Realizing the Full Value of Industrial Internet and Data Analytics in LNG Facilities

Transcription

1 INFRASTRUCTURE MINING & METALS NUCLEAR, SECURITY & ENVIRONMENTAL OIL, GAS & CHEMICALS Realizing the Full Value of Industrial Internet and Data Analytics in LNG Facilities Jaleel Valappil, David Messersmith Bechtel Oil, Gas and Chemicals Kelly Knight Bechtel Nuclear, Security and Environmental Level 4 - Bechtel Public

2 Presentation Overview Introduction to Industrial Internet (IIoT) Key Application Areas in LNG Operations Process monitoring, Predictive maintenance, Process optimization Leveraging Existing Assets Benefits of EPC Phase Implementation Case Study in Data Analytics LNG plant amine system monitoring 2016 Bechtel 2 Level 4 - Bechtel Public

3 Introduction to Industrial Internet/Data Analytics Digital Transformation Enabled by Cloud computing Decreasing cost of sensors, storage, bandwidth Big data analytics and Sensor technology Analytics Integration of Physical plant and Digital information IT (ERP/CRM etc.) and OT (DCS/PLC etc.) Cybersecurity IT and OT security challenges Site 1 Site 2 Site 3 Office 2016 Bechtel 3 Level 4 - Bechtel Public

4 Operations Information Application Industrial Internet/Data Analytics Industrial Internet Domains/Solutions Includes new ways of using existing technology OEM, Automation provides and others IIOT Functional Domains (IIC) Business Sensors Wireless sensors/intelligent sensors Vibration Monitoring Virtual sensors Big Data Analytics Ability to deal with large datasets Higher resolution/storage Better analytics Machine learning Sense Control Actuation 2016 Bechtel 4 Level 4 - Bechtel Public

5 Applications of Industrial Internet Applications Related to LNG Facility Operation Process Optimization Value Predictive Maintenance Anomaly/ Fault Detection Data Analytics Exploratory/ Statistical Analysis Complexity 2016 Bechtel 5 Level 4 - Bechtel Public

6 LNG Process/Equipment Monitoring Tracking Key Performance Indicators (KPI) for LNG Efficiency, Production, Yield, Quality Condition and Performance Monitoring of Equipments Process Control Monitoring Ensure loops are in auto and working Abnormal Situation management/anomaly or Fault Detection Enhancement of safety Reduce plant downtime Early detection of anomalies Operator intervention» Fault diagnosis important 2016 Bechtel 6

7 LNG Process/Equipment Monitoring - 2 Approaches to Fault/Anomaly Detection Numerous Application Areas in LNG Amine system and dehydrators Heavies/Scrub Columns Plate and Frame and Other Exchangers Fundamental Model Based Historical Data Based Supervised (Known Fault Samples) Unsupervised (Learn Online) 2016 Bechtel 7 Level 4 - Bechtel Public

8 LNG Production Asset Management - Predictive Maintenance Continuous Monitoring and Prediction of Equipment Conditions 82% random failure pattern Benefits Compared to Reactive/Preventive Maintenance (ARC) Reduction in maintenance cost (50%) Reduction in unexpected failures (50%) Increase in MTBF (30%) Increase in availability (30%) Time Idle Plant 2016 Bechtel 8 Level 4 - Bechtel Public

9 Equipment Condition Asset Management - Predictive Maintenance - 2 Failure Latent Error and Enabling condition Methodologies for Predicting Failure Engineered algorithms Supervised learning for prognostics Optimal Asset Condition Over Time Predictive maintenance detects problems early» Models for Remaining Useful Life (RUL)» Model for probability of failure in time Unsupervised learning techniques Broken Cost to repair» Limited failure history Time Application Areas in LNG includes Turbomachinery Heat exchangers/valves etc. Physical Model Machine Learning Statistical 2016 Bechtel 9 Level 4 - Bechtel Public Prognostics

10 LNG Plant Optimization LNG Process Optimization Current Status Advanced Process Control (APC) Supervisory Systems Real Time Optimization (RTO) not Common Opportunities from Industrial Internet Supervisory optimization (Less frequent) Smaller units/equipments that are currently ignored Enterprise-wide optimization (Multiple facilities) Supervisory Optimization APC DCS 2016 Bechtel 10 Level 4 - Bechtel Public

11 LNG Plant Optimization - 2 Typical Application Areas in LNG Maximizing Plant Efficiency Optimum Process Conditions MR compositions, Other operating parameters Operating point for compressors to enhance efficiency Optimal load distribution between compressors 5-15% power reduction reported in studies 12.9% (Wang et al., 2012) 4.5% (Alabdulkarem et al., 2011) Energy Optimization for Utilities 2016 Bechtel 11 Level 4 - Bechtel Public

