Phase I Preliminary Design Report - FINAL

Transcription

1 Phase I Preliminary Design Report - FINAL Riser Lifecycle Monitoring System for Integrity Management Contract November 18, 2014 Judith Guzzo, Principle Investigator, and Team: Uttara Dani, Brandon Good, Jeff Lemonds, Shaopeng Liu, John Carbone, Mike Volk GE Global Research One Research Circle Niskayuna, NY

2 Table of Contents Table of Contents...2 Executive Summary...3 Task 5- Overall RLMS System Design using TRL 5 & 6 Subsystems...4 Subtask 5.1 Voice of the Customer (VOC) Effort...4 Summary of Approach...4 Preliminary VOC Results...5 Initial Framework of Cost/Benefit Analysis...8 Subtask 5.2 Preliminary System Design and Risk Analysis for Key Subsystems Summary of Preliminary System Design for RLMS Summary of Failure Modes and Effects Analysis for RLMS Subsytems Subtask RFID Subsystem for Asset Identification for RLMS Initial Design Criteria for RFID in RLMS System Technical Approach Failure Modes and Effects Analysis Next Steps Subtask Subsea Sensing & Acoustic Telemetry Subsystem for RLMS Initial Design Criteria for Subsea Platform Technical Approach & Results Failure Modes and Effects Analysis Next Steps Subtask Vibration & Fatigue Analysis Methodology for RLMS Initial Design Criteria for Vibration and Lifing Analysis Technical Approach and Results Failure Modes and Effects Analysis Next Steps Subtask Software Management Subsystem for RLMS Initial Design Criteria Technical Approach & Results Failure Modes and Effects Analysis Next Steps

3 Executive Summary The objective of this two-phase project is to develop an integrated, reliable, and commercially viable solution for a real-time, telemetry-based marine Riser Lifecycle Management System (RLMS). RLMS is an integrated system of hardware and software tools comprised of sensors located on select riser joints, wireless subsea communication between the vessel and select instrumented risers, and software for data collection, processing, riser fatigue analysis, visualization and alerts for enhanced operational decision-making for contractors and operators. The initial focus is on drilling risers but this technology could translate to production risers. Summarized herein are initial Phase I results which focus on the RLMS technical solution design, development, and risk retirement. Initial end-user requirements for an integrated structural riser monitoring system design were obtained using Voice of the Customer (VOC). This information was collected from drilling contractors, an offshore classification society, and riser offshore engineering manufacturer subject matter experts. Using Six Sigma methodology, this VOC was then translated into preliminary system user requirements for a RLMS System, and functional design specifications for select subsystems using a Quality Function Deployment (QFD) tool. An initial framework for a cost-benefit analysis (CBA) is presented to evaluate all relevant costs and benefits of the RLMS solutions, with the goal to quantitatively assess whether oil and gas users, public and private enterprises, and government agencies would experience a net benefit from the proposed RLMS solution (note, the formal CBA will be completed in Phase II). For each RLMS subsystem, the initial design criteria based upon the VOC is presented. This is followed by the preliminary system design, technical approach, initial test results, failure modes risk analysis (FMEA) results and next steps. The key RLMS subsystems are RFID, subsea sensors, acoustic communication, vibration and fatigue analysis, topside software and architecture. Operational considerations such as RLMS system installation and maintenance are considered as well. 3

4 Task 5- Overall RLMS System Design using TRL 5 & 6 Subsystems Subtask 5.1 Voice of the Customer (VOC) Effort Summary of Approach For the preliminary Riser Lifecycle Monitoring System (RLMS) design, the team identified key stakeholders for Voice of the Customer (VOC) input into a structural riser monitoring system for deepwater marine drilling. Initial VOC was obtained from drilling contractors, an offshore classification society, and riser offshore engineering manufacturer subject matter experts. Benefits and innovation of this system include: 1. Modular and open subsea platform approach - for ease of installation, near real time data backhaul with acoustic telemetry and open sensor Input and Output for commercial-off-the-shelf (COTS) sensor integration. This system will produce highquality, time-synchronized measurements of riser response to environmental and operational excitation at several discrete subsea sensor data logger installation points along the riser length 2. Economical sensor node placement to reduce impact on riser running operations and address criteria in Cost-Benefit Analysis. 3. Intelligent Decisioning System for Continuous Calculation of Fatigue Damage and Key Performance Indicators - for enhanced visibility during drilling operations, to identify highly fatigued riser joints and optimize riser configuration post extreme events. Display real-time frequency and time measurements. Display fatigue damage rate and cumulative damage estimates at any elevation and angle around the riser circumference, along with intermediate results (excited modes, modal contribution to vibration, etc.) at specified intervals (e.g. hourly). 4. Performance-based Inspection Track the accumulated fatigue damage on a perjoint basis, to aid in joint rotation and optimize inspection schedule & estimate remaining useful life (re: condition- based monitoring). The above features and benefits enable realization of a Fleet Wide Lifecycle Management System as a tool to enhance safety, optimize drilling operations and future equipment design and provide information to the industry (OEM s, contractors, operators, regulatory) for data-driven inspection and maintenance of riser equipment. In Phase I of the program, the framework for a cost-benefit analysis (CBA) is being developed by Dr. Michael Volk, in conjunction with the GE team and WPG/Project Champion, to evaluate all relevant costs and benefits of the RLMS solution. The final analysis will be performed in Phase II (Task Business Model Analysis and Cost vs. Benefit Assessment). 4

5 Using Six Sigma methodology 1, the VOC was then translated into preliminary system user requirements for RLMS, and functional design specifications for the Subsea Sensor Platform using a Quality Function Deployment (QFD) tool. This tool is a quantitative mechanism to translate customer needs into prioritized technical requirements and facilitates communications of Customer-to-Quality needs and design (CTQs) between the key stakeholders (e.g. customer, business and technical team) and reduces risk of program delays. This iterative process will be used to refine and validate the Riser Lifecycle Monitoring System (RLMS) user requirements and product functional design specifications during the remainder of the program (Phase I and II) with additional stakeholders and SME s. From this VOC, an initial framework for a cost-benefit analysis of the proposed preliminary solution design has been developed. Objectives of the VOC are to obtain an understanding of the following: Current challenges during drilling operations Expected value & benefits Actions that can be taken based on a near real time monitoring system System installation & maintenance needs (e.g. operationalization requirements) Expectations for system requirements/functionality Economics/Return on Investment (ROI) Preliminary VOC Results A prioritized summary of customer needs from the VOC includes: 1. Enhance Operations & Reliability Provide high availability to drill Keep riser in service (e.g. how much longer can risers stay in service compared to expected design life?) Facilitate planning of riser configuration Increase operational window and monitoring of safety margins 2. Impact Inspection and Maintenance (I&M) schedules Condition based maintenance of deployed and stored equipment Performance based Inspection: o Accurately measure, record and evaluate riser utilization and inspection criteria (Table 1) 5

6 Table 1: Summary Inspection Criteria and Riser Utilization Criteria Impacted by Riser Monitoring System 3. Easily retrofit and install on existing risers Minimal impact on operations 4. Real time loads & tension near wellhead Risk aversion strategy (e.g. reduce uncertainty in variation in tensioners/ ability to accurately monitor & calculate tension in the riser at key points) Maintain integrity of well head 5. Cost effective Translate benefits to ROI 6. Rugged, reliable & accurate system Environmental deployment (e.g. at 10,000 ft), operational handling & storage conditions 7. Intuitive User Interface (UI) with actionable information Visibility of real time critical information to operator Present results of analysis of relevant data to rig crew in real-time in a comprehensive way, and such that the rig crew can optimize the rig and riser operation, compare with operating limits, and take necessary action to avoid exceeding the specified operating limits These prioritized customer expectations are summarized below in Table 1, and are used to construct the first House of Quality (House 1) which translates Customer Needs into RLMS System Requirements (Figure 1). 6

7 Table 2: Summary of Initial Customer Expectations for Riser Monitoring System 5= high importance 3= medium importance 1= low importance House 1 System CTQs (Xs or HOWs) Customer Expectations (Ys or WHATs) Importance Real-time advisory Information for riser operations Ability to retrofit and install on existing installatio 5 H H M M M 135 Enhance operations reliabilty (e.g. Impact oper 5 H H H 135 Impact inspection & maintenance schedules wit 5 H M M M M 105 Rugged, reliable and accurate system 5 H H H H 180 Cost effective 3 M H 36 Simple, intuitive, easy-to-understand user exper 3 H 27 Total Online stress and fatigue level estimation Easy, tetherless installation Mimimal impact on existing operations, processes Rugged construction of system Sufficient system operation life Reduce uncertainty in variation of riser tensioner, well head loads, etc. Low cost ownership Actionable info with varing information levels depending on user roles Total Figure 1: Translation of Customer Needs into Initial System Design Requirements for Riser Monitoring System 7

8 A Pareto diagram of prioritized system requirements for a RLMS System (Figure 2) highlights attributes key to a successful system design that will be accepted by the industry (e.g. easy, tetherless installation that does not interfere with existing riser operations). This process will continue to be refined and validated by industry SME s throughout the program. Figure 2: Pareto of Prioritized System Requirements for Riser Monitoring System Initial Framework of Cost/Benefit Analysis As part of Phase II (Task Business Model Analysis and Cost vs. Benefit Assessment) of the program, the GE team, in conjunction with Dr. Michael Volk, will conduct a rigorous cost-benefit analysis (CBA) to evaluate all relevant costs and benefits of the RLMS solution. The goal is to quantitatively assess whether oil and gas users, public and private enterprises, and government agencies would experience a net benefit from the proposed RLMS solution. The methodology entails the systematic estimation of all benefits and all costs of a contemplated course of action in comparison with alternative courses of action. Note the framework for the CBA is being developed in Phase I, including the criteria information drilling users will see (Figure 1), and the formal CBA will be performed in Phase II. CBA considers both gains and losses to all members of the community, including offshore oil and gas users, public and private enterprises, and government agencies, who are affected by the project. This analysis will not concentrate solely on the financial implications of a project but other tangible and intangible externalities that must be assessed. The analysis for this project will include a forecast of the costs and benefits of each option (i.e. without project and with-project, e.g. incorporating GE s RLMS for Integrity Management) to convince end users to implement the operational improvements. In developing a CBA model for this project, the following key elements will be included: 8

9 Scenario A: Benchmark or base case or without-project scenario which represents the current level of service Scenario B: Case with Riser Lifecycle Monitoring System implemented for drilling contractor and/or operator Planning period/horizon Identification and estimation of costs over the planning period including operating expenditure (opex), capital expenditure (capex), social and environmental costs for the RLMS Solution Provider (RLMSP). Table 3 highlights example of the tangible and intangible costs that will be used: Table 3: Examples of Tangible and Intangible Costs in Framework for CBA Tangible Costs (monetary) Price of equipment (CAPEX) Start-up fees (Development costs) Licenses Shipping, handling and transportation costs Operating expenses (OPEX) Field trials Testing Maintenance Staffing costs (wages, training, etc.) Real estate (rental offices, etc.) Insurance and taxes Utilities Intangible Costs (non-monetary) Cost of time spent on project Imperfect processes Cost of energy spent on project Cost of adjusting an established routine Cost of any lost business during project implementation Risk factor value for safety and customer loyalty Market saturation or penetration from uncertainties Influence on one s reputation Identification and estimation of the benefits for a Riser Lifecycle Monitoring System, to customers and society as a whole over the planning period (expressed in terms of monetary benefits, cost savings or both). Potential project benefits would include:. Income produced (increased sales) Money saved (expense reduction/decreased cost of service) reduced service and maintenance cost Time and effort saved (productivity savings) Repeat customer business Referrals, customer satisfaction, happier employees, a safer workplace Operate in increasingly deeper and harsher environments Reduced likelihood of event occurrence, enhance safety Risk and sensitivity analysis to integrate risk and uncertainty into the framework. An initial framework for this analysis is under development as part of Phase I to ensure the team gathers critical information (e.g. hardware, software, labor costs, and potential benefits) relevant to the analysis. 9

