Case Study: US Petrochemical Facility Sees a 62% Reduction in Loss of Primary Containment Failures Over Seven Years with Mechanical Integrity Program

Learn how we helped a petrochemical facility reduce the number of Loss of Primary Containment (LOPC) failures by implementing a Risk-Based Inspection and Evergreening program.

Challenge

A petrochemical facility was experiencing a high number of LOPC failures from its fixed assets and was looking for a cost-effective way to manage its assets.

Solution

Pinnacle helped the facility to select and implement an IDMS, conduct RBI analysis, evergreen the program, and conduct inspections.

Result

The facility reduced the number of LOPC failures by 62% over seven years and is now set up with plans and procedures for long-term success.

Introduction

A large producer of polyurethane chemicals in North America creates materials for various industries, including the automotive, construction, and aerospace sectors. The facility has specific production objectives focused on efficiently delivering high-quality products to its customers while maintaining availability. To meet these objectives, the facility identified a need to implement a robust Mechanical Integrity (MI) program that would provide a long-term, cost-effective way to manage its assets.

The Challenge

While the facility regularly tracked important asset information such as overall equipment effectiveness, failures, and inspection spend for critical and non-critical equipment, the facility recognized there were improvements that needed to be made in their existing reliability program. For example, asset data was stored in different databases and managed by different teams, making it difficult to develop standardized approaches across the facility. As a result, the facility had a more reactive approach to maintenance and faced multiple challenges, including:

  • Inconsistent and siloed data and processes across all groups
  • Lack of focused asset strategies
  • Difficulty building and implementing evergreening processes

To address these challenges, improve reliability, and create consistency across the site, a site-wide initiative was instituted. The initiative aimed to equip the facility with the tools and resources needed to reduce inspection spend, ensure compliance, and guarantee the safety of its employees and surrounding communities. With this end goal in mind, facility leaders sought a third party to help implement a holistic reliability solution.

Pinnacle’s Solution

Pinnacle was brought in as a strategic to develop and implement a proactive Risk-Based Inspection (RBI) and inspection program for the site’s fixed equipment. Pinnacle created a multi-year, four-phase implementation plan which included Inspection Data Management Software (IDMS) selection and implementation, RBI analysis, evergreening, and RBI revalidations. The goal of these strategies was to help the facility efficiently manage its operating risks.

Phase 1

One of the most critical steps in the plan was to organize the facility’s data. The facility had relied on data stored in multiple systems and managed by different teams, making it difficult to accurately pinpoint the timing and frequency of inspections. As a result, the facility was wasting money and resources on unnecessary, time-based inspections. To help organize this data, the Pinnacle team aided the facility’s leadership in choosing an IDMS that best-suited facility needs. Pinnacle helped configure the software to the site’s specific needs, and once the data was organized, it was uploaded into the system.

Phase 2

Pinnacle placed a team onsite to work collaboratively with the facility’s personnel to aid in the implementation of an RBI program. This program took place over two years and included piping systemization and circuitization, asset datamining, corrosion modeling, and asset strategies for 13 units. Each task was validated by both Pinnacle and facility Subject Matter Experts (SMEs). As a result of these strategies, the site also leveraged Pinnacle to offer inspection support through API and NDE Technicians.

Phase 3

Once the RBI program was in place, the facility took over the program for the next two years to gather data while Pinnacle continued to work on various special emphasis projects for the site, such as consolidating line specs and updating drawings. Pinnacle was then brought back to implement a robust evergreening program to maintain Management of Change (MOC) requests and conduct inspection grading in accordance with API 581 inspection effectiveness tables.

Phase 3

The final phase, RBI revalidations, came approximately five years after evergreening began and will be completed in 2022. The revalidation process is outlined in API RP 580 and says that an RBI program should be reevaluated on a ten-year schedule if there were changes that would affect the validity of the original study. This reevaluation will take the initial analysis and assumptions made in the original assessment and add them to data gathered over those five years. Depending on what data is available, some assumptions need to be made based on SME knowledge and industry standards during an initial RBI assessment. During the revalidation process, new data that has been collected over the previous five years is integrated into the model and helps to verify previous assumptions about corrosion rates are accurate or if they should be adjusted. In some cases, this data can help remove mechanisms that may not actually be applicable.

Additional elements of Pinnacle’s solution included field drafting, an embedded inspection team to support planned and unplanned inspections, and several special emphasis projects.

Results

The site split its assets into two groups, one for what it deemed critical and one for non-critical equipment. These categories were determined by the Environmental, Health, and Safety (EHS) impact that asset or circuit had if it failed. Over the years of implementation, the benefits started to become apparent. Using failure reports to track the impact, between 2013 and 2020, the site saw a 72% reduction in critical failures and a 48% reduction in non-critical failures, with an overall site failure reduction of 62%. When multiplied by the average cost per type of failure (critical vs non-critical), there is upwards of $500MM in value over that seven-year span that could be attributed to the improvements in the facility’s MI program.

Failure Reduction

Reduction in Equipment Failures

With the help of Pinnacle, the site received a set of prioritized, tailored risk mitigation strategies that will equip facility leadership with the data they need to make strategic, cost-effective decisions. Leadership buy-in from the site and corporate was instrumental in the success of the implementation and sustainability of this program.

