OIL PIPELINE LOGISTICS Jaime Cerd Instituto de Desarrollo - - PowerPoint PPT Presentation

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OIL PIPELINE LOGISTICS

Jaime Cerdá

Instituto de Desarrollo Tecnológico para la Industria Química Universidad Nacional de Litoral - CONICET Güemes 3450 - 3000 Santa Fe - Argentina

Pan American Study Institute on Emerging Trends in Process Systems Engineering August 11-21 , Mar del Plata, Argentina

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• Motivation
• The multiproduct pipeline planning problem
• Available pipeline planning approaches
• Presentation of a continuous planning approach
• Critical operational decisions & major problem constraints
• An illustrative example
• Static vs dynamic planning problem
• The detailed weekly pipeline schedule
• Conclusions

OUTLINE

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ACKNOWLEGMENT

The material included in this presentation have been extracted from DIEGO C. CAFARO’s Doctoral Thesis currently in preparation

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Most reliable, safest and cheapest way of delivering large volumes of a wide range of refined products from refineries to distant depots. Batches of different grades and products are pumped back-to-back in the line without any separating device. Batches move forward in the line and products are transferred to terminals whenever a new batch is injected at the head terminal.

LIQUID PIPELINE OVERVIEW

Segment Segment Distribution Terminals D2 D1 D4 D3 D5 Interfaces Head Terminal Refinery

P4 P3 P1 P2

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PIPELINE MAJOR FEATURES

Usually buried and invisible to the public

• With several intermediate entry and exit points

With segments of varying diameter Large diameter pipelines due to high construction costs With crude oil and refined products moving in separate lines Always remaining full of liquid and pumping in only one direction.

Trans Alaska Pipeline System Colonial Pipeline

REFINERIES COLONIAL

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PIPELINE OWNERSHIP – REMOTE OPERATION

Owned by a large number of companies, almost all are common carriers An increasing number are owned by non-oil companies Operations are fully automated and remotely performed From centrally located control rooms, operators direct the product flow

• From there, they start & stop pumps, open & close valves, fill & empty tanks

Supervisory control & data acquisition systems, known as SCADA, are used SCADA continuously monitors: pump pressures flow rates batch locations tank levels

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PIPELINE ADVANTAGES

Operate around the clock all seasons and under all weather conditions No container moves with the cargo. Products only move. No backhauls Employment is only 1% of that of the trucking industry Very low transport damage to products and especially to the environment. THE CHEAPEST MODE OF TRANSPORTATION Lines coated with corrosion-resistant chemicals to prevent corrosion Chance of leaks reduced by an extensive maintenance program “Smart pigs” sent through the line

• detect dents and imperfections
• measure wall thickness

Scraper PIGS

THE SAFEST MODE “Scraper pigs” clean the inside of a line by removing residual material clinging to the walls

BUT THE SLOWEST MODE (3 TO 8 MPH)

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INTERMODAL PRODUCT MOVEMENTS

Pipelines dominate the oil industry transportation Participate in intermodal product movements with other modes of transportation

• tankers & pipeline combination for crude oil
• pipeline/truck combination for refined products
• A batch in the line arriving at a terminal:
• can be placed in a tank
• can be rerouted into another pipeline
• Lines provide tanks to buffer the

flow rates between two connecting pipelines or line segments of different diameters

REFINERIES DISTRIBUTION TERMINALS OIL FIELDS CLIENTS CRUDE OIL IMPORTS PIPELINES

10 20 30 40 50 60 70 80 1980 1985 1990 1995 2000 2005 Pipelines (%) Vessels (%) Trucks (%) Trains (%)

CRUDE OIL DOMESTIC TRANSPORT MARKET IN USA PIPELINES VESSELS

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MONITORING BATCH STATUS

The specific gravity of the flow is continuously monitored at every terminal When it changes, the operator knows that:

• one product batch is ending
• another product batch is beginning to arrive

Refined products are often “color-coded” with dye The operator can visually

• bserve the transition

Distribution Centers D2 D1 D4 D3 D5 Interfaces Head Terminal Refinery

P4 P3 P1 P2

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POWER CONSUMPTION

• The power consumption is the largest pipeline operating cost.
• Liquid products are propelled by centrifugal pumps sited at the pumping

stations one at the origin and the others distributed along the line.