10 Subtask 5.2 Preliminary System Design and Risk Analysis for Key Subsystems Summary of Preliminary System Design for RLMS Based on initial VOC and identification of initial System Design Requirements (Figure 1), the following enabling technical design elements for the RLMS solution are required: 1. Radio-Frequency Identification (RFID) to automate marine riser identification and to enable topside riser analytics, riser pedigree, and Condition Based Maintenance (CBM) 2. Subsea Sensing and Communication for marine riser monitoring and near real time tetherless data transmission, and to enable CBM 3. Vibration and Fatigue Analysis for topside surface alerts during drilling operations and for estimated riser life prediction 4. Topside Software for data acquisition, RLMS analytics and intuitive user interface Figure 3 summarizes these design elements, highlighting functionality of the Subsea Sensing and Acoustic Platform and the underwater and surface analytics. Detailed design elements, risk assessment and next steps in Phase I for each subsystem are described in subsequent sections of this report. Figure 3: System Design for RLMS based on VOC 10

11 The QFD process was used to translate output from House 1 (Figure 1) into Subsystem Product Design specifications. By example, this is shown for the Subsea Sensing and Acoustic Platform (Figure 4). House 2 System CTQs (Xs or HOWs) Product Fuctionality Importance Wireless/acoustic communication from subsea to surface Battery powered Report extreme events, high tension/stress occurrences along the riser Measure acceleration and angle at selected locations on the riser Easy, tetherless installation 5 H H M L 110 Mimimal impact on existing operations, process 5 H H H H M 195 Online stress and fatigue level estimation 5 H H H H H M L 245 Real-time advisory Information for riser operatio 5 H H H H H M M L 260 Reduce uncertainty in variation of riser tensione 5 H H H 135 Rugged construction of system 5 H 45 Sufficient system operation life 5 H H L 95 Actionable info with varing information levels de 3 H H 54 Low cost ownership 3 M M H 45 Total Monitor/estimate the actual tension at riser tensioner Measure/estimate loads at critical locations, e.g., wellhead, slick joint, flex joint, etc. Rugged system packaging that is resistant to tough handling: "roughneck", and withstand ru Low overall/equivalent system supply current Simple attachment mechanism, e.g., magnetic installation, or ROV deployable Interface to external existing sensors on the riser Platform generic HW/SW design, not customized, suitable for various riser types Reconfigurable SW user interface SW platform that allows customized SW development Energy harvesting Total Figure 4: Translate System Requirements for Riser Monitoring System to Functional Design Specifications for Subsea Sensing and Acoustic Platform 11

12 House 2 Pareto Wireless/acoustic communication from Battery powered Report extreme events, high Measure acceleration and angle at Monitor/estimate the actual tension at Measure/estimate loads at critical Rugged system packaging that is resistant Low overall/equivalent system supply Simple attachment mechanism, e.g., Interface to external existing sensors on Platform generic HW/SW design, not Reconfigurable SW user interface SW platform that allows customized SW Energy harvesting Figure 5: Pareto of Functional System Requirements for Subsea Sensor Platform A Pareto diagram (Figure 5) of the prioritized Functional System Requirements for the Subsea Platform highlights functionality key to a successful RLMS system design that will be accepted by the industry. Again, this process will continue to be refined and validated by industry SME s throughout the program. Summary of Failure Modes and Effects Analysis for RLMS Subsytems A Failure Modes and Effects Analysis (FMEA), or risk analysis, was performed by the team for the following six key categories: (1) RFID, (2) Subsea sensor package, (3) Subsea acoustic communication, (4) vibration and lifing analytics, (5) Topside data acquisition and software and (6) System installation and maintenance. The team rated each risk by severity, probability and detectability, with the following definitions for each: Sev = Severity of consequences if failure mode activates 1: minor performance loss 2: results in partial system malfunction 3: renders product unfit for service OR could cause injury OR dissatisfies customer Prob= Probability of occurrence of failure mode 1: very low probability 2: occasional occurrence 3: very likely to occur Detect = Detectability of activation of failure mode 1: defect is obvious or detection process can be automate 2: detection requires manual inspection 3: defect is not detectable OR difficult or expensive to detect RPN = Severity x Probability, with note of Detectability-rating 12

13 From the 66 risks identified (Figure 6), 3 emerged as high Probability and high Severity (red), and 14 risks emerged as medium or high Probability and medium or high Severity (orange). Risk mitigation plans were assigned to each potential failure mode. Probability Severity L M H H M L Figure 6: Output Summary from FMEA on RLMS Table 4 provides the details for the 17 High and Medium-High Priority Risks. These are the focus for Phase I and Phase II of the program. Detailed discussion for key subsystems is discussed in subsequent sections of this document. Table 4: Summary of High and Medium-High Priority Risks for RLMS HIGH PRIORTY (3 Risks) System Installation & Maintenance Risk / Failure Mode Sev Prob Detect RPN Batteries run out during drilling campaign Acoustic Communication buoyancy module blocks acoustic link Acoustic Communication Transducer beam pattern not appropriate Acoustic Communication excessive acoustic noise from working enviroment MED HIGH PRIORTY (14 risks) Vibration & Lifing Analytics Data screening not accurate Vibration & Lifing Analytics Vibration & Lifing Analytics Ocean currents only measured to a certain depth Unavailability of real time ocean current/velocity measurements Vibration & Lifing Analytics Complex components (BOP, LMRP) not modeled or fidelity is too low TopSide Data Acquisition System and Software No data in Historian TopSide Data Acquisition System and Software Bad data in Historian System Installation & Maintenance HW system leaking saltwater System Installation & Maintenance broken cabling Acoustic Communication Transducer beam pattern not appropriate Acoustic Communication No certification to perform field testing Subsea Sensor Package not enough sensor sampling data for analytics Subsea Sensor Package sensors installed to insensitive location Subsea Sensor Package can't reliably detect events of interest by customer (e.g. real time tension near wellhead) RFID modification of riser for tag (e.g. drill holes)