12 Existing Assets for Data Analytics Process Knowledge Key to Successful Applications Selecting right variables Selecting right objectives for optimization Digital Plant Information Digital repository of plant information EPC project data for greenfield facilities Existing Control Infrastructure Working with DCS/PLC systems Starting with supervisory levels and gradual move to base layer 2016 Bechtel 12 Level 4 - Bechtel Public

13 LNG Simulation Models and Digital Twins Existing Assets Steady State/Dynamic Models Operator Training Simulator Computational Fluid Dynamics Models Applications Selection of Variables/Causality Model Based Optimization Boosting Data Models IIoT Process Model/OTS 3D Models Digital Data Digital Twins for LNG Plants 2016 Bechtel 13 Level 4 - Bechtel Public Equipment Model

14 EPC Phase Implementation of IIoT Benefits of Early Implementation Preparing sensors/it infrastructure Configuring models based on process/project information Testing during startup and commissioning Avoiding Retrofits after Commissioning LNG PLANT EVOLUTION EPC IT Infrastructure Sensor Selection Model Scoping Startup Commissioning Model Development System Testing Operations Model Refinement Implementation 2016 Bechtel 14 Level 4 - Bechtel Public

15 Case Study Anomaly Detection Monitoring of Amine System in LNG Plant Amine system performance important CO 2 removal Anomaly Detection Method used Identify abnormal operation considering group of variables Statistical approach using data Operating Data from Plant after Startup About 320 tags for amine system Seven months of operation Wash Water Inlet Feed Separat or Optional Absorber LC FC LC FC Treated GasC3 Chiller KO Drum Regenerator Wash Water Flare FG LC Mole Sieve Dryers Air Cooler Condenser LC Reboiler Acid gas to SRU Sulfur recovery Reflux Drum Flare Performed in Offline Mode Rich Amine Flash Drum LC Antifoam L/R Amine Exchanger Amine Surge Tank Lean Amine Cooler Antifoam Filtration Pkg Bechtel 15 Level 4 - Bechtel Public

16 Anomaly Detection System Set-up Big Data Analytics Framework/Tools Splunk - Machine data database and indexer Prelert Anomaly detection tool Neo4j Graphical database Design Data from Smartplant Instrumentation Captures relationships among tags, equipment Enables setup of monitoring system with minimal effort LNG Plant Data Neo4j Splunk Prelert Anomaly Scores SmartPlant Instrumentation Level 4 - Bechtel Public 2016 Bechtel 16

17 Anomaly Detection - Methodology Predictive Model Consists of Statistical Probability Distribution Bayesian distribution modeling Fit is determined by unsupervised machine learning Distributions have different shapes (Not just bell curves) Distributions used to determine what is unexpected (anomalies) Anomaly Score Normalized Probability Score Score measures level of unusualness Output has no false positives or negatives 2016 Bechtel 17 Level 4 - Bechtel Public

18 Anomaly Detection Approaches Three Different Approaches All amine tags used to calculate anomaly scores (unit-wide) Individual equipment tags to calculate separate anomaly scores Clustering based on Smartplant Instrumentation Individual groups to calculate separate anomaly scores Obtained from process understanding Wash Water Optional Absorber FC LC Treated GasC3 Chiller KO Drum Regenerator Mole Sieve Dryers Air Cooler Condenser LC Flare Acid gas to SRU Sulfur recovery Reflux Drum Separator Performance Acid Gas Extraction Inlet Separat Feed or LC FC Wash Water Rich Amine Flash Drum Amine Inventory Amine Surge Tank LC Flare FG LC Acid Gas Reboiler Removal Antifoam L/R Amine Exchanger 2016 Bechtel 18 Level 4 - Bechtel Public Antifoam Filtration Pkg. Lean Amine Cooler

19 Case Study Scenario 1 Increase in CO2 to >100ppm Caused by Amine Regenerator Operation Reflux failure leading to increase in regen column pressure Anomaly Score - Regenerator CO 2 Composition Column Pressure 2016 Bechtel 19 Level 4 - Bechtel Public

20 Case Study Scenario 2 Increase in CO2 to >100ppm Caused by Increase in Feed Gas CO 2 Concentration Column differential pressure increases CO 2 Composition Anomaly Score - Absorber Feed Gas CO2 Column Diff. Pressure 2016 Bechtel 20 Level 4 - Bechtel Public

21 Case Study Root Cause Analysis Ability to Quickly Evaluate the Root Cause Equipment contribution to anomaly score Further drill down to particular tag Contributor to Anomaly 2016 Bechtel 21 Level 4 - Bechtel Public

22 Thank You and Questions 2016 Bechtel 22 Level 4 - Bechtel Public