• The capacity of a pipeline can be increased by installing additional pumping

stations along the line to rise pressure.

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INTERFACE MATERIAL

Pipelines move different grades of a product or distinct products sequentially through the same line in “batches”. At the boundary of two consecutive batches some mixing occurs. Between batches of different grades Interface Mixed with the lower grade product

PRODUCT DEGRADATION

Between batches of different products Transmix Separated and sent back to the refinery

TRANSMIX REPROCESSING

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INTERFACE COSTS

Product degradation and transmix reprocessing costs both significantly contribute to the pipeline operating cost. Amount of Interface Number of batches Arrangement of batches in the line CRITICAL DECISIONS Batching Operations

• Keep similar products from

different refiners together

• Inject the lowest possible

number of product batches Sequence batches by specific gravities Batching Sequencing Some products are prohibited to be consecutively injected to avoid a serious product degradation.

• Batch sequencing is also important to meet product delivery due dates at terminals

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PIPELINE OPERATING MODES

• More stringent environmental regulations on car fuels have resulted in a

proliferation of refined products.

• Major refined product pipelines currently move 100-120 distinct products

compared with 10-20 in the ‘60s. OPERATING MODES BATCH MODE FUNGIBLE MODE

the same volume accepted for shipment to a particular depot is the

• ne delivered to that destination

standard refined products from different refiners are consolidated into a single batch LARGER NUMBER OF BATCHES HIGHER INTERFACE COSTS SMALLER NUMBER OF BATCHES LOWER INTERFACE COSTS

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Tiem po [sem anas] 1 2 3 4 P1 P1 P2 P3 P1 P1 P2 P3 P1 P1 P2 P3 P1 P1 P2 P3 Tiem po de C iclo (TC ) [días] N o. de Batches 7 16 P1 P1 P2 P3 P1 P1 P2 P3 14 8 P1 P1 P2 P3 28 4 TC = 28 TC = 14 TC = 7 N ivel de Inventario de Producto P2 en el D estino, según el Tiem po de C iclo (TC )

Tiem po Tiem po de Transporte

PIPELINE BATCHING OPERATIONS

Number

• f batches

16 8 4

THREE PRODUCTS : P1, P2 , P3 SELECTED BATCH SEQUENCE: P1 – P3 – P1 – P2 THE SAME AMOUNT OF PRODUCTS SHIPPED TO TERMINALS TIME HORIZON: 4 WEEKS

Period Length 7 14 28

weeks

time days

SHORTER PERIOD LENGTH – SAME BATCH SEQUENCE IN EACH PERIOD LARGER NUMBER OF BATCHES AND INTERFACE COSTS SMALLER BATCHES AND LOWER TERMINAL TANK CAPACITIES

4-PERIOD HORIZON 2-PERIOD HORIZON ONE-PERIOD HORIZON Inventory Level of P2 at the Depot

Transportation Time

time

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B1 B2 B3 D1 D2 REF B4 D1 REF D2 B4 D1 D2 REF B4 D1 D2 REF B4 D1 D2 REF B4 D1 D2 REF D1 D2 REF B1 B2 B3 B4 B5 D1 D2 REF B5 D1 D2 REF B5 D1 D2 REF

STRIPPING OPERATIONS (“CUTS”)

Every new batch injection pushes some batches forward while others that arrive at their destinations are partially or completely sent out of the line (“stripping

• perations”) and loaded in the terminal tank.

Therefore, both the size and the location of every batch in the line can change during the pumping of a new batch. Batch stripping takes place if the batch has arrived at the terminal and enough storage capacity to receive the material is available. Otherwise, the line should be temporarily stopped and deliveries are interrupted.

D1 D2 REF B5 B1 B2 B3 B4

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• A fungible batch with multiple destinations will undergo several stripping operations

(“cuts”) along the journey.

• A batch can travel to the farthest destination for 7-14 days (“delivery lead-time”).
• A fungible batch may satisfy several product requirements at different terminals,

i.e. multiple destinations.

Every product delivery has its own due date.

BATCH DUE DATES & DELIVERY LEAD-TIME

Fungible batch Multiple destinations Multiple due dates Delivery lead-time Is a function of Depot location Pumping rate Pipeline idle time

• Most short-term product requirements are satisfied by batches currently in transit.