The program was kicked off almost ten years ago. In that time, facility leadership has made better strategic decisions, reduced inspection spend, and significantly reduced the number of LOPC events. Overall, the new program in place also allows for:

  • Improved safety and asset integrity
  • Optimized inspection plans and spend
  • Compliance with best practices and industry regulations
  • A robust evergreening plan and procedures
  • Improved understanding across the site’s departments on the impact of the work being completed and increased confidence of facility leadership in their data and programs

Conclusion

The success of this facility’s MI program has led to it being the focal point of corporate improvement strategies. In addition to starting the RBI revalidation process for this facility, Phase 4 of this project included the kickoff of a corporate initiative to improve the overall reliability of all the company’s Polyurethane sites. Each facility has now built its own program based on the framework of this US facility.

The next steps for the facility will be to complete the revalidations and continue to evergreen its MI program. As the site collects new data and makes operational and design changes, it is imperative that those changes are implemented into the analysis in a timely manner. Pinnacle is also currently helping implement a non-fixed asset program as outlined in this case study.

To learn more about how Pinnacle can help your facility build its best version of reliability, set up a discovery call.

Case Study: Leading Fertilizer Manufacturer Leverages APM Software Migration to Improve MI Program Performance and Meet Compliance

Learn how we helped a fertilizer manufacturer integrate a new IDMS into its existing business systems to improve the performance of its mechanical integrity (MI) program and meet regulatory compliance.

Challenge

A North American fertilizer manufacturer needed a new IDMS to improve its performance and meet compliance.

Solution

Pinnacle helped the manufacturer evaluate IDMS options and select Predix APM, a cloud-based version of GE Digital’s APM software. Pinnacle assisted the manufacturer in not only selecting the software and effectively migrating the data but also in upgrading data quality and risk results.

Result

The manufacturer was able integrate the new IDMS into its existing business systems and standardize its MI work processes across its sites, improving the visibility of performance data across all levels of the organization, mitigating MI risk and ensuring compliance across its five facilities.

Introduction

A leading fertilizer manufacturer with multiple sites across the US and Canada wanted to improve the quality of its MI program to meet regulatory compliance. The manufacturer’s leadership wanted a top-tier MI program that would provide the information they needed to make cohesive decisions across its sites. After assessing the current state of its MI program, the manufacturer’s leadership determined that its current IDMS no longer aligned with company objectives. In order to have a top-tier MI program, the sites would need to transition to an IDMS that would support current and future facility needs.

The Challenge

The manufacturer’s existing IDMS created numerous challenges for leadership across multiple sites. The primary challenge for the manufacturer was a lack of consistent, organized, and high-quality data across its sites. For example, some sites stored their equipment lists in spreadsheets while others used the corporate IDMS. Secondly, the manufacturer’s IDMS only stored data for certain types of equipment, limiting IDMS usability across different asset specialties. The existing IDMS also restricted the ability to access and export data to the IDMS’ support team, which often led to inconsistent reporting across sites.

Additionally, the manufacturer’s IDMS did not connect to its Enterprise Asset Management (EAM) system, which made it difficult for facility leadership to be confident that all of its assets were in compliance with industry code. Because the availability, location, and quality of data also varied by site, corporate leadership struggled to drive consistent asset management strategies across all sites. The manufacturer needed a more comprehensive data management system that would enable users to improve the quality of data and allow the manufacturer to apply improvements across all its sites.

Pinnacle’s Solution

While there was buy-in from the manufacturer’s management team to implement a new IDMS, corporate and site leadership was concerned about the logistics of transitioning to the new system. Pinnacle was brought in to evaluate viable application options and implement the selected solution for five of its sites. Pinnacle was selected because of its extensive expertise in designing, evaluating, and implementing a variety of Asset Performance Management (APM) platforms across multiple industries. After a detailed analysis of the manufacturer’s system requirements and a thorough review of the application options, Predix APM was selected because of its ability to meet the following functional requirements:

  1. Integrate management of the master equipment list, inspection scheduling, inspection results, thickness measurements, and Risk-Based Inspection (RBI) calculations into a single platform.
  2. Integrate the full system with the manufacturer’s EAM system, including equipment, functional locations, inspection scheduling, work history, and recommendations.
  3. Simplify management of day-to-day MI work processes and automate where appropriate.
  4. Increased visibility of MI data to make data-driven decisions.
  5. Track inspection recommendations, temporary repairs, and deferrals to meet compliance.
  6. Provide a solution that the manufacturer can modify as their business needs evolve.

After selecting Predix APM, Pinnacle worked with the manufacturer to address the program’s data silos, centralize its asset registry in the EAM system, and consolidate all MI data in Predix APM. The focus of the overall project included the standardization of the MI program, the definition of new work processes, data cleanup and validation, optimization of fixed equipment strategies utilizing RBI, and application training and implementation.

As a part of data organization and validation, the Pinnacle team cleaned, organized, and uploaded all fixed equipment data from the five sites into Predix APM. This data included the facilities’ most recent RBI criticality calculations, Thickness Monitoring Location (TML) data, critical thickness data, historical inspection data, and inspection work plans. The scope of work for the five sites included over 14,000 assets and 150,000 TMLs.

After all data was migrated to Predix APM, the Pinