Operational Intelligence in Pipeline Natural Gas Transmission Wilson Navarrete, [email protected] Luis Yacher, [email protected]

Operational Intelligencein Pipeline Natural Gas Transmission

Wilson Navarrete, [email protected]

www.gasatacama.cl

Luis Yacher, [email protected]

www.contac/scan.cl

Copyright © 2006 OSIsoft, Inc. Company Confidential. All rights reserved. 2

•The operation area is home to the largest copper mines, lithium and nitrates reserves in the world.

•GasAtacama Pipeline owners are Endesa, Chile (50%) and CMS Energy, USA (50%)

•Gas supply comes from Argentina’s Northwest Basin. YPF and Pluspetrol, under long term agreements

OverviewSome characteristics of the pipeline are: •The 800+ miles GasAtacama Pipeline goes from northern Argentina to northern Chile, through the Atacama desert and the Andes mountain range, reaching altitudes over 16,000 feet.

•A Remote control and supervision system based on satellite telemetry is necessary due to :Very difficult access to the pipeline locations, adverse climate conditions and the need for secure and controlled operations.


Arica

Mejillones

Iquique

Antofagasta

Alto NorteSmelter

Cerro Dominador

GasAtacama PowerPlant

BOLIVIA

ARGENTINA

P. Patache

Taltal PowerPlant (Endesa)

Taltal

Main Pipeline• From Cornejo (Argentina) to Mejillones (Chile)• Length: 951 km 20“ pipe• 2 compressor stations• Current Capacity 5.4 million scm /day• Maximum Capacity 8.5 million scm /day

Taltal pipeline• From Mejillones to Taltal power plant• Length: 223 km, 16“ and 12“ pipe• Maximum Capacity 2.2 million scm /day

Pipeline system

Atacama GasPipeline

Cuenca GasPipeline

Taltal GasPipeline

Cornejo

PERU

CHILE


Overview - Transmission Gas Pipeline SCADA System

3 Gas Control RoomsSantiago ChileAntofagasta ChileJujuy Argentina


The RtPM Infrastructure ( Chile & Argentina Gas Control Room)MS Excel Add-in

Data Link

PI-TGNET

PI Server

Simulationpipelinestudio®

TGNET

Trend Client

PI-NotifyEmail

Back-endOperational Systems

MiddleTier

RtWebParts Web Browser / Enterprise PortalClients

RelationalDatabaseMS-SQL

MRO MAXIMO

TimeSeries Data

GAS Flow Computer

DANIEL

Real TimePoint DataTime

Series Data

OPC RS Linx Server

PI InterfaceData abstraction layer

OA Framework

OA PDA via WiFi

PI-ACE( *)Calculation

EngineReal-time

Data Cache

SCADAObject

AutomationServer

Microsoft W2K3

PI Notify( *) Engine

Process Book

GIS Interface (*)ESRI

OAView

pipelinestudio®


Operational Intelligence RtPM application review

• Pipeline status and online reporting examples• Online calculations for efficiency, quality and

operational indicators• Provides a common view of critical business and

operational data from different sources throughout the company.

• Enabling plant floor and operations personnel, as well as operation management to monitor real-time performance against business goals.


Trend Graphics manager

Operation and supervision tool that allows a direct an easy access to pipeline variables using role specific MDB

structures as well as “personal views”


Report AGA 3:2000 , AGA8 GAS Supercompressibility (Gas Custody Transfer, Metering Station )

Integrates disparate data into an organizing data model.

The data model brings a broader business context to the data delivering comprehensive views of a situation in real-time”


Gas Compressor Station Supervision


Reciprocating Compressor Power, Efficiency &. Flow Calculation


Gas Quality Control


Perfomance management of the pipeline


System architecture

PI

PI ACE

pipelinestudio®

Valve Modeling

Compressor Modeling

Multivariate Analysis

•External Models

•ACE (Native) Models

Control System pipelinestudio®


•GasAtacama has developed an application, customized to facilitate the operation and to complement the pipeline simulation and tracking performed with the pipelinestudio® Gas (TGNET) software package form Energy Solutions International. www.energy-solutions.com

•The application uses a reference model calculated from TGNET to evaluate the real operation of the pipeline.

•The main purpose is to determine the future behavior of the pipeline system under certain forecasted operation conditions.

GasAtacama PI-TGNET (pipelinestudio®)


•GasAtacama PI-TGNET application allows for the complete automation of the simulation of future forecasting of the pipeline, based on historic information as a baseline for dynamic simulations.