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• A common carrier pipeline terminal typically connects to the marketing terminals of

its main shippers or to public storage terminals.

• Gasoline tank trucks are loaded from storage tanks at marketing terminals
• Terminals have few tanks just to facilitate stripping operations and quality control tasks.
• In fungible mode, a fewer number of larger storage tanks is usually needed.
• Tanks for long-term storage must be provided by the customer at entry & exit points.

LOADING & UNLOADING OPERATIONS

Trunk Line Marketing Terminal Pipeline Terminal

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• A cyclic schedule is usually performed.
• Customers should make the product timely available at the input terminal and

provide enough storage capacity at its destinations.

• US pipelines are mostly COMMON CARRIERS, i.e. services are provided to multiple
• il refiners.
• Customers contact the pipeline operator to place their shipment orders for the next

month, called NOMINATIONS.

The monthly planning horizon is composed by a number of periods, called CYCLES.

• A NOMINATION specifies the product and the quantity to be shipped.

SHIPPER NOMINATIONS

• Every nomination is divided into a number of equal-size batches, one for each cycle.

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• Operational decisions concerning to every batch to be injected include:
• the assigned destinations (terminals)
• the amount allocated to each destination (the cut sizing)

THE PIPELINE SCHEDULING TASK

• Planning pipeline operation in fungible mode implies to choose:
• the set of batches of each product to be injected, and the batch sizing
• the sequence of batch injections
• batch injection rates and starting times
• Operational decisions related to each batch pumping run include:
• the set of “stripping operations” to be carried out

in-transit batches to be stripped out - receiving depots - cut sizes

• the location & size of every in-transit batch at the end of a batch injection

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BATCH INJECTION & STRIPPING OPERATIONS

Depot D1 Depot D2 Depot D3 C5-L5 _ C5 150 50 30 50 20 At time C4 At time C5 200 190 180 200 150 150 160 130 180 B1 B2 B3 B4 B5 B4 B3 B2 B1 P4 P3 P2 P1

CURRENT PIPELINE STATE NEW BATCH INJECTION NEW BATCH B5 STRIPPING OPERATIONS REFINERY STRIPPED BATCHES B4 – B3 – B2 – B1

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PIPELINE SCHEDULING GOALS

• To minimize operating costs including:
• the transmix reprocessing cost & the product degradation cost
• the pumping cost
• the inventory costs in refinery and depot storage tanks
• To keep the pipeline running at nearly maximum capacity during off- peak hours
• To enhance the information on the current status of batch movements

To meet product delivery requests on time

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The sequence of “old” batches already inside the pipeline.

• The scheduled production runs at the refinery.
• The inventory levels in refinery and terminal tankage at the initial time.
• The set of shipment requests, each one involving a refined product, the assigned

terminals and the delivery due dates.

PROBLEM DATA

• Their locations & volumes at the initial time of the planning horizon.

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• Knowledge-based Search Techniques (Sasikumar et al., 1997)
• Cyclic Scheduling Techniques (Used by pipeline schedulers)
• Mixed-Integer Mathematical Programming Formulations
• Discrete Formulations (Rejowski & Pinto, 2003)
• Continuous Formulations (Cafaro & Cerdá, 2004 & 2008; Relvas et al., 2007)

PIPELINE SCHEDULING APPROACHES

Metaheuristic Search Algorithms

• Greedy algorithms (Hane & Rattliff, 1995)
• Genetic algorithms (Nguyen & Chan, 2006)
• Tabu search (García et al., 2008)
• Discrete Event Simulation (Maruyama Mori et al., 2007)

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• Discrete Formulations (Rejowski & Pinto, 2003)

MIP DISCRETE FORMULATIONS

Pack 1 Pack 2 Pack 3 Pack 4 t = T1 T2 T3 P1 P1 P1 P2 P1 P2 P1 P1 P2 P1 P1 P1 ...

• The pipeline is divided into packs of uniform size at each segment
• Each pack contains exactly one product
• The time scale is divided into slots of fixed length (fixed pumping rate)
• Whenever a pack of product enters a segment, the content of the first

pack in that segment is displaced to the next pack.