14 Since System Installation & Maintenance is not one of the five technical areas discussed in this document, the FMEA is shown below (Table 4). The FMEA is an iterative process which will be updated and refined through the life of the program by the WPG and project champion. Table 5: FMEA Results for System Installation & Maintenance Saftey Risk / Failure Mode Sev Prob Detect Issue? RPN Risk Mitigation Plan Create procedure for power loss & replacement. Batteries run out during drilling campaign Develop/Optimize the battery model HW system leaking saltwater Robust sensor node packaging design and testing Broken cabling SOP with customer & HW certification Sensor package interferes with riser depoyment Sensor packaging design with O&G Chief engineer Batteries run out after 1 drilling campaign Create procedure to evaluate power state (e.g. visual, etc) & process for device or battery replacement Hardware disconnects SOP for HW setup and training plan for HW I&M Don't meet regulatory requirments/certification for field trial Review cert. requirements with customer & DNV Modem function unreliable or impared without firmware updates Create procedure for firmware updates Dead subsea modem SOP for predeployment testing of modems Subtask RFID Subsystem for Asset Identification for RLMS RFID technology will be utilized to identify each riser section for the drill string and to enable topside riser alerts and analytics (condition-based maintenance). RFID is an enabler to automate processes such as riser string reading and configuration, and enable the analytics and riser pedigree/utilization. Complete hardware and software solutions are not readily available on the market today for this application (e.g. stationary readers for automated reading during string deployment). Some development work thus far has been done by riser or drill pipe manufacturers, and they are selling the technology as part of their commercial riser systems. solutions. Since RFID technology is relatively mature and has lower technical risk compared to other RLMS sub-systems (e.g. vibration and fatigue analytics), the objective for this RLMS subsystem is to evaluate existing ruggedized RFID hardware for riser identification and incorporate the tag data into the overall RLMS being developed. Initial Design Criteria for RFID in RLMS System The following are initial design criteria to address customer CTQ s identified in Table 1: 1. RFID Reader will be handheld and dockable 2. RFID Reader battery life will last for an entire drilling campaign (3-6 months) 3. RFID Reader will be ruggedized and water resistant

15 4. RFID Tags will attach to the riser without requiring modifications 5. RFID Tags will withstand 5,200 PSI and F 6. RFID Tags will be passive (no battery) 7. RFID Tags will read from 2ft away 8. RFID Tag placement will not interfere with riser operations 9. Riser sections will be scanned during staging before going to the spider Technical Approach The RFID system will consist of a handheld reader and RFID tags attached to each riser section. The tags will be attached to each riser before the riser string assembly process is started. Each tag will be associated with the riser s unique ID and stored in the backend system. At the beginning of the riser string assembly process, the handheld will start a new riser string build list. The rig worker will use the handheld to scan each riser section as it is being selected to add to the riser string. The handheld will add the scanned tag to the riser string build list. At the end of the riser assembly process, the handheld will have a complete build list of the riser sections and the order they are connected. The handheld will be docked and the riser string build list will be uploaded to the onsite workstation. This file will be utilized by the vibration & fatigue analysis software. After an extensive analysis of RFID Commercial-off-the-Shelf (COTS) technology based on the above design criteria, three systems have been down selected for purchase and lab testing (Table 6). Each system is from a different RFID frequency family (125 khz, MHz, 915 MHz) and will be tested and validated against the design criteria. Using a tradeoff matrix for quantitative assessment, the highest performing system will be implemented in the final solution. Table 6: Summary of Three RFID Systems for Lab Testing Failure Modes and Effects Analysis Table 7 shows the results of the FMEA performed for the RFID subsystem. A majority of the Failure/Risks are low severity/probability and do not require mitigation plans. Riser modification for tag installation emerged as the highest risk item. A majority of the RFID riser management solutions on the market require modification of the riser for installation. 15

16 This program and pilot will mitigate this risk be selecting an RFID system that can be attached without structural modification to the riser. Table 7: FMEA Results for RFID Subsystem Next Steps Risk / Failure Mode Sev Prob Detect Three RFID systems have been purchased and will be evaluated in our lab. 1. Develop lab test plan and conduct lab testing; down-select top RFID subsystem based on design criteria: a. System performance b. mechanism to attach tags to riser section 2. Write handheld application to collect tag IDs and build riser string list., This application will have a simple User Interface for the rig crew user. 3. Develop Docking Solution and Test Upload Process 4. Develop SOP for RFID system operation 5. Plan for field trial testing and vendor validation (Phase II) Subtask Subsea Sensing & Acoustic Telemetry Subsystem for RLMS Initial Design Criteria for Subsea Platform Saftey Issue? RPN Risk Mitigation Plan riser modification for tag (e.g. drill holes) Pick RFID technology that doesn't require modification HH battery dies Have extra charged batteries on hand HH User Operation error Simple User Interface-- SOP's HH reads too many tags Chose tag technology/size to limit read distance electrostatic discharge from HH Y 3 Get Ruggedized ATEX Reader tag interferes with riser operation Get VOC for tag placement Drillstring out of sequence Notify user that wrong section has been selected riser failure due to tag placement Avoid modifying the riser to attach tag equipment damaged by dropped HH Y 3 Tether HH to User HH will not read tag Move closer to the tag lost riser string build file system testing & validation; SOP for operator dock HH fails system testing & validation; SOP for operator HH freezes - data lost system testing & validation; SOP for operator HH breaks / drop HH into water system testing & validation; SOP for operator tag installed on wrong riser SOP for operator tag stops reading system testing & validation; SOP for operator tag falls off riser system testing & validation; SOP for operator The primary customer expectations (Table 1) in the preliminary QFD design (Figure 1) drive the system CTQs and define the initial design criteria for the Subsea Platform: 16

