aspen planning and scheduling seminar

1

© 2010 Aspen Technology, Inc. All rights reserved |

1

Agenda (17th & 18th Sep)

– Refinery Industry Vision

– Overview of PIMS software

– Demonstrate Planning activities using Aspen PIMS

– Discuss & demonstrate Audit findings of BORL PIMS Model and improvements

– Refinery Scheduling and its significance

– Q&A


2

Plan vs Actual gap: Issues & its sources

85%

90%

95%

100%

105%

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31

Gro

ss M

arg

in (

% o

f th

e p

lan

)

December

Plan vs. Actual Analysis

Planned Profit Actual Daily Profit Average Reconciled Actual Profit

5-1

0%

How do you control and reduce your reconciled gap?

This could be costing you

millions/month

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3

Issue 1: No methodology to analyze it.

Inventory

Gap

General Operations Issues

Operational & Hardware Trouble

Variant Constraints

Blending Issues

Off-spec &

reprocessing

Non-economic blending

Logistics Constraints

Improper timing of unloading or shipping Pipeline

Occupation

• There is no or limited KPI and visualization(notification). • It is hard to find its reasons and resolution with logical frame.

Schedule vs Operations Differences

Process model inconsistency

Demand Qty,

Mode Change

Change OP. Conditions.


4

Report on Findings Manual data mapping, correlation and analysis

Issue 2 : Performance appraisal process is manual

Manual Data Collection

Analyst

Laboratory (Quality)

Marketing (pricing)

Yield Accounting

Planning

Operations Accounting

Scheduling / Blending

1 – 2 Weeks

Summary

Manual process

- Very time intensive

- Very complex

- Requires expertise

Prone to error

- Data manually mapped and interpreted each time

- Potential for missed analysis

- Inconsistent results

Purely retrospective

- Identify issues that may have occurred 10-40 days ago

- Bleeding profits during this time

3


5

Issue 3 : No Common Communication and Method to solve issue.

Management

Process Department Operations Planning & Scheduling Performance Mgmt

Why are we not

performing to plan?

I don’t know, I’m still

collecting data

Plan from HQ is

unrealistic, we will

never reach the plan

You are giving me

continuously changing

targets Your LP models are not

representing the reality


6

Refinery Industry Vision

Margin Maximization by setting the KPI’s for :

Crude and feedstock supply

Product slate

Crude/Product logistics

Refinery asset utilization

Decision support on margin & cash-flow

Maximize margins from Refining Business

Margin Management

Primary

Distribution

Crude

Chartering/logistics

Refining Blending Crude

Trading

4


7

What are Typical Planning Horizons ?

Long term (1-5 years or more) – Strategic investment planning – Supply/demand strategy – New units/debottlenecking

Medium term (up to 18 months)

– Six-quarter rolling plan/annual budget

– Feedstock selection

– Product market targets

Short term (up to 3 months)

– Plant optimization

– Inventory management

– Products blending

Immediate

– Production planning

– Performance monitoring


8

Refinery Model

(Aspen PIMS)

Plan Recommendations

Crude selection.

Crude indifference values.

Crude arrival sequencing

Production plan.

Marketing plan

Operating strategies

Constraints

Processing constraints

Blending constraints

Inventory levels.

Feed availability

Product demand

Export term contracts

Product specifications

Refinery Process Models

Base vectors

Shift vectors

Stream property data

Drivers

Performance targets

KPIs

Scheduling

Economics

Feed-stock prices

Product prices

Data flow in Planning

5

© 2010 Aspen Technology, Inc. All rights reserved

Dharmendra Sah, Principal Business Consultant

17th & 18th Sep 2012

Aspen PIMS™ Seminar

Advanced Refinery Planning for Better and quicker Decision Making


10

Agenda

Refinery Best Practices

Planning Key Activities

Why Refinery Planning

The Basics

LP Concepts

PIMS Features & Options

Study Areas

Optimization Areas / Economic Studies / Profit Improvement Plans / Investment Options

When to use Aspen PIMS

Aspen Petroleum Scheduler

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11

Refining Best Practises

Emphasis on operational excellence

Lowering of feedstock acquisition costs

Increasing use of technology

Better utilization of supply chain assets


12

Aspen Solutions in Space and Time to support Industry Best Practices

Daily Weekly Seasonal Annual

Ou

tsid

e

the

Fe

nce

Geogra

phy

Insid

e

Th

e F

en

ce

M

ark

et

Wid

e

Primary Distribution (IMOS)

Historical

Refinery Planning (PIMS)

Refinery Scheduling

(APS)

Collaborative Demand Manager

(CDM)

Yield Accounting (Advisor)

Fleet Optimizer

(AFO)

Distribution Planning

(DPO/PSCP)

TIME

7


13

Selects Crudes

Plans Operations

Optimizes Sets

Targets for schedulers

Delivers profits

What is PIMS?

