEEEERRAANNDDPPRROOCCUURREEPPRROOJJEECCTTVVAALLUUEE

OOVVEERRTTHHEELLIIFFEECCYYCCLLEE

Luis Eduardo Nio Monr

Mariana Nio Rivero

TRANSITION MANAGEMENT CONSULTANTS VENEZUELA C.A.

Caracas, Venezuela


2/34



CONTENTS

ABSTRACT......................................................................................................................2

I. Introduction ..............................................................................................................3

II. Objectives ................................................................................................................5

III. Scope .......................................................................................................................7

IV. Designing and Simulating a Virtual Plant Model.......................................................8

V. Structuring a Capital Project Simulation Model ......................................................10

VI. Ten Steps to Design, Engineer and Procure Project Value....................................12

VII. A Practical Example: The Case Of a Natural Gas Liquid Extraction Project ..........15

VIII. Conclusions............................................................................................................32

IX. References Cited....................................................................................................32

X. Bibliography............................................................................................................33


3/34



ABSTRACT

Prevailing wisdom indicates that the economic value of a capital project is defined at

the front end and must be assured through its EPC phase. Value has been

traditionally measured in terms of expected financial returns on the associated capital

investment; todays concept, however, goes deeper into the roots of value to include

plant supply reliability and availability, cost competitiveness and client satisfaction.

In order to achieve the expected level of project value at the front end it is necessary

to measure the impact of the different options of equipment configuration and

specification on the net present value of the CAPEX, OPEX and revenue cashflows

over the total life cycle. Performing these analyses, with the necessary efficiency and

accuracy, demands however the use of proven computerized modeling and

simulation techniques designed to readily answer these questions through

appropriate performance indicators.

The objective of this paper is to demonstrate the validity and benefits of using a

Virtual Plant computer model throughout the projects conceptual development and

FEED phases in order to simulate and quantify the impact of the different design,

engineering and procurement options on the end project value.


4/34



I. Introduction

Capital projects represent the tangible version of a business idea when it

requires depreciable capital goods, designed and engineered to process andgenerate specific products to be sold for an expected profit. Given the

availability and cost of the required feedstock and the market and price for the

end products, the success of a capital venture depends on the capacity of the

process facility to adequately deliver products on time, volume, specification and

cost, in order to generate the expected shareholder value.

Sound analysis, on the other hand, supports prevailing wisdom in that the

economic value of a capital project is defined at the front end and must be

assured through its EPC phase. Value has been traditionally measured in terms

of expected financial returns on the associated capital investment; todays

concept of value, however, goes deeper into its own roots to include plant

supply reliability and availability, cost competitiveness and client satisfaction.

To be able to achieve the desired level of project value at the front end it is

necessary to measure the impact of the different options of equipment

configuration and specification on the net present value of the CAPEX, OPEX

and revenue cashflows over the total life cycle. Performing these analyses, with

the necessary efficiency and accuracy, demands however the use of proven

computerized modeling and simulation techniques designed to readily answer

these questions through appropriate performance indicators.

The authors objective is to demonstrate the validity and benefits of using a

Virtual Plant throughout the conceptual development and FEED phases in

order to simulate and quantify the impact of the different design, engineering

and procurement options on the end project value. A Virtual Plant is a

computerized mathematical model of the plant and equipment system, designed

to answer specific questions regarding the systems ability to adequately fulfill

the requirements of the demand through simulation techniques.


5/34



In order to achieve this purpose the authors will use the CAPITAL PROJECT

SIMULATION MODEL, CAPSIM, developed by their technical financial

consulting firm. CAPSIM is a comprehensive financial model that inserts the

Virtual Plant in the context of the CAPEX and OPEX environment that definesand quantifies the capital and operating costs associated with the modeled

system. These three components of CAPSIM interact with each other thus

allowing the engineer to select the equipment configuration, specification and

procurement options that maximize project value over its total life cycle.