Very large MILP formulations for longer planning horizons

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MAJOR FEATURES

MILP CONTINUOUS APPROACH

• A “cheap” generalization to pipelines with several intermediate input and

exit points

• Delivery due dates at the end of every planning period
• Explicit treatment of interface volumes

Multiperiod planning horizon Pre-defined ordered sequence of empty batch slots of variable-size Continuous time & volume representation

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MAJOR DECISION VARIABLES

• Allocation variables assigning products to “empty” batch slots

MILP CONTINUOUS APPROACH

• Stripping operations to take place during a batch injection (batch to be stripped,

cut size, receiving terminal)

• Location and size of in-transit batches at the end of a new batch injection
• Starting and completion times of new batch injections (the time events)
• Assignment variables denoting the planning period at which a batch injection ends
• Control variables indicating the arrival of a batch at the assigned terminal to start

the stripping operation MAJOR CONTINUOUS VARIABLES

• Initial sizes of batches to inject in the pipeline
• Inventory levels at refineries and pipeline terminal tanks at every time event

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• The size of the interface between consecutive batches depends on the

assigned products

B1 B2 P3 P1 IFP1,P3 flow WIFB2,P1,P3 =

new P p p i

I i y ∈ ∀ ≤

∑

∈

1

,

• A single product can at most be assigned to a batch slot

P p p i I i y y IF WIF

p i p i p p p p i

∈ > ∈ ∀ − + ≥

−

´ , 1 , ) 1 ( *

, ' , 1 ' , ' , ,

MAJOR MODEL CONSTRAINTS

• A new batch injection can be started after completing the previous one

P p p I i y y C L C

new p i p i p p i i i

∈ ∈ ∀ − + + ≥ −

− −

´ , ; ) 1 ( *

, ' , 1 ´ , 1

τ

new max i i

I i h C L ∈ ∀ ≤ ≤

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• The length of a pumping run depends on the batch size & the pumping rate

MAJOR MODEL CONSTRAINTS

• The size of a flowing batch changes during a batch injection due to the

execution of stripping operations

new i i i

I i L vb Q L vb ∈ ∀ ≤ ≤ * *

max min

At time C4 200 Depot D1 C5-L5 _ C5 100 At time C5 260 100 (B5) 100 160 (B4) DB4,D1

(B5) = 40

200

i ' i , I ' i , I i D W W

new J j ) ' i ( j , i ) 1 ' i ( i ) ' i ( i

> ∈ ∀ ∈ ∀ − =

∑

∈ −

200 – 40 = 160

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• The overall amount of products delivered to terminals through stripping
• perations is equal to the size of the new batch injected in the line

MAJOR MODEL CONSTRAINTS

Depot D1 Depot D2 Depot D3 C5-L5 _ C5 150 50 30 50 20 At time C4 At time C5 200 190 180 200 150 150 160 130 180 B1 B2 B3 B4 B5 B4 B3 B2 B1

150 (in) = 50 + 30 + 50 + 20 (out)

• A single time period will contain the completion time of a pumping run

0 h

wB1,T1 = 1 35 h 65 h 0 h T1 T2 T3 T4 48 h 72 h 96 h 144 h wB2,T2 = 1 wB3,T3 = 1 wB4,T4 = 1 23 h B1 B2 B3 B4 70 h 93 h 102 h 125 h

TIME PERIODS BATCH INJECTIONS

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• Feasibility conditions for stripping operations
• An upper bound on the cut size
• The flowing batch has reached or will reach the depot during the pumping run

MAJOR MODEL CONSTRAINTS

At time C5 300 100 Depot D1 160 50 reserved for D1 Depot D2 350 100 50 already gone 200 available for D2 B3 B4 B5 290 100 100 10 10 10 240 100 100 50 60 50 50 100 100 190 250 190 At time C6 B3 B4 B5 B6 B3 B4 B5 B6 B5 B6 B4 B3

CONSECUTIVE STRIPPING OPERATIONS DURING INJECTION OF B6

CUT 1 CUT 2 CUT 3 CURRENT PIPELINE STATE

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Delivery time constraints

THE OBJECTIVE FUNCTION

∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑ ∑

∈ ∈ ∈ ∈ ∈ ∈ ∈ ∈ > ∈ ≠ ∈ ∈ ∈ ∈ ∈

⎥ ⎦ ⎤ ⎢ ⎣ ⎡ ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ + ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ + ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ − − + + + + ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ =

P p Inew i i p p Jp j Inew i i j p j p new Inew i i P p J j T t t j p t j p i I i p p i p p p p P p P p J j I i Inew i i j i p j p

IRS cir ID cid I card L PH h cu B cb WIF cf H DP cp z Min

' ) ' ( ' ) ' ( , , max max , , ) ( , 1 ' , , ' , ' ' ' ) ' ( , , ,

* * ) ( 1 * * ρ

• Minimize pumping cost, interface reprocessing cost, pipeline idle time

and inventory carrying cost OBJECTIVE FUNCTION Batch injections completed up to period t are available to meet product requirements to be delivered to terminals before the end of period t

new p t j p t j p t i t i t k k j p i I j p

I i T t J j P p B B w w dem DM

new

∈ ∈ ∈ ∈ ∀ + − ⎟ ⎠ ⎞ ⎜ ⎝ ⎛ − ≥

− + = ∈ =

∑ ∑

, , , ) ( *

) 1 ( , , , , , 1 , 1 , , 1 ) ( , l l l

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• A pipeline system with a single entry point and multiple exit points (5 terminals)

A REAL-WORLD PIPELINE PLANNING EXAMPLE

PROBLEM DATA

• Unidirectional flow

Four different products (gasoline, diesel, LPG, jet fuel) are sent to terminals

• Time horizon length: 4 weekly periods (672 h)
• Pipeline Length: 955 km

Variable Segment Diameter: 12 – 20 in Pump rate range: 800 – 1200 m3 per hour

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OPTIMAL STATIC PLANNING

R

Run Time Interval [h] Volume [10

2

m3]

P4 P3 P1 P2 D2 D1 D4 D3 D5 120 70 1180 400.37 320.37 962.5 679.63 134.63 1220 672.5 555 425 415 400 400 700 550 200 190 200 70 135 200 400 600 800 1000 1200 1400 1600 5.00_52.00 55.00_198.33 202.33_309.21 358.28_412.07 524.50_672.00 425 1720 90 60 80 10 135 50 310 190 410 140 247.5 70 152.5 10 INITIAL STATE INJECTING P4 INJECTING P2 INJECTING P1 INJECTING P3 INJECTING P1 A VERY LARGE BATCH STRIPPING OPERATIONS

• ASSUMING A FIXED PLANNING HORIZON

THE HORIZON-TIME EFFECT FIVE BATCH INJECTIONS

IDLE TIME

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• As time goes on, new transport requests are received and others are cancelled
• Periodical planning update permits to eliminate the horizon-end time effect and,

more important, the pipeline idle time

DYNAMIC PIPELINE PLANNING TASK

• The current pipeline schedule should be periodically updated at the start of a

new period

• A sufficiently long rolling time horizon should be considered

The horizon-time effect arises because later batch injections have the only purpose of pushing batches to their destinations

• As the planning horizon rolls, such later batches will be injected because of new

real shipment requests

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DYNAMIC PIPE PLANNING ALGORITHM

y n

Refinery Production Schedule Planned Pipe Schedule for periods

k+hf to k+N-1

Definite Pipe Sequence for periods k+hf to k+hf+sf-1 Initialization Stage Data Updating Stage Trigger Stage Rescheduling Stage Dispatching Stage Definite Pipe Schedule for periods

k to k+hf-1 OUTPUTS INPUTS

SCADA Remote Pipeline Controlling System clock = ddk-1 ?

• Capture pipeline batch scenario (products, volumes

and locations) (Ioldp, Woi, Foi)

• Capture product inventories at refinery and depot

tank farms (IRop, IDop,j)

Updating the Pipeline Schedule Run the Multiproduct Pipeline Scheduling Optimization System (MPSOS) for the planning horizon including periods k to k+N-1

• Execute the Pipeline Schedule for the time horizon

going from ddk -1to dd(k+hf-1) (periods k to k+hf-1)

• Set k = k+tRS

Demand Updating Process Update Product Demand Data for periods k to k+N-1

• Import updated refinery production schedule and

product output rates for periods k to k+N-1 (time horizon [ddk-1 ; dd(k+N-1)])

• Set h (time period length) [hours]
• Set N (number of time periods to be considered)
• Set sf = ⎜TSF ⎜ (soft-frozen time periods)
• Set hf = ⎜THF ⎜ (hard-frozen time periods)
• Set k = 1. ddk-1 = 0.
• Set clock = 0 [h]. Run clock