Planning


14

Schedules Crude

Schedules Units

Schedules &

Optimizes Blends

Sets Targets for Operations

Delivers profits

What is APS and MBO?

Scheduling

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15

Leaders in Planning & Scheduling

70%

11% 9%

10%

PIMS Honeywell

Haverly No/Unknown

36%

7% 0% 0%

55%

APS

M3

Honeywell

Haverly

Excel based/Unknown

Planning Scheduling


16

Refinery Planning Key Activities

Evaluate Crude Feedstocks

Create Regional Plan

Create Production Plan

Maintain On-going Models

Create Long-Term Strategic Plan

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17

Why Refinery Planning ??

Monthly Refinery Operating Plan

– Determine next month’s production plan for feedstock, operating parameters, modes of operation, blend flexibility, and sales

– Shutdown planning

– Inventory optimization

– Cost of constraint

– Cost of QGA

Performance Management

– Compare plan vs. actual operation for on-going improvement

Capital Investment and Long-Term Plan

– Decide whether to invest in new plant or shutdown assets

– Determine production plans for multiple months or years

– Technology evaluation

Feedstock Evaluation

– Requires running dozens or hundreds of scenarios to evaluate optimal purchases and sales



The Basics

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19

aspenONE Application Integration

aspenONE Planning & Scheduling is a Key Component of Integrated Supply Chain Management…

Collaborativ

e Demand

Mgmt (CDM)

ERP

Historical

Demand

30/60/90Day

Inventory Mgmt

& Operations

Scheduling

Demand

•Product

•Date

•Location

•Channel

of Trade

30/60/90Day

Actualized Movements

Daily

3rd Party Nominations

-Pipeline Companies

-Vessel Providers

-Inspection Companies

-Rail

Terminal

Inventories

Daily

Secondary

Distribution

(Retail)

Short

Term

Demand

Next 50 lifting

Deal

Capture Deals – Spot,

Term, Exchange

Daily

Production Plan

30/60/90/120

Day

Refinery

Planning

Fwd

Demand

Terminal Demand

& Inventories

30 Day Distribution

Planning

Transportation Loading

Plan (Sourcing priorities

for a given location)

30 Day

Product Nominations &

Scheduled movements

Daily

Production Schedule, Refinery

Inventories

30/60/90/120 Day Refinery

Scheduling

Production Plan

Long Term &

Short Term

30/60/90/120 Day


20

Operational Excellence – The Next Challenge

Supply Chain Engineering Manufacturing

Demand

Concept

Operations

Supply

Plan

Produce

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What is Aspen PIMS?

Process Industry Modeling System

LP-based Optimization Tool, but it can handle non-linearity as well.

Short-Term and Long-Term Economic Evaluations

Primary Applications in Petroleum, Petrochemical, and Related Industries

Offers the flexibility of a scalable, single or multi-user system that facilitates enterprise-wide planning for refineries and petrochemical industries

Solve for single / multi-plant and single / multi-period planning requirements

Uses spreadsheet or data tables for data input

Standard PIMS reports and custom reports using ARW

Multi case capability and comparability reporting


22

Background

• Development began in Oct.,1984 based PC

• Presented at the 1985 NPRA Computer Conference

• First Site : Phibro Texas City, Nov. 1985

• Today, more than 300 petroleum, petrochemical and engineering companies (over 500 sites) use Aspen PIMS suite of software for planning and scheduling

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23

How is PIMS Used?

Aspen PIMS is a powerful LP optimization tool for economic planning in the Process Industries.

The main applications of PIMS in Refinery are:

– Optimized production plan (short term and long term)

– Feed stock optimization / product mix optimization

– Product blending formulation

– Planning of feedstock and product inventory

– Strategic or tactical decision support

– Back Casting / Performance Monitoring

– Evaluation of various alternate economic scenarios for nil or minor modifications within existing facilities

– Technology evaluation

– New plant / Refinery configuration

– Sizing of plant units in grass root as well as expansion studies

– Feed Stock costing / New product pricing


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Who* Uses PIMS ?