The methodology to be used in order to demonstrate the validity of the approach

is based on the application of the following ten steps to a particular project:

1. Define plant adequate operation conditions

2. Design the Process Technology Model

3. Identify critical equipment functions

4. Select configuration arrangements for each critical equipment function

5. Design and validate the Conceptual Development Model

6. Specify equipment and issue Requests for Quotations

7. Select the most cost effective proposals

8. Design and validate the FEED Model

9. Issue Purchase Orders to selected vendors

10. Complete and freeze basic engineering and perform comprehensive risk

analyses

In this paper the authors use a natural gas liquid extraction project as an

example to demonstrate the value enhancement capabilities of the proposed

approach.


6/34



II. Objectives

The objective of this paper is to demonstrate the validity and benefits of using a

Virtual Plant computer model throughout the conceptual development and

FEED phases in order to simulate and quantify the impact of the different

design, engineering and procurement options on the end project value.

The proposed Virtual Plant approach constitutes a fundamental tool for this

purpose due to its capacity to model a specific plant and equipment system and

simulate its behavior over the projects life cycle. The systems mathematical

model is designed using process engineering information and defines the

functional relationship between equipment availability and the systemsproduction capacity; equipment availability is simulated using appropriate

reliability and maintainability probability density functions thus enabling the

model to process the performance indicators associated with the systems

production effectiveness and supply reliability and availability.

To achieve this objective the authors will use the CAPITAL PROJECT

SIMULATION MODEL, CAPSIM, a comprehensive financial computer model

that inserts the Virtual Plant model in the context of the CAPEX and OPEXenvironment that defines and quantifies the capital and operating costs

associated with the modeled system, thus allowing the technical and economic

analysis and evaluation of design, engineering and procurement decisions over

the projects life cycle.

The Figure 1 is graphical description of the structure of the CAPSIMmodel.


7/34



Figure 1 The CAPSIMModel

The three modules of CAPSIMinteract with each other in order to generate the

fundamental performance indicators of project value from the standpoint of the

internal, external and financial strategic perspectives of the capital venture, at its

different stages of development throughout the life cycle.

The CAPEX cash flows are determined based on information obtained from the

appropriate class estimates and project execution schedules while the OPEX

cash flows are determined using the models own simulation results and

statistical operation and maintenance costs profiles.

Revenue cash flows and penalty costs can be calculated by associating

simulated production volumes and product price forecasts over the life cycle.


8/34



III. Scope

Given the availability and cost of the required feedstock and the market and

prices for the end products, the success of a capital venture depends

fundamentally on the capacity of the process facility to adequately meet demand

conditions at the right production cost. This paper will in consequence deal with

the root attributes that in essence define project value; that is, those associated

with plants ability to meet the adequate operation conditions set by the projects

business drivers.

These root attributes are defined in terms of internal and external performance

indicators that measure the plants capacity to reliably deliver products to clientsin the required volume and specification, and at adequate unit production costs.

The following are some of the root performance indicators that can be generated

by CAPSIMat the conceptual and FEED phases of a project:

1. Internal, plant performance

Total production

Total revenue

Average production

Production effectiveness

Production losses

Mean production loss per interruption

Penalty costs for lost production

Systems ownership cost

Unit production costs


9/34



2. External, service quality

Mean time between (adequate operation) interruptions, MTBI

Mean interruption time, MIT

Supply reliability, Rs

Supply availability, As

All these indicators are essential requirements to properly measure the financial

performance the project through appropriate indicators such as:

1. Internal Rate of Return, IRR

2. Net Present Value, NPV

IV. Designing and Simulating a Virtual Plant Model

The proposed Virtual Plant approach constitutes a fundamental tool due to its

capacity to model a specific plant and equipment system and simulate its

behavior over the projects life cycle. The systems mathematical model is

designed using process engineering information and defines the functional

relationship between equipment availability and the systems production

capacity; equipment availability is simulated using appropriate reliability and

maintainability probability density functions thus enabling the model to process

the required performance indicators associated with production effectiveness

and supply reliability and availability.

Virtual Plant models are used to support design and engineering efforts as wellas to audit resulting and/or existing design and engineering proposals, at any

level of development of a project. When they are used at the project

development concept phase we call them Process Technology (PT) models; if at

conceptual design level we call them Concept Development (CD) models and

FEED models when used at the front end loading phase.