17 Integrated Acoustic telemetry, allowing real-time or near real-time condition monitoring and alerts A modular platform, integrating commercial off-the-shelf (COTS) motion sensors (accelerometer + gyro), interfaces for additional sensor data acquisition, processing capability for customized edge computation and analytics, wireless communication, storage for data backup when wireless not present, battery, and marinized pressure vessel/casing Plug-and-go and battery powered, eliminating the requirement of auxiliary cabling, and minimally impacting existing operations Open OS environment on the processor, allowing customized software application development for interfacing with additional sensors, performing signal processing, and edge analytics. These features differentiate the proposed Subsea Platform from existing products. Note that the detailed specifications will depend on the overall design of the entire RLMS system, considering both the Subsea Platform and the vibration and fatigue analysis, with the goal of optimizing the system battery life and analysis performance. Technical Approach & Results The Subsea Platform uses a modular design approach, aiming to provide a plug-and-go system for easy installation and minimal impact on existing operations. The platform consists of the following seven components, as seen in the system architecture (Fig. 7), where COTS components are leveraged as much as possible for optimized cost: Acoustic Modem and Transducer. The subsea platform will integrate an acoustic modem with transducer attached enabling underwater wireless communication to the topside of a drilling vessel. The subsea platform leverages the acoustics for data transmission from the subsea platform to the topside data center, as well as for platform management and control when needed. Micro-Modem 2, a small-footprint, low-power acoustic modem developed by the Acoustic Communications Group at the Woods Hole Oceanographic Institution (WHOI), is being evaluated for integration in the Subsea Platform. A COTS acoustic transducer was selected from those on the market by considering the specific beam pattern design in the actual ocean environment. Battery. A rechargeable Li-ion battery will be used to power the subsea platform and eliminate the use of auxiliary cabling. A detailed and scalable battery model is being developed to estimate and optimize the Subsea Platform battery life. Various aspects of the RLMS system specifications have been factored into the model, such as the sensor data sampling interval, sampling duration, and sampling rate, as well as the selection of the acoustic transmission power level, transmission rate, etc. Depending on the choice of the above system specifications and the intended battery life, the battery model will output the estimated battery size/capacity, and vice versa. 17

18 Potential risks of overheating in the subsea platform are minimal, primarily due to 1) the colder subsea environment becomes a natural heat sink, and 2) the electronics in the subsea platform, which are mostly COTS components, have been used in many subsea deepwater applications by the vendor, Woods Hole Oceanographic Institution. As such, WHOI have not observed issues related with heat generation. Sensors and Sensor Interfaces. Each subsea platform will consist of two motion sensors: one triaxial accelerometer and one triaxial gyroscope (angular rate sensor). Together with the vibration and fatigue algorithms (Subtask 5.2.3), it is expected that loads and stresses at different sections of the risers and related fatigue levels will be calculated using the motion sensor data. Both the accelerometer and gyroscope are COTS components with high sensitivity for the low vibration conditions of drilling risers. The Subsea Platform will also have additional sensor interfaces such as serial/rs232 connections, I2C/SPI digital interfaces, analog-todigital conversion I/O, etc., that are open to end users to connect existing field sensors to provide real-time visibility for topside control. Microprocessor. A single board computer will serve as the edge intelligence of the subsea platform, and will control the acquisition of the sensor data, perform signal processing and/or algorithms on the collected data as needed, manage the acoustic communication protocol, data backup/storage, and power management. The open Operating System (OS) on the microprocessor will provide spaces for users to develop customized software applications, e.g., user specific analysis on the sensor data. The microprocessor will also host flash memory allowing secondary data backup and storage in case of situations when the acoustic link is down. Figure 7: Subsea Platform System Architecture 18

19 System Functionality Testing & Preliminary Results A laboratory test setup has been prepared for the Subsea Platform system functionality testing. The block diagram is shown in Figure 8. To streamline lab testing, one subsea acoustic modem and one surface modem have been assembled in a benchtop modem box, between which Bayonet Neill Concelman (BNC) connectors are used to simulate a perfect acoustic channel. Real acoustic environments will be simulated by adding artificial noise into the BNC cable. A processor is connected to the subsea modem through serial connection, and an accelerometer and gyroscope are connected to the processor via the I2C interface. A laptop containing the acoustic communication protocol is connected to the surface modem via serial port. The laptop also hosts the user interface for topside data collection and display. Figure 9 shows the actual lab test setup, where (a) shows the test setup connection, (b) and (c) show the inside components of the setup. Additional laboratory experiments will test the communication protocol and sensor data collection accuracy. Figure 8: System functionality test setup block diagram 19

20 (a) (b) (c) Figure 9: Subsea Platform Laboratory Test Setup Failure Modes and Effects Analysis A FMEA has been performed to capture the potential failure modes and risks of the Subsea Platform. The FMEA was divided into two sections: the acoustic communication and the sensing platform. Table 8 shows the FMEA results for the sensing platform, and Table 9 shows results for acoustic communication, respectively. 20