• BP

• Exxon/Mobil

• Shell

• Marathon

• Valero

• COP

• Pemex

• Adnoc

• Aramco

• Total

• Bapco

• McKenzie

• Basf

• Bechtel

• Jacobs

• Chevron (Caltex)

• Citgo

• Pdvsa

• Jacobs

• Petrobras

• Petronas

• Premcor

• Repsol

• Sinopec

• Statoil

• Sunoco

• Tesoro

• Murphy

• Hpcl

• Lyondell

• Ecopetrol

• Bpcl

• Giant

• Koa

• FlintHills

• Fortum

• Alon

• HMEL

• NRL

* Partial List – Over 450 Sites

13



LP Concepts


26

LP Concept

Objective Function = Products - Raw Materials - Utilities - Catalysts - Chemicals -

Labor - Any Other Costs - Penalties

Subject to Linear Constraints

Raw Material Limits

Product Limits

Capacities

Specifications

Other Constraints

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27

Simplified LP problem

I have a plant that produces RUL, RUP and FOL. There are 3 Crudes available with the following yields: Yield From Crude A B C PRICE ($/bbl) RUL 50% 20% 20% 90 RUP 20% 50% 20% 100 FOL 30% 30% 60% 50 Cost Crude ($/bbl) 60 65 55 In addition, the plant can only produce 120k Bbls of RUL and RUP and 60K Bbls of FOL


28

Simplified LP problem

LINEAR EQUATIONS:

RUL = .5 * A + .2 * B + .2 * C

RUP = .2 * A + .5 * B + .2 * C

FOL = .3 * A + .3 * B + .6 * C

Constraint 1: RUL + RUP < 120

Constraint 2: FOL < 60

Maximize Objective Function: 90 * RUL + 100 * RUP + 50 FOL - 60 * A - 65 * B - 55 * C

15


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Single feedstock economics Case A B C

OBJECTIVE FUNCTION VALUE 3428.6 3085.7 1300.0

Yield

RUL 0.5 0.2 0.2

RUP 0.2 0.5 0.2

FOL 0.3 0.3 0.6

Margin 20.0 18.0 13.0

FEEDSTOCK PURCHASES

AAA 171.4

BBB 171.4

CCC 100.0

PRODUCT SALES

RUL 85.7 34.3 20.0

RUP 34.3 85.7 20.0

FOL 51.4 51.4 60.0

CAPACITY UTILIZATION

RUL & RUP Limit 120.0 120.0 40.0

FUEL OIL LIMIT 51.4 51.4 60.0


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Optimum Economics

16



PIMS Features


32

What are Key PIMS Features?

Powerful non-linear distributive recursion

Automated flowsheeting

Comprehensive diagnostics

Sophisticated blending technology

Powerful optimization engine

Integrate with Rigorous Process Simulator for greater fidelity

Builds realistic and credible models

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33

What is a PIMS Model ?

A Set of Data Tables (Spreadsheets) Define the Model

Data Tables Have a Prescribed Form

Data Tables Can Be a Single Spreadsheet, a Sheet From a Multi-sheet Table

A Data Table Can Be Shared by Models or Be in a Library

A Model Is a Subdirectory Under the PIMS (Home Directory)

Base PIMS includes PIMS, ABML, PPIMS, MIP, REPORT WRITER


34

What Are Data Sources for Configuring a New PIMS Model?

Old LP model database

Current and historic plant data

Process unit simulators

Licensor data

Published, public domain data

Generic databases

– Refinery technology database delivered with PIMS

– Crude assay databases such as BP or Chevron (separately licensed)

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35

What Data Is Included with PIMS?