GasAtacama PI-TGNET interface is a powerful tool that enables a quick and accurate prediction of the pipeline operation since it loads historic information (real data) from PI directly into TGNET for a more reliable dynamic analysis. •Steady State Generation: It establishes the initial condition for pipeline simulation. It considers about 72 hours of historical data in order to create the initial conditions for transient (dynamic) simulation. •Transient Simulation: for every variable a complete transient analysis is performed.

GasAtacama PI-TGNET


Simulate the “past” 96 hours of the transient history of the pipeline, in order to accurately reproduce the “present” state and predict the “future” transient states of the operation.

Model Operation base concept


Input Data - Simulate the “Past” 96 hours

• Client Flows• Gas Compressor(GC) Stations Discharge• Cornejo GC Suction Pressure• Flow at Cornejo GC.

Operation


Operation

Input Data: Simulation of the Future

• Client Flows (Nominations)• Volcan GC Pressure Discharge• Cornejo GC Suction Pressure• Flow at Cornejo GC• Cornejo GC Discharge Pressure, as an MAOP to

force TGNET to control by flow (Cornejo GC is controlled by flow, through a pressure setpoint).


Operation

Output data – Predicted Future State

• Clients Pressures and Flows• Pressure at valve locations• Pressure, Flow and Power at compressor

stations.


PI DataLink Add InnUser options:

Generate Transient data

Generate Prediction

Transient Re Start

Import Values from TgNet Model

Data Validation and export to PI


Sample Results Obtained

Detailed compressor station calculation: Units, RPM y Power

Linepack change validation.

Initial – Final, Balance.

Actual vs. Simulated.


Sample results, Pressure Profiles History, Actual and Predicted (Activex Add Inn for ProcessBook)

Pressure Profiles (along the pipeline length) :

•history

•real time

•next hour

Real Time and Model Based Variables

A custom ActiveX was developed to show Time Series & Spatial values on the Process

Book


•Using SCAN, a PI DataLink and PI-ACE based application development tool.

•Off Line modeling tool that runs as an add in to PI DataLink

•On Line analysis models runs on PI-ACE, model values are sent to PI Server and shown on ProcessBook and Excel

•Dedicated models were developed for pipeline valves and compressor perfomance supervision.

•Model parameters are managed in PI-MDB

Advanced analytical applications for equipment and pipeline perfomance

monitoring


Compressor Modelling Operation Mapping

Operation point is shown using the

Compressor curves as calculated based on the

actual operating conditions.


Actual operation is compared with the simulation of “best” cases.


Smart diagnostic of pressure control valves •Verification of real vs. theoretical operation, using real time data from PI and a Valve Model. •Monitor performance of control valves variables in order to meet with standard practices as per IEC 60534 related to industrial control valves performance. •Uses on-line PI-ACE model calculations of control valve performance, including percentage of opening, noise level, critical conditions and performance curves.


Valve Model, Module DataBase Editor

Model Parameters Management


Statistical Multivariate analysis

Purpose:

evaluate the operation against empirical (statistical) models and then be able to early detect abnormal conditions.OFF Line analysis and Model Build is done using SCAN OffLine, that works with DataLink/Excel.

Models are then downloaded to PI-ACE, using the SCAN Online shell.

Using PI-MDB, Input/Output Tag´s are then assigned to the models, calculated values are sent back to PI, for displaying, alarming and reporting


Multivariate Analysis, examples

1 Real vs. Predicted values for the output pressure of a Gas Station showing a good fit for the theoretical model

2 Model parameters are trended, showing a deviation from the pattern limits

3 Individual Statistical Indexes are trended, three of them showing an abnormal variability, Pattern indexes shows the deviation trend in advance as compared to the individual variables deviations


•Few statistical indexes allow for complex variable relationships representation.

• Indexes provide early alerts for process deviations

•Drill from aggregated indexes down to individual variables give the “problem explanation”

Perfomance Analysis, summary

•Phenomenological and empirical models allow for the online supervision of the pipeline


Thank you for your attention…

The value of GasAtacama Operational Intelligence solution, based on OSISOFT platform, comes into effect when pipeline users take actions based upon the information provided by the solution.

Documents

Operational Intelligence in Pipeline Natural Gas Transmission Wilson Navarrete, [email protected] Luis Yacher, [email protected]