10/34



Virtual Plant models can be upgraded as the level of precision increases

through detailed engineering to as built drawings in order to expand its use into

the asset management phase of the project. At the detailed engineering level

these models represent a valuable low cost virtual project debottlenecking tool.

Virtual plants are useful at any moment during the development of a capital

project. We have used them in consulting engagements for several capital

projects in the energy sector, mostly oil and gas, during the following phases of

development:

1. Project Conceptualization

2. Concept Development

3. FEED

4. Detailed engineering

5. Procurement

6. O&M

For the gas sector in particular we have used them in consulting engagements

at different stages of the value chain:

1. Gas compression and transmission

2. Gas liquids extraction

3. Gas liquids fractionation

4. Ethane compression and transmission

The following steps are required to design and simulate a Virtual Plant model

from existing process engineering data:


11/34



1. Define the systems battery limits

2. Establish its Adequate Operation Conditions, AOCs

3. Design a functional model of the system using process flow diagrams

4. Quantify plant production capacity for the different productive states of the

system

5. Estimate the reliability, availability and maintainability (RAM) parameters of

equipment functions or positions included in the model

6. Simulate the systems internal and external performance indicators

7. Compare simulation results with established AOCs

8. Identify systems effectiveness and reliability risks areas

9. Identify areas of potential system value enhancement

10. If required, apply CAPSIM in order to choose most economic options to

mitigate risk or enhance value

RAM equipment estimates can be obtained from sources such as statistical

failure and repair data from similar equipment or using industry sources such as

the Offshore Reliability Data Handbook, OREDA [1].

These steps will be documented as part of a practical example to be developed

later in this paper.

V. Structuring a Capital Project Simulation Model

When inserted within the framework of CAPSIM, the Virtual Plant becomes its

Performance Module and can now be used to technically and economically

evaluate design, engineering and procurement options in order to enhance

project value or for mitigation of effectiveness and reliability risk areas.


12/34



CAPSIMexpands the scope of the Virtual Plant capabilities by adding to it the

capacity to incorporate the time value of money in the analyses and to generate

financial performance indicators. On the other hand, the insertion of the Virtual

Plant model in CAPSIM actually empowers the intrinsic capacities of thetraditional CAPEX/OPEX model by adding to it the ability to interact with the

plant itself.

The CAPEX capital cashflows are determined based on information obtained

from the appropriate class estimates and project execution schedules while the

OPEX expense cashflows are determined using the virtual models own

simulation results and statistical operation and maintenance costs profiles.

Revenue cashflows and penalty costs can be calculated by associating

simulated production volumes and product price forecasts over the life cycle.

By adequately structuring its PERFORMANCE, CAPEX and OPEX Modules,

CAPSIM is capable of generating all the internal, external and financial

performance indicators associated with the system being modeled.

CAPSIMhas been used for projects in the gas industry mostly in the area of

analysis of procurement options.

The following information is required in order to structure the CAPEX Module of

CAPSIM:

1. Installed capacity

2. Equipment costs

3. Engineering and construction costs

4. Commissioning and start up costs

5. Project work schedules

The following data should be provided to set up the OPEX Module:


13/34



1. Mean equipment unscheduled repair costs

2. Mean equipment inspection cost and frequency

3. Mean equipment overhaul cost and frequency

4. Operating costs

The process of structuring these modules will be documented through a

practical example to be developed later in this paper.

VI. Ten Steps to Design, Engineer and Procure Project Value

The authors propose ten steps in order to design, engineer and procure the

expected project value at the frond end:


From the projects development concept define the physical scope of the

plant system to be analyzed as well as any other system outside the battery

limits that may affect its behavior.

The systems applicable adequate operation conditions are, for example:

Volume of products to be supplied

Supply reliability and availability

Allowable mean time between interruptions of adequate supply


14/34



Allowable mean penalty cost per interruption

Unit production cost


From the Project Development Concept process information, design a

Process Technology (PT) Model of the plant system using process

information data at the equipment function level.