Delivered with system in the form of sample models / data libraries

Process units

– Reforming, Isomerization

– Hydrocracking, Catalytic Cracking

– Alkylation, Coking

Property index correlations

Typical physical property data


36

PIMS Sample Models

WEIGHT VOLUME MIP RFG LIBRARY

PIMS SAMPLE VOLSAMP MIPSAMP VOLRFG PETROLIB

PCHEMLIB

PPIMS PSAMPLE PVOLSAMP PMIPSAMP PVOLRFG

MPIMS MODELA

MODELB

GLOBAL

MIPA

MIPB MIPG

XPIMS XMODELA

XMODELB

XGLOBAL

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The PIMS Work flow

VALIDATION & MATRIX GENERATION

DATA

MANAGER MENUS

SOLUTION

REPORTS RECURSION OPTIMIZATION

PIMS EXCEL

Non-Converged

PIMS

XPRESS PIMS PIMS

SummarySolution.LST

FullSolution.LST

IterationLog.LST PrimalDual.LST


38

Why You Have Recursion – The Pooling Problem

Tank

Stream A at 10 with

a quality of 20

Stream B at 20

with a quality of 10

Product from Tank,

Flow at 30 with quality

of 13.334

• Quality is an average. Average implies division.

• LPs Do not divide, only add, subtract and multiply.

• How do you divide in an LP.

• Guess quality, Solve LP, then compare guess to actual.

• The Pooling Problem.

20



PIMS Options


40

Solution Tracking Data Assistance

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41

HTML Reports

Synchronized Scrolling The synchronized scrolling feature is now available with the Go to command.


42

Enhancement of Data Assistances

22


43

43

Use of KPI’s

* TABLE SOLNKPIS

* Solution KPIs

TEXT YELLOW RED ***

*

CCAPCCU Cat Cracker Capacity 32 30

ZLIMSEV Reformer Severity 96 100

PURCARL Purchased Arab Light 55 20

MARGVALU Marginal Values 1.00E+03 1.00E+06

XRVIURG RVI of Unleaded Regular 15 13

*** End

Table of Contents


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44

First Time

Period

Second Time

Period

Third Time

Period

Inventory

Inventory

PPIMS Periodic PIMS

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45

Aspen Report Writer

What does it do? – Provides a Excel Add-in which implements new cell functions that

can be used in template workbooks to design report images

– Provides a function wizard to help create the Report Writer add-in functions in a template workbook

– Provides an execution interface to create a finished report workbook from a template workbook

Report Writer


46

MIP - Mixed Integer Programming

Typical modeling uses are:

– Mutually exclusive process operations, such as ... Feeds from multiple tanks requiring use of a common

feed pipe Model real blender capability where there are more

components than available pumps

– Threshold purchases/sales, such as ... Pipeline tenders or tanker shipments

– Threshold process throughputs, such as ... zero or minimum blending rate for specific components Minimum blend size Minimum turn down rate

MIP

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47

47

MIP


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Powerful Modeling and Visualization

Accurate representation of refinery operations

– Use real tower crude assay data

– Support various modeling for process submodels

– Sophisticated blending technology

Powerful optimization technology

– Non-linear distributive recursion

– Extended SLP

Automated flowsheeting

Global Optimization with Parallel Processing

Various Reports (Text, HTML, Excel, DB) and customized reports by Aspen RW

Multiple periods and sites optimization

Solution KPIs and comprehensive diagnostics

Determines optimal economic breakpoint for shifting refinery operating mode

Integration between Planning and Scheduling

Aspen PIMS™ Family

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49

Synergies of an integrated approach based on a Common Model Environment (CME)

Improve PIMS models

Integrated Refinery

Scheduling & Blend

Optimization

Rigorous Simulation

Improving shared sub-models provides more accurate planning & scheduling.

RefSys models can be used to provide data to retune shared P&S models as

necessary

APS has functionality to monitor model accuracy on ongoing basis.

Sustained Model

Accuracy

CME


50

Integrated Assay Management tool with PIMS

PIMS Assay Management has unique capabilities that set it apart from the competition

Tight integration with PIMS

– Read, Characterize, and Re-Cut data from PIMS Assay tables

– All results are written directly to PIMS Assay tables

Formulas and references are preserved and mapped to new crudes

Standard and Deferred cuts are supported

CM

Calcs

Output

Copy Paste

PIMS

Assay Management

PIMS

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51

Molecular characterization by PIMS Assay Manager

Available systems perform characterization calculations using statistical and/or engineering equations

Only PIMS employs a new, patented molecular characterization process that provides superior property calculations and extrapolations into all crude regions


52

52

Workflow for improving accuracy of PIMS model

Data from Data Historian,

Laboratory, etc

RefSYS Reactor

Calibration Mode

(one or more base cases)