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OPTIMAL DYNAMIC PIPELINE PLANNING

INITIAL STATE

• ASSUMING A 4-WEEK ROLLING PLANNING HORIZON

TEN BATCH INJECTIONS

Run Time Interval [h] Volume [10

2

m

3]

P4 P3 P1 P2 D2 D1 D4 D3 D5 R 200 400 600 800 1000 1200 1400 1600 400 700 200 200 135 120 70 1220 425 415 400 550 190 70 5.00_52.00 55.00_168.00 425 1356 90 60 80 10 135 50 136 410 140 247.5 70 152.5 10 120 1220 295 173.00_183.00 120 120 924.63 120 547.5 42.87 184.00_286.89 90 180 100 245 120 160 247.5 92.13 1234.63 659.78 390 647.72 120 477.28 327.5 259.62 507.66 280 280 247.72 247.72 120 220 338.00_384.00 385.50_440.95 441.95_463.58 466.58_504.00 276.91 42.87 70.22 110 5.59 400 149.78 390 665.37 44.41 107.71 259.62 120 107.5 449.04 259.62 90 40 105.38 449.04 402.28 190 247.72 213.66 80 6.34 290.38 1446.34 1155.96 9.62 9.62 49.04 49.04 130 130 504.00_630.25 635.25_659.44 400 3.62 65 120 350 129.62 6.34 80 247.72 70 42.66 1513.96 290.38 36.38 254

SHORT IDLE TIME

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Pipeline Usage Refinery Inventory Profiles

500 1000 1500 2000 2500 168 336 504 672

Time [h] Inventory Level [m

3]

P1 P2 P3 P4 168 336 504 672

P4 P3 P1 P2 Changeover Idle time Time [h]

Qi

[102 m3] 425 1356 120 1235 390 665 260 1963 290

ADDITIONAL RESULTS

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• Multiple-source pipelines include additional input terminals at non-origin points

to collect oil product batches from downstream refineries

• So far, we deal with single-source multiple-destination trunk pipelines

B1 B2 B4 B6 B3 s1 s2 j1 j2 j3 B1 B2 B4 B6 Al final de K1 B3

xsB3,s2

(K1) = 1

xdB2,j2

(K1) = xdB1,j2 (K1) = 1 xdB1,j3 (K1) = 1

B5 B5 P1 P2 P3 P4

MULTIPLE-SOURCE TRUNK PIPELINES

INTERMEDIATE INPUT TERMINAL B3

• Need of choosing the input terminal where the next pumping run will occur
• At intermediate input terminals, a new batch can be injected or the size of a

flowing batch can be increased

INJECTION OF BATCH B3

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• In multiple-source trunk pipelines, batches are not sequenced in the same order

that they were injected in the line

B1 B2 B4 B6 B3 s1 s2 j1 j2 j3 B1 B2 B4 B6 Al final de K1 B3

xsB3,s2

(K1) = 1

xdB2,j2

(K1) = xdB1,j2 (K1) = 1 xdB1,j3 (K1) = 1

B5 B5 P1 P2 P3 P4

MULTIPLE-SOURCE TRUNK PIPELINES

INTERMEDIATE INPUT TERMINAL B3

• A batch is not necessarily preceded by those previously pumped in the line
• Batch B4 is preceded by batch B3 even though B4 was inserted before
• Need of separately handling the pumping run sequence and the batch

sequence

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• At the very operational level, a detailed pipeline schedule for the action period
• f the current horizon must be prepared

The basic information is provided by the monthly pipeline planning

DETAILED PIPELINE SCHEDULE

Just the batch injections and stripping operations planned for the first period of the current time horizon are to be performed

• A more detailed definition of the stripping operations to execute during a batch

injection is required: sequence, timing and extent of stripping operations

• Additional systematic heuristic/algorithmic procedures providing a detailed

description of the required stripping operations are to be applied

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DETAILED PIPELINE SCHEDULE

Nearest Active Depot First (NDF) rule:

Run Time Interval [h]

D2 D1 D4 D3 D5 R 400 700 200 200 135 300 200 5.00_70.00 150

MDS

Q dd[h] N2 100 18 N3 200 72 Nominations Q dd[h] N1 200 48 Nominations Q dd[h] N4 150 12 Nominations