Using appropriate estimates of equipment function reliability, maintainability

and availability (RAM) parameters, simulate the system effectiveness as

well as the supply reliability and availability of the PT Model and, based on

the definition of adequate operation conditions of the plant system, identify

critical equipment functions.

Critical functions are defined based on impact in number and duration of

adequate operation interruptions and ranked as well as in terms of

production losses per interruption.


Identify the different equipment configuration options to be considered for

each critical equipment function and use CAPSIM to select the most cost

effective configuration using appropriate RAM attributes and cost estimates.

Equipment RAM estimates can be obtained from sources such as statistical

failure and repair data from similar equipment or using the OREDA [1]

database. Class 1 cost estimates, +40% to -30%, for CAPEX and OPEX are

sufficient at this stage of analysis.



15/34



Upgrade the PT Model into a Conceptual Development (CD) Model using

the selected equipment configurations, and use CAPSIM to simulate

results and validate fulfillment of system adequate operation conditions.

If fulfillment is not validated, review and revise the equipment configuration

analyses and selection performed in step 4 and repeat the process until

validation is confirmed.

6. Specify equipment and issue requests for quotations

Based on the approved configuration arrangements, generate engineering

and RAM specifications for the different equipment procurement processes

to be initiated and issue the corresponding Requests for Quotations (RFQs)

to selected bidders.

RFQs must specifically request that bidders provide information related to

their estimates of equipment failure and repair rates as well as maintenance

and operation costs of proposed equipment. Recommended scheduled

maintenance policies should be also quantified in terms of frequency and

cost.

7. Select most cost effective proposals

Analyze and compare bids using CAPSIM and select the most cost

effective proposals based on actual bid cost and RAM data.

Class 2 cost estimates, +20% to -10% for installation hook up and

commissioning of equipment systems are required at this stage of analysis.

8. Design and validate the FEED model

Upgrade the CD Model into a Front End Engineering Design (FEED) Model

and run a full CAPSIManalysis, using the selected proposals, in order to

validate fulfillment of system adequate operation conditions.


16/34



If fulfillment is not validated, review and revise the bid analyses and

selection performed in step 7 and repeat the process until validation is

confirmed.

In case of selecting proposals from different manufactures, measure the

cost and benefits of equipment standardization.


Issue Purchase Orders (POs) to selected equipment suppliers.


analyses

VII. A Practical Example: The Case Of a Natural Gas Liquid Extraction Project

To illustrate the proposed process in this paper we will analyze the case of a

natural gas liquid extraction project proposed to supply the ethane requirements

of new ethylene plant.

The business idea

Presently there is a current of 950 MMSCFD of wet production associated gas

being used to provide fuel gas to an existing refinery and for transmission and

distribution of natural gas for domestic and industrial consumers.

The business idea is to extract the natural gas liquids by installing a new liquid

extraction facility on ethane extraction mode in order to sell 40.000 BPD of

ethane to a new ethylene plant.

The remaining NGL would be processed in an existing fractionation facility.

The residue gas produced by the new extraction facility would be used to satisfy

the requirements the refinery and the domestic and industrial clients.


17/34



The economic value of the proposed project is to be estimated considering only

the revenue coming from the sale of ethane. Penalty cost for lost production has

been established at 35 US$/barrel.

The Project Development Concept

Figure 2 shows the approved Project Development Concept using two 2

extraction trains in parallel with a capacity to produce 20.000 BPD of ethane

each at 90% ethane recovery.

Figure 2 Project Development Concept


18/34



Apply the ten steps process to design, engineer and procure project value

at the front end






6. Specify equipment and issue Requests for Quotations

7. Select most cost effective proposals

8. Design and validate the FEED Model



analyses

Step 1 - Define plant adequate operation conditions

To operate adequately the new extraction plant must be able to deliver 40.000

BPD of ethane in specification at least 97.5 % of the time with a maximum

permissible interruption time of 36 hrs.

Step 2 - Design the Process Technology Model

Figure 3 shows the PT model to be simulated in order to identify critical

equipment functions.