RefSYS Reactor

Simulation Mode

Generate Case Studies

using Aspen Simulation Workbook

or Delta base Utility of RefSYS

What-if

Analysis

Aspen

PIMS

Update LP vectors or

sub-model calculator

27


53

Challenge Challenge Challenge Impact

Maintain On-going Models

Process unit performance changes with time

Hard to keep planning & scheduling models accurate

Schedulers don’t trust the plan

Large gap between plan and actual operation

Major economic decisions based on inaccurate model

Solution

Planning models are maintained regularly to reflect accurate process

performance

More accurate plans – better economic decisions Adherence to the plan–reduced Planning vs. Actual gap

Lost Margin


54

Integration Planning and Scheduling Data

Use real tower crude assay data

– Integration with crude assay management tools

– Rigorous process simulation technology of Aspen HYSYS Petroleum Refining (REFSYS)

Support various modeling techniques for process submodels

– Vector or Delta base model

– Non-linear modeling

– External model by process engineering technology

Standard Blending Correlations (ABML)

Share process submodel with Scheduling

Planning & Scheduling Model Accuracy (Model Accuracy capabilities in Petroleum Scheduler can indicate need to update models)

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55

Aspen Reporting Framework enables effective Performance Management

Automatically combine information from different applications for plan vs.

schedule vs. actual analysis. 777


56

Today: Plan vs. Schedule vs. Actual

Separate spreadsheets from disparate sources

Variations from plan, scheduled and actual often not

caught during real time leading to monetary losses

Lack of real-time feedback and audit of changes

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57

Now: P&S Synergies

PIMS user sends targets to APS

Scheduler can plot planned, scheduled and actual

Scheduler can now see variances as they are occurring

and can correct as necessary

Real-Time Feedback between PIMS and APS


58

CEPSA Evaluation and planning for increased margins

Challenge Solution Result Challenge

Analyze multiple crudes for multiple modes of operation

Increase frequency of assessing crudes and refinery performance

Ref: Angel Morales Morales, CEPSA, and Maria Jesus Guerra, AspenTech, “Process Simulation for Planning”, Hydrocarbon Engineering, Nov. 2006

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59


aspenONE Process Engineering for Refining and Marketing with Aspen RefSYS

Improved workflow

− Generate yield and properties for all crudes and modes for LP

− Required crude blends

RefSYS model with Excel interface for planners and schedulers

− Predict yields and properties to help operators

− Assist schedulers and planners to improve model accuracy

Challenge Result Solution



60


Better planning with higher confidence

Reduced gap in plan vs. actual performance

− Products available on spec and on time

− Less reprocessing off-spec products

Challenge Solution Result



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61

Technology Services

Global Professional Services Manufacturing and Supply Chain

aspenONE Solutions

Supply Chain

APC

MES

Modeling

Enterprise

Solution/Architectural Design

Process optimization

Decision support

Workflow automation

Data visualization

Database

Installation, Configuration & Commissioning

Post “Go Live” support

Supply Chain

Forecasting

Planning and Scheduling

Distribution

Advanced Process Control

Control strategy

Performance Monitoring

Sustainability

Production Management & Execution

Performance Management

KPIs

Batch & genealogy

Mass balance

Unlocking greater business value


62

AspenTech’s Expertise in Process Industry Consulting & Project Delivery

Breadth of experience Business Process Analysis, Design and Modeling Implementation and Deployment Support and Enhancement Program Evaluation and Audit

Depth of experience 70% of AT consultants have more than 10 yrs industry

experience and a third have more than 20 years A third have been at AspenTech at least 10 years 60% have post-baccalaureate degrees in relevant fields

(chemical engineering, operations research, industrial engineering, etc.)

Team has almost 400 professional publications/ patents

Global delivery About 250 consultants worldwide APAC team around 55 and in rapid growth mode. Large teams

in Singapore, India and China. Strong emphasis on Project Management (Nearly all Project

Managers are PMP Certified) and Local delivery.

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Aspen PIMS™ Support

Software Maintenance and Support (SMS) Services - defined by the “Aspen Premier Support” package and covered by SMS contracts:

– Maintenance Services (Bug Fixes and Upgrades)

– Technical Support

Technical Hotline Support (phone/email/web)

Remote access & diagnostics

Online Support Center (Web Self Service Support)

Technical Knowledgebase

Local support resources with local language

– Chinese, Korean, English, Japanese, Indian, etc

Email Support : [email protected]


64

Profit Improvement Plans

Sr. No.