DPS

200 400 200 50 135 650 400 650 900 1500 1635

Volume [10

2

m3]

Mean Flow Rate = 10.00 650 D2 D1 D4 D3 D5

Run Time Interval [h]

R 400 700 200 200 135 200 135 5.00_15.00 150 100 135 100 15.00_30.00 200 135 200 450 200 400 135 150 500 400 250 400 600 450 30.00_50.00 50.00_55.00

Volume [10

2

m3]

Flow Rates = Mean Flow Rate 100 150 200 50 200 400 200 50 135 650 400 650 900 1500 1635 55.00_70.00 150 50 200 200 200 450 200 200 200 200

In which order the “stripping

• perations” should be

executed during a batch injection?

PRIORITIZE DELIVERIES TO THE NEAREST DEPOT

AT THE PLANNING LEVEL AT THE OPERATIONAL LEVEL

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DETAILED PIPELINE SCHEDULE

MILP Formulation:

Run Time Interval [h]

D2 D1 D4 D3 D5 R 400 700 200 200 135 200 50 135 5.00_18.00 150 150 200 50 135 100 18.00_30.50 200 200 50 135 200 450 200 400 200 50 135 200 650 400 700 250 400 600 600 400 650 900 1500 1635 30.50_48.00 48.00_70.00

Volume [10

2

m3]

Flow Rates 11.53 8.00 11.42 9.09 150 100 200 200

Comparative Results: Rule Valve operations Earliness [h] Tardiness [h] NDF 5 39 43 FDF 4 22 4 EDD 4 2 2 MILP 4 2

NEAREST DEPOT FARTHEST DEPOT EARLIEST DUE DATE

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B1 B2 B3 B4 B5 Refinery 1 Refinery 2 Depot 1 Depot 2 Depot 3

Batch B3 will be pumped in Refinery 2

30 70 40 Supply 30 50 30 Demand 30

A MULTIPLE-SOURCE PIPELINE SCHEDULE

Horizon Length: 120 hs.

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Inject Product P1 (Batch B5) in Refinery 1 Deliver Product P1 (Batch B5) to Depot 1

B1 B2 B3 B4 B5

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P1 (Batch B5) to Depot 1 Inject Product P2 (Batch B6) in Refinery 1

B1 B2 B3 B4 B6

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P1 (Batch B2) to Depot 2 Inject Product P2 (Batch B6) in Refinery 1

B1 B2 B3 B4 B6

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P1 (Batch B2) to Depot 2 Inject Product P3 (Batch B3) in Refinery 2 Refinery 2 is ready to inject Product P3 in Batch B3

B1 B3 B4 B6

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P3 (Batch B3) to Depot 2 Inject Product P3 (Batch B3) in Refinery 2

B1 B3 B4 B6

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P3 (Batch B3) to Depot 2 Inject Product P2 (Batch B6) in Refinery 1

B1 B4 B6

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P2 (Batch B1) to Depot 3 Inject Product P1 (Batch B8) in Refinery 1

B4 B6 B8

Note that Batch B7 has been preserved to be injected in Refinery 2

B7

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P2 (Batches B4 & B6) to Depot 3 Inject Product P2 (Batch B9) in Refinery 1

B6 B8 B9 B7

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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Deliver Product P2 (Batch B6) to Depot 3

B6 B8 B9 B7

Inject Product P3 (Batch B7) in Refinery 2 Refinery 2 is ready to inject Product P3 in Batch B7

A MULTIPLE-SOURCE PIPELINE SCHEDULE

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• A continuous pipeline planning approach has been presented
• Multiproduct pipeline planning is a very complex industrial problem
• The approach can even be applied to multi-source multiproduct pipelines

CONCLUSIONS

• Tools for generating a weekly detailed pipeline schedule have also

been briefly described

• Pipeline planning over a multiperiod rolling horizon with delivery due

dates at period ends is performed

• The approach still remains competitive for a monthly time horizon

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OIL PIPELINE LOGISTICS

Jaime Cerdá Instituto de Desarrollo Tecnológico para la Industria Química Universidad Nacional de Litoral - CONICET Güemes 3450 - 3000 Santa Fe - Argentina

Thanks for your attention! Questions?

Contact: jcerda@intec.unl.edu.ar