21 Table 8. FMEA Results for Subsea Sensing Platform Risk / Failure Mode Sev Prob Detect RPN Risk Mitigation Plan Not enough sensor sampling data for Perform simulation together with the vibration team to analytics determine the analysis accuracy vs. the data sample size Perform simulation together with the vibration team to Sensors installed to insensitive location determine the analysis accuracy vs. the sensor location Can't reliably detect events of interest by Connect with customers to determine the event of customer interests Perform system integration testing at BTC to test the Sensor not attached to enclosure perfectly (as one rigid body) sensor installation mechanism and collected signal integrity Sensor falls off (inside packaging) Perform system integration testing at BTC to test the sensor installation mechanism and collected signal integrity Sensor fails due to damage Perform system integration testing at BTC to test the sensor installation mechanism and collected signal integrity Subsea processor fails / reboots Processor stress testing Sampling interval too long to capture Connect with customers/industry experts/ocean current instantaneous extreme event profiles to identify the proper event monitoring interval Perform simulation together with the vibration team to Sensors are inaccurate (not enough sensitivity) determine the analysis accuracy vs. the sensor resolution/sensitivity Perform simulation together with the vibration team to Vibration exceeds sensor range determine maximum possible acceleration Table 9. FMEA Results for Acoustic Communication Acoustic Buoyancy module blocks acoustic link Field testing with buoyancy module on riser joints Transducer beam pattern not appropriate Field testing with buoyancy module on riser joints Excessive acoustic noise from working Increase tx power & determine regulatory enviroment requirements (e.g. FCC) for maximum data Acoustic transuder interference by (or to) other systems Engagment with GE O&G and drilling contractors No certification to perform field testing Discuss with customer DNV and/or API to get clarity Corrupted data due to acoustic transmission from interference/noice Increase tx power & determine regulatory requirements (e.g. FCC) for maximum data transmission power Risk mitigation for failure modes with RPN values 6 will be the focus of efforts during the remainder of Phase I and in Phase II of the program. Laboratory tests and results on the subsea sensor module platform will be presented in the final Phase 1 report. Next Steps The next steps in the development of the Subsea Platform are: Rig testing will include attaching the subsea platform to a full scale riser joint to: 1) test the sensor signal integrity under controlled axial tension and bending loads, and 2) evaluate installation mechanism of the subsea platform. 21

22 Enhance the software functionality and capability, and define strategy and architecture for customized app development Build the transfer function for modeling the platform battery life with respect to the various system parameters Working with Woods Hole Oceanographic Institute (WHOI) to leverage their experience in underwater acoustic communication systems and vessel marinization (e.g. 12,000ft depths), define system marinization approach for a customized, pressurized enclosure for field testing Define strategy & plan for system installation on riser deployment operations Subtask Vibration & Fatigue Analysis Methodology for RLMS Initial Design Criteria for Vibration and Lifing Analysis The Riser Lifecycle Monitoring System (RLMS) will include state-of-the-art methodology for predicting fatigue damage based on data from real-time sensor measurements. Fatigue damage rate estimates will be updated frequently in order to adequately capture events that produce above-average fatigue damage. Figure 10 highlights a block diagram for RLMS inputs, key analysis process steps, and example operational alerts and recommendations, all at the individual riser joint level. For example, the system will display high-level plots to the rig operator showing how fatigue damage is actually accumulating during a drilling campaign relative to what is expected based on design specifications and known average ocean current levels in the drilling region. In addition to this enhanced visibility into the drilling operations, the system will make recommendations to the rig operator on how to optimize the riser configuration when fatigue damage estimates in some riser components reach high levels or after extreme events. Figure 10: Workflow for Riser Health Analytics with Example User Interface Outputs Several factors contribute to fatigue damage in deepwater risers, all of which are difficult to quantify with existing data. The primary factor responsible for fatigue damage is VIV vortex-induced vibration from ocean currents. Much uncertainty exists in the factors 22

23 responsible for VIV which makes fatigue damage prediction quite difficult. Deep water currents vary considerably in magnitude, direction and duration. In addition, high toptensions frequently need to be applied to the riser, yet precise quantification of the stresses produced by the cable tension is difficult. Load-sharing between the main pipe and auxiliary lines can cause mismatches in tension that magnify bending stresses at joints. High hoop stresses exist due to mud weight in the riser which can vary over time -- this affects the hydrodynamic response which is predicted by empirical models that have precision issues. Uncertainty also exists in many of the riser system inputs used in design. The ability to estimate fatigue damage rates from real-time sensor measurements, root mean square (rms) acceleration (ft/sec 2 ), can do much to alleviate concerns regarding the aforementioned uncertainties and to provide damage predictions that can be used with confidence when making decisions regarding inspection and maintenance actions. The RLMS system will provide continuous updates on key parameters related to the health of the riser string. These data will assist the rig operator with decision-making processes that affect drilling operations. The top-level parameters that will be continuously updated include: Maximum fatigue damage level in the riser assembly Average and maximum fatigue damage rates during the past day, week and month Planned and recommended time to the next inspection Remaining useful life based on accumulating fatigue predictions vs. design specs Estimated time-history of the axial force on the wellhead The continuous availability of such data will offer the rig operator an enhanced view of the effects of the current drilling operations on riser life metrics and will assist on decisionmaking processes related to performance-based inspection and maintenance. Several of these processes and related scenarios are discussed here, with many more arising in practice. Of primary importance is the identification of critical riser joints those which are aging faster than expected from a fatigue standpoint. These joints will be identified and highlighted in visual displays (Figure 11) and can be flagged for scrutiny during upcoming maintenance cycles. The system will display a plot of the highest level of fatigue damage rate, compared to expected design life, in the riser assembly and will recommend revisions to the next inspection date if the fatigue damage history warrants such action. 23