Description

1 TGO has the highest value to the Hydrocrackers. Consider designing

Hydrocracker for maximum TGO processing.

2 CGO is most valuable as HCR feed stock. Next best routing is to ARDS Unit.

CGO to FCC is the lowest value.

3 Consider routing of CDU Heavy Diesel to Diesel Hydrotreater to the extent it

meets cold flow properties.

4 Heavy diesel should be recovered and routed to the DHTU than dropping it

in the CDU to AR and processing it in the ARDS unit.

5 Consider recovering iC5 from HCR LN & Light St. run Naphtha for MOGAS

blending.

mailto:[email protected]

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65

Analyze Investment Options

Sr. No. Description

1 New Refinery - configuration of Refinery and sizing of new units are

decided, as per results from PIMS.

2

Up gradation study of the existing Refinery for meeting future

specification – flow scheme (configuration) and sizing of new units are

fixed, as per results from PIMS.

3 Gasoline blending study - the selection of components / new units are decided, as per results from PIMS – Add DIP for IC5

4 Diesel blending study - the selection of components / new units are decided, as per results from PIMS - 2 DHT verses 1 DHT

5 Optimized production rate from the above can be utilized in project economics work sheet for calculating IRR & NPV values, which helps management to take decisions on Investment


66

Recap - When to use PIMS ?

Determine constraints in streams disposal (qualities, units' capacities, etc.) and analyze the commercial impact of cost of constraints e.g. RON/MON, RVP, Benzene in Gasoline.

Analyze the cost of Quality Give away.

Analyze the impact of various modes of operation and cut point optimization.

Determine the available blend flexibility and constraints, impact of seasonality etc.

Fine-tune regularly and maintain an updated and accurate LP model for the Refining Complex and work with SCO.

Refining margin analysis - Short-term.

Determine minor hardware modifications for removal of process/ logistical constraints.

Concentrate on "Quick Wins" and push for their implementation.

Monitor the Market and cash in on possible short-term opportunities.

Use real time prices for accurate economics and analyze quick-wins.

Absolute results are less significant than deltas

34


67

PIMS

SAYS

PIMS

Optimizes

&

You Say


68

Planning and Scheduling Best Practices

Improve supply chain

visibility

Improve operational efficiency

35


69

Refinery Scheduling Best Practices

Integrate planning & scheduling

Collaborative scheduling

Align refining & logistics

Monitor & maintain

model accuracy

Optimize product blending


70

Why Refinery Scheduling

Gap between monthly plan and operations is narrowed

Scheduling determines ‘how and when’

Coordination among groups increases operating margins

Improved Refinery Margins


Distributed Control System & Plant

Scheduling

Planning

Scheduling


Distributed Control System & Plant

Scheduling bridges the gap between the monthly plan and daily operations.

– Planning determines ‘what’ to do (what crude to buy, what products to make)

– Scheduling determines ‘how and when’

Managing the daily operation of a refinery using spreadsheets is now widey recognised as inadequate.

Implementing a scheduling solution improves coordination, resulting in increased margins.

36


71

Refinery Scheduling Key Activities

Synchronize Refinery & Logistics Schedules

Manage Refinery-Wide Schedule

Optimize Product Blending

Evaluate ‘What-If’ Scenarios

Monitor & Maintain Model Accuracy


72


Manage Refinery-wide Schedule

Multiple schedulers using disconnected spreadsheets

No ‘models’ of process units

Unable to properly understand impact of changes

Many data inputs

Lost Margin

Solution

Multi-user scheduling system having refinery-

wide visibility

Improved collaboration and visibility

Lower Production costs, Higher Margin

Lack of coordination and visibility

Continuous ‘fire-fighting’

Instability in refinery operations

Excess safety stock

37


73

Visibility into Refinery-wide Schedules

Single system for crude, process unit and product scheduling

All data stored in shared database

Icon that alerts Schedulers to changes made by others

Direct updates to share crude assays, process unit submodels, and blending correlations with planning model

Visibility into receipts, shipments, quality and inventories

Import of Planning targets to assist with schedule creation


74

Multi-User Environment

•Multiple simultaneous users

•Access controlled by role-based security

Teamwork

•All users share the same common data

•Coordination between schedulers is improved

•Coordination between departments is improved

Coordination

•Automatically notifies all users of updates to schedule

•Users leave messages informing others of what’s changed

Communication

38


75

Data Import and Audit

Automatically import inventory data and compare Actual vs. Scheduled highlighting potential problems.