19/34



Turboexpansion

Demethanization

Chargepumping

Deethanization

Refluxpumping

Extraction Train 1

Turboexpansion

Demethanization

Chargepumping

Deethanization

Refluxpumping

Extraction Train 2

Hot oilpumping

Propanecompression

Residue gascompression

Ethanecompression

Figure 3 Process Technology Model

Step 3 - Identify critical equipment functions

Figure 4 shows the results of simulating the PT model at the Plant and

Equipment Function levels. The criteria chosen to rank equipment function

criticality was % of lost production.

The results of the simulation indicate that 59.61% of the lost production is

associated with the three process compressor equipment functions. The

simulated results also indicate that the PT model has a supply availability of

94.46%, below the 97.5% established in the AOCs.

Equipment configuration analyses will be performed in the next step in order to

define the most effective compressor configurations for each service required in

order to increase system supply reliability to at least 97.5%


20/34



Table I shows the RAM parameters applied to each equipment function in order

to simulate the results presented in Figure 4.

Table I RAM parameters PT Model

Mean Time BetweenFailures MTBF (hours)

Mean Time Down - MTD(hours)

Compressors 1,100.00 10.00

Turbo expanders 2,150.00 8.00

Pumps 1,500.00 6.00

Vessels 20,000.00 40.00

In this paper the Weibull distribution will be used for all reliability and

maintainability simulations, using values of the shape parameter, equal to 1.00

and 2.50 respectively.

Step 4 - Select configuration arrangements for each critical equipment

function

Table II shows the process design operating conditions for each one of the

different compressor equipment functions to be configured.

Table II Compressor operating conditions

Service Ethane Propane Residue gas

Flow (MMSCFD) 68 190 800

Inlet temperature (F) 45 36 122

Inlet pressure (psig) 415 62 500

Discharge pressure(psig) 780 250 1,300


21/34



Figure 4 - Critical Equipment Function Identification


22/34



Figures 5, 6 and 7 show the results of the configuration analysis for the different

compressor equipment functions. The performance indicators to be used for

selection of configurations are Production Effectiveness and Mean Production

Loss per Interruption due to their direct impact on ethane production.

The results presented in the above mentioned figures indicate that for all

equipment functions the best configuration arrangement is 3x50%. In the next

step these configurations will be validated by inserting them into the model in

order to generate the required simulation results at the plant level.

Table III shows the input data used in order to model, simulate and evaluate the

indicated configurations for each equipment function using electric motor driven

centrifugal compressors.


23/34



Table III CAPSIMinput data

Ethane Propane

Configuration option 2 x 60% 3 x 50% 2 x 60% 3 x

Equipment cost MMUS$ 5.04 6.83 12.23

Construction costs MMUS$ 15.12 20.48 36.68

TOTAL CAPEX MMUS$ 20.16 27.30 48.91

Operation costs

Annual operation costs US$/yr 290,155 424,023 313,413 45

Annual maintenance costs US$/yr 193,437 282,682 208,942 30

TOTAL OPEX US$/yr 483,592 706,704 522,355 75

Maintenance costs parameters

Mean cost per failure US$ 10,000 10,000 10,000 1

Mean cost per inspection US$ 19,500 16,250 24,300 2

Mean cost per overhaul US$ 117,000 100,750 178,200 14

RAM parameters

Mean Time Between Failures MTBF hrs 1,100 1,100 1,100

Mean Time Down - MTD hrs 10 10 10

Scheduled maintenance data

Mean Time Between Inspection - MTBIN hrs 40,000 40,000 40,000 4

Mean Inspection Time - MINT hrs 19.5 16.25 24.3Mean Time Between Overhauls - MTBOH hrs 80,000 80,000 80,000 8

Mean Overhaul Time - MOHT hrs 117 100.75 178.2


24/34



Figure 5 Equipment Configuration Analysis Ethane Compression


25/34



Figure 6 - Equipment Configuration Analysis Propane Compressio


26/34



Figure 7 - Equipment Configuration Analysis Residue Gas Compr


27/34



Step 5 - Design and validate the Conceptual Development Model

Figure 8 shows the results of simulating the CD model using only the selected

configurations

Figure 9 shows the results of simulating the CD model using all possible mixes

of configurations for the three compressor equipment functions.