24 Figure 11: Identification and Display of Critical Riser Components at any Point in a Drilling Campaign The monitoring system will also provide continuous updates on how the fatigue damage history is affecting the next planned inspection interval and the remaining useful life. Structural integrity risks increase if inspections are performed too late, when fatigue damage levels are high. Conversely, the operator might decide to postpone or skip an inspection should the fatigue damage be observed to be accumulating much slower than anticipated. Figure 12 shows a point in time following a series of several drilling campaigns when the accumulated fatigue damage has reached a high enough level to prompt the system to recommend that an inspection be performed right away, even though the original plan did not call for an inspection for two more years. In addition to this alert, the system also identifies that if fatigue damage rates continue at the high recent levels, the remaining useful life will be reduced by six years. The system identifies five specific riser joints that have sustained high damage, and recommends that they either be repaired or replaced. Alternatively, when the riser string is reassembled at the next drilling field, those five joints can be swapped with riser joints that have sustained lower damage levels. In that case, even if ocean current levels remain high, the higher fatigue levels will occur in younger riser joints, thereby enabling the drilling contractor to restore much of the remaining useful life to the rest of the string that would otherwise have been lost. 24

25 Figure 12: Recommendation to Perform a Repair to Five Specific Riser Joints Following High Fatigue Damage Accumulations Conversely, if this riser string is moved to a new field in which the ocean currents are less intense than anticipated, the system may recommend that the next planned inspection interval be postponed or delayed. Figure 13 shows a scenario in which fatigue damage has accumulated more slowly than was anticipated, possibly allowing the planned inspection at 20 years of service to be skipped, with the next planned inspection to be performed at 25 years. In addition, the remaining useful life is shown to have increased considerably (assuming that average ocean current intensities remain the same). 25

26 Figure 13: Recommendation to Postpone an Inspection Based on Low Fatigue Damage Accumulation Rates A high-level view of the architecture of the RLMS system is shown in Figure 14. The use of the system is simple and effective, involving essentially just five steps (Figure 10), some of which are repeated in the continuous monitoring phase. The first step involves the specification of the initial riser configuration via a file that contains the unique ID (RFID) of each of the joints in the riser assembly. Once specified, the system retrieves geometric data (length, weight, inertia, etc.), material properties (Young s modulus, S-N curves for fatigue calculation, etc.) and buoyancy data on the riser components from a master database and builds an analytic model for vibration analysis. At that point, the model can be viewed, and sensor locations displayed (Step 2). The remaining three steps perform analysis using the periodic sensor measurements and provide the rig operator with displays of high-level results related to the instantaneous state of fatigue damage in the riser assembly. Each time the riser configuration changes, such as when joints are repaired or interchanged, or when the assembly is moved to a shallower area and fewer joints are needed, the riser configuration file must be updated (Step 3). The riser components with the highest damage at any point in time can be viewed in Step 4 and the state of the health of the riser string is displayed in Step 5. Detailed information, such as RMS stress and acceleration values, and ocean current velocities can also be displayed for each riser component. 26

27 Figure 14: RLMS Software System Architecture Technical Approach and Results This section presents information on the methodology for estimating stress and fatigue damage from sensor measurements. However, due to intellectual property considerations, some of the details behind the method are not discussed. The RLMS will have accelerometers attached at various locations along the riser to obtain real-time acceleration data. The accelerometer data will be conditioned to remove potential spurious points and to isolate the vortex induced vibration response from other dynamic responses. Data conditioning tools such as anomaly detection that use Gaussian processes to determine outliers and noise will be used to further clean the data prior to its use in fatigue life estimation. The algorithm to obtain the excited modes, amplitudes and fatigue damage estimates from these data is being developed through a semi-analytical approach using the software package Shear7. This state-of-the-art VIV analysis code will predict the modes, mode shapes and fatigue damage in response to vortex-induced vibration caused by ocean currents. The Shear7 recommended values were used for the input parameters in the Shear7 model and based on previous tests and literature (e.g. strouhal number, reduced velocity bandwidth, power cut off ratio and primary zone amplitude limit). In addition, the empirical lift coefficients are taken from Shear7 lift coefficient curves. The measured acceleration data will be used in conjunction with a data-matching algorithm to tune the parameters in the Shear7 model in order to obtain the highest-fidelity fatigue damage rate predictions possible. The number of sensors and their locations along the length of the riser will be determined through numerical studies in order to achieve the best possible 27

28 match between measured and predicted dynamic responses. Publicly available model test VIV data will be used to benchmark the algorithm. The prediction of the real-time fatigue damage using accelerometer data will be performed using two approaches. The first approach being developed assumes that the ocean current velocities are measured from the ocean surface to the mudline; this results in the highest level of confidence in the predictions. In this case, only the dynamic analysis parameters such as the Strouhal number, reduced velocity bandwidth, primary zone amplitude limit and power cut off ratio are needed to estimate the vortex shedding frequency and will be calibrated to predict the fatigue damage. Even if the ocean current velocities are measured only up to a certain depth, curve fitting algorithms can be used to estimate the ocean current velocity along the entire riser length. In the second method, the ocean current velocities are not directly measured. This approach is being included under the presumption that sensor data may not be available during some (presumably short) periods of the drilling campaign due to measurement errors or sensor equipment failure. Along with some tuning of the Shear7 parameters, this algorithm will estimate the ocean current velocities and in turn the stresses and fatigue damage, albeit at a somewhat lower level of fidelity than in the first approach. Failure Modes and Effects Analysis As mentioned previously, a detailed risk assessment was performed to identify risk items related to all tasks associated with the development of the riser life monitoring system. A sub-team of experts in the areas of vibration and life assessment then rated the severity of each failure mode related to lifing. The results of the risk assessment are shown in Table 9. 28