Automatically import logistic events (receipts, shipments) and automatically see changes to the schedule.


76


Synchronize Refinery & Logistics Schedules

Logistics schedule constantly changing

Unplanned outages and shutdowns

Difficult to coordinate refinery & logistics activities

High demurrage costs

Instability/slowdown of refinery operation

Friction between refinery & logistics

Lost Margin

Solution

Refinery scheduling system integrated with logistics information

Improved refinery & logistics coordination

Reduced demurrage & more stable refinery operation

39


77

Synchronization of Shipment Data for Scheduling

Built-in interface for shipment events (crude & product)

Shares crude assays, process unit submodels, and blending correlations with planning model

Productized integration with IMOS

Visibility of schedule to logistics and other HQ groups

Scheduling

DB

Feedstock Scheduling Process Unit Scheduling Product Scheduling Feedstock Receipts

Product Shipments

Refinery


79


Optimize Product Blending

Tighter and more complex specs

Difficult to determine most profitable recipes using spreadsheets

Sub-optimal blending (quality/recipe giveaway)

Frequent reblending

Shipments delayed

Lost Margin

Solution

Blending solution to meet product specs and maximize margins

Higher blending margins

Shipments made on-time

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80

Blend Visualization over time

Aspen Petroleum Scheduler is fully integrated with MBO sharing a common database and GUI

Sophisticated, non-linear optimizer for all blends across the scheduling horizon

Uses event based time, not fixed time

Easy to use interface for optimizing blends

Applicable to gasoline, diesel & fuel oil

Built-in interface for on-line blend controllers

Tank heels and re-blending capability

Batch and in-line blending capability


81

Solves Tighter and Complex Specifications

Aspen Blend Model Library (ABML) can handle a variety of property calculations

• Index Blending (Component Volume)

•RVP, Viscosity, Flash, Pour, Cloud Index Calculations

•Calculated from other Properties

•Road Octane, Cetane Index Derived

Calculations

•Calculated from multiple properties

•Distillation, VOC, RBOB, CARBOB Complex

Calculations

Users can also defined their own blending correlations in the User Blend Model Library (UBML)

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82

Planning, Scheduling & Blending

Aspen PIMS

Refinery Planning


Refinery Scheduling

Aspen MBO

Blending and Scheduling

Unit Activities and Planned Recipes

Rundowns, Qualities, and Shipments

Optimized Blend Recipes

Integrated with Petroleum Scheduler and provides event based multi-blend optimization for blending

of products.

Can be used for gasoline, diesel and fuel oil blending


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Challenge Solution Results

ExxonMobil Optimize Gasoline Blending

Challenge

For three refineries, determine which refinery should supply which demand center(s) and the amount of that demand.

Some demand centers can be supplied by more than one refinery. Others supplied by a single refinery.

Gasoline components can be potentially be bought, sold, or transferred between refineries.

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Challenge

Use M-PIMS for gasoline circuit blend planning for time period “M+1”.

Use MBO Site Blend Planning for “M” time horizon.

Use MBO Blend Scheduling for week time horizon.

Perform validations between what PIMS and MBO models “predicted” versus “actuals” so future model predictions will be more accurate.


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Challenge

Consistency checks between the refinery planning (PIMS) and scheduling (MBO) models narrow the gap between plan vs. Actual, improving planning accuracy.

This allows better crude purchase decisions and determination of what gasoline grades should be made at which refinery to supply given demand centers.

Ref: “Gasoline Blending and Validation”, Frank Kelly, ExxonMobil ; AspenTech Global

Conference Washington, DC, May 2011

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Refinery Scheduling Best Practices

Integration between

Planning & Scheduling

Collaborative scheduling

Align refining & logistics

Monitor & maintain

Model Accuracy

Optimize product blending


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Why Aspen Petroleum Scheduler

Advanced scheduling to meet demands

with higher margins

Improved coordination among schedules

Proactive decision making rather than constant ‘fire-fighting’

Reduced gap between plan & actual operation

Benefits typically ~$0.19 per barrel of crude throughput

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Business Case studies

Case studies for improved scheduling and blending

across 12 refineries


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Aspen Petroleum Scheduler Benefits