Figure 10 shows the results of simulating the CD model using the selected

configurations together with the rest of equipment functions.

The results of the first simulation validates that the selected configurations

indeed have the capacity to meet and exceed AOCs while the second

simulation confirms that of all configuration schemes the 3x50% is definitely the

best option.

The results of the third simulation however indicate that the CD model is still not

meeting supply availability requirements and that further configuration analyses

must be performed in other equipment functions, such as hot oil pumping, in

order for the system to operate adequately.

Step 6 - Specify equipment and issue Requests for Quotations

Based on the approved configuration arrangements, generate engineering and

RAM specifications for the different early equipment procurement processes to

be initiated and issue the corresponding Requests for Quotations (RFQs) to

selected bidders.

RFQs must specifically request that bidders provide information related to theirestimates of equipment failure and repair rates as well as maintenance and

operation costs of proposed equipment. Recommended scheduled maintenance

policies should be also quantified in terms of frequency and cost.


28/34



Step 7 - Select the most cost effective proposals

Figure 11 shows the results of simulating bids from suppliers A, B and C for the

propane compressors. Using the same criteria applied for configuration selection

the bid from supplier B was selected.

The same procedure has to be applied to the rest of the equipment items to be

early procured.

Step 8 - Design and validate the FEED Model

Upgrade the CD Model into a Front End Engineering Design (FEED) Model and

run a full CAPSIManalysis, using the selected proposals, in order to validate

fulfillment of system adequate operation conditions.

If fulfillment is not validated, review and revise the bid analyses and selection

performed in step 7 as well as detected effectiveness and reliability risk areas

and repeat the process until validation is confirmed.

In case of selecting proposals from different manufactures, measure the cost

and benefits of the different options of equipment standardization.

Step 9 - Issue Purchase Orders to selected vendors

Issue Purchase Orders (POs) to selected equipment suppliers

Step 10 - Complete and freeze basic engineering and perform

comprehensive risk analyses


29/34



Figure 8 Configuration Validation, selected options


30/34



Figure 9 Configuration Validation, all options


31/34



Figure 10 CD Model Validation


32/34



Figure 11 Bid Analysis


33/34



VIII. Conclusions

The discussion regarding project investment strategies has traditionally spun

heavily around the costs and benefits of investing in equipment reliability andmaintainability. Between those who preach that the benefits are there and those

who think that the numbers are not sufficiently substantiated to support the

lobbying effort for the extra capital required.

We believe that the missing links thus far have been the resources and

capabilities to assess the impact that investment decisions at the equipment

level have on the end financial results of the capital venture.

What we have presented in this paper is precisely an approach that allows the

analysts to not only evaluate the stand alone behavior of an equipment system

but, more importantly, to measure its impact on the fulfillment of the plant

performance and service quality indicators that are at the root of end project

value.

It is our conclusion that the proposed procedure and its practical application

show the strength and validity of the use of a Virtual Plant approach to design,engineer and procure project value at the front end. It also shows the

importance of performing these analyses before equipment early procurement

efforts are otherwise initiated.

We cannot, on the other hand, overemphasize the importance of assuring the

resulting project value throughout the intensive time and cost dominated EPC

phase of the project. That is, if the shareholders want to receive the plant they

bet their money on.

IX. References Cited

1. OREDA Offshore Reliability Handbook, 4th Edition, OREDA Participants,

2002


34/34


X. Bibliography

1. Guidelines for Improving Plant Reliability through Data Collection and

Analysis, American Institute of Chemical Engineers, 1998

2. John W. Hackney, Control and Management of Capital Projects, John Wiley

& Sons, Inc., 1965

3. Nio, L.E. and Nio M., Modeling and Simulation of Capital Projects: How

to assure successful investments in the energy sector, Venezuelan

Association of Gas Processors, AVPG, XVI International Gas Convention,

Caracas, Venezuela, May 2004

4. Nio, L.E., Management of Capital Projects: A Value Approach, Project

Management Institute, 3rd. Iberoamerican Project Management Congress,

Caracas, Venezuela. July 2002

Cost Engineering Natural Gas plant

Documents

Transcript of Cost Engineering Natural Gas plant