29 Table 9 Results of Initial Risk Assessment for Vibration and Lifing Analysis Risk / Failure Mode Sev Prob Detect RPN Risk Mitigation Plan Vib & Lifing Unavailability of real time ocean current/velocity measurements Methodology will include ability to estimate stress &damage rates when current data are absent. Data screening not accurate Use anomoly detection and data cleansing algorithm Methodology will include a hybrid approach in which Ocean currents only measured to a certain ocean currents are known only for a portion of the riser depth string. Complex riser system components (e.g. Blow out preventer, Lower Marine Riser Package) are not part of the model or the model fidelity System will include integration capability with a global is too low Third-party software vendor(s) fails to deliver working software for the inverse problem Incorrect VIV model inputs (material properties, parameters, etc.) Inability to model surface waves and vessel drift riser working analysis with package industry leader with VIV in package the field of VIV analysis and prediction. Current plans call for testing and delivery of all software in Q Data-matching methodology for estimation of damage rates from sensor data includes tuning of VIV analysis parameters over time. System will include integration capability with a global riser analysis package with VIV package Incorrect riser model / configuration RFID methodology used to track riser configurations Imminent failure from a single event unlikely; system will Rig operator misses / overlooks fatigue-driven display alarm when severe conditions occur. Miss on event calculated by RISERLIFE high wellhead tension could be critical. Next Steps The next step for vibration and fatigue analysis are to develop a reliable fatigue damage prediction model based on sensor measurements. A number of numerical tests based on available field data will be conducted to build a robust vibration and fatigue model that uses measured acceleration data to make fatigue damage estimates. These tests are designed to provide data in order to achieve the following goals: 1. Determine the relationship between the number of motion sensors (accelerometer, angular rate) along the riser vs. model accuracy. The modal data (natural frequencies and modeshapes) was obtained from Shear7. Obtain the minimum number of sensors that can be used to obtain a desired level of accuracy between model responses (calculated via Shear7) and measured responses. 2. Test model accuracy using different ocean current velocity profiles from publicly available data 3. Assess the model prediction capabilities with ocean current velocities up to certain depths. This includes curve fitting/estimation for the remaining part of the velocity profile. 4. Calibrate the Shear7 parameters such as the Strouhal number, lift coefficients etc. to assess their effects on fatigue damage predictions. 29

30 5. Determine the influence of the top tension and mud weight on the mode shapes and in turn on fatigue damage. These tests will guide the calibration of the model for use in obtaining reliable real-time fatigue damage estimates and help in identifying any additional sensor needs, such as the placement of strain gauges at critical locations. Subtask Software Management Subsystem for RLMS Initial Design Criteria The subsea structural monitoring system should provide sensor measurement data for real-time estimation of actual loads (e.g. tension, bending moments) and motions (e.g., displacements, inclinations, angles) 2 in selected locations of the marine drilling riser. It is desired to have relevant data from existing rig system (e.g. mud weights, top tensions, environmental data) integrated with the subsea data. It is desired to have results of analysis of all relevant data should presented to the rig crew in near real-time in an intuitive view, such that the rig crew can optimize the rig and riser operation, compare the status with operating limits, and take necessary action to avoid exceeding the specified operating limits. It is desired to have raw data stored in a redundant database for post retrieval, processing and analysis. In addition, select data can be transmitted to an onshore database server or data center, to allow onshore support personnel to monitor the operation in near real-time with similar views for the on-board crew. Initial detailed specifications include: i. manual route-based data collection instruments ii. iii. iv. online intermittent condition monitoring data on essential assets various interfaces to process control and automation systems for importation/exportation of key parameters and statuses manual data entry of notes, and links to pertinent asset documentation such as manuals, drawings, and maintenance logs v. engineered interfaces to industry accepted Computerized Maintenance Management System systems Technical Approach & Results The initial prototype version of the Riser Lifecycle Monitoring System (RLMS) software will be built using a mature GE engineering software tool, 3DFAS (3D Fracture Analysis System). 3DFAS is a software engineering tool widely used across GE for fracture mechanics. Due to its ease-of-use and streamlined user interface design methodology, it was selected for development of the prototype RLMS Software, RiserLife, for near real time operational visibility and fatigue life assessment of deep water risers. 30

31 A review of the goals and objectives of 3DFAS and its software architecture is presented in this section, along with a discussion of the benefits of using 3DFAS. As background, 3DFAS evolved as an efficient and easy-to-use software framework for fracture mechanics based analysis of cracks in engineering structures. This tool facilitates the process of inserting cracks into either solid geometric models or finite element meshes. The model is then discretized and a stress and fracture analysis is performed to obtain stress intensity values along the crack fronts. This allows the analyst to determine whether or not a crack in a component will propagate under design loading. If so, a crack advancement analysis can be performed to determine the total part life which is the sum of the crack initiation life and the crack propagation life. Development of 3DFAS began in 2003 and continues today. The tool has been used in numerous NPI programs and for determination of the root cause of critical fracture-related field issues at GE Aviation, Power & Water, Oil & Gas, and Consumer & Industrial. During development, the tool has undergone about a dozen formal tollgate reviews under the auspices of GE s Software Tools Center of Excellence. It is built on a solid software foundation of C++ and Microsoft s foundation classes. Two versions of the tool are available: a 32-bit GUI version for the Windows operating system, and a 64-bit Linux version for use in GE s HAL cloud-computing environment. DOEs in which crack size parameters vary can be set up and run in batch-mode with either version. A diagram of the 3DFAS system architecture is shown in Figure 15. Figure 15: 3DFAS System Architecture The software architecture of 3DFAS has been used as the foundation for approximately 10 other visual engineering analysis codes, including oxidation lifing for coated metal airfoils, blade scrap rate prediction for Aviation services, and rotor lifing for steam turbines. As a result of ease and speed in which other tools can be built upon the 3DFAS software foundation, the decision was made to use 3DFAS for the foundation of the prototype of the 31