Fewer production disruptions and extended production runs

Integrated planning and scheduling for increased accuracy and better decisions

Reduction of working capital requirements due to inventory reductions

Increased yields through better unit scheduling

Reduced stock-outs and distressed purchases through improved visibility

Improved Refinery

Efficiency

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Key Product Features


Schedules that balance equipment constraints, feedstock availability and product lifting requirements for greater accuracy

Integration for better synchronization between refinery and distribution

A 5% reduction in inventory results in a one time savings of

$8M of working capital for a 200,000 BPD refinery


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Integration of Planning and Scheduling Data

Use real tower crude assay data

– Rigorous process simulation technology of Aspen HYSYS Petroleum Refining (REFSYS)

Support various modeling techniques for process submodels

– Vector or Delta base model

– Non-linear modeling

– External model by process engineering technology

Standard Blending Correlations (ABML)

Share process submodel with Scheduling

Planning & Scheduling Model Accuracy (Model Accuracy capabilities in Petroleum Scheduler can indicate need to update models)

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Improve Supply Chain Visibility


Performed in silos

Spreadsheets can’t handle complexity and business constraints

Difficult to align supply and demand profitably

Procure less optimal crudes

Produce less profitable products

Solution

Buy the right crude and sell product more profitably

Greater visibility and agility

yield higher margin

Lost Margin


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Shell Improve Integrated Petroleum Supply Chain

Challenge

Creation and standardization of demand forecast business process integrated with Collaborative Demand Management tool.

Forecasting tool with:

State of the art statistical forecasting algorithms.

Flexible hierarchy with fast aggregation and disaggregation

EO

Demand

Mgmt

(DM)

Sales to

Customer

(ERP)

EO

Primary

Distribution

Planning

(DPO)

Optimised

Plan

RPS

Refinery

Planning

(PIMS)

Pricing

engine

Product

Prices

EO

Primary

Distribution

Scheduling

RPS

Refinery

Scheduling

(Orion)

Latest

Estimate

Constraints

&

Contracts

Actual

Sales

(Demand)

Crude

Prices

Transport

Plan

Demand

Scheduled

Liftings

Refinery

Production

Scheduled

Stocks

Integration is

KEY

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Challenge

Different demand forecasts across different departments (marketing, finance, supply, distribution).

Many local forecasting processes or no process at all.

Different forecasting tools used in different countries.

Desire to have one global process using one standard global tool with one volume forecast across the supply chain.

Demand Focal Point

Pricing Engine

Regional Price

Strategists

Collaborative

Forecasting

Demand Cell

Owners

Handshake PIMS

Refinery

Planners

Consolidated Demand

Forward

Prices

Call on

Refinery

Envelope

Plan

DPO

Envelope

Planner

Production

Scheduling

Tool

Schedulers Latest Estimate


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Challenge

Demand planners liked the changes:

More accurate visibility of months 2/3 in future to aid refinery PIMS planning decisions. Couldn’t see beyond first month previously.

Can visualize where sales are deviating from forecast.

More timely and accurate lifting plans from refinery Supply schedulers.

Ref: “Demand Forecasting & Management - Collaborative Demand Management Improves

Shell’s Integrated Supply Chain”, Jeannie Gardner, Shell: AspenTech Global Conference

Washington, DC, May 2011

“The commissioning of the EO Demand

Forecasting Tool was used as a

springboard to strongly drive methods to

sustainably improve the overall demand

forecasting result. The outcome has

exceeded expectations in the timeframe

with an absolute demand forecasting

result now consistently exceeds previous

limits”

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Total Petroleum New scheduling system yields higher margins

Each refinery had their own scheduling model and database

Need to integrate 12 separate models into one standard model

Convert older version of scheduling software to reduce IT costs

Challenge Solution Result Challenge


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Upgrade to Aspen Petroleum Scheduler

Standardize on one extensive Aspen Petroleum Scheduler refinery model

Standardize interfaces, databases and plug-ins

Create a data warehouse


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Reduce IT costs significantly with one model versus twelve

Reduce training costs and time with common model and user interface

Expect additional benefits as users learn the new system

“The project is expected to significantly reduce our IT support and user training costs. Additionally, the schedulers will be using one standard model utilizing the latest Orion version.”

Magali Peysson Total Petroleum

Ref: “Management of the Migration to a New Orion”, Magali Peysson, Total; PIMS User Conference, Seattle, WA, November 6, 2008



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Thank You for your attention

aspen planning and scheduling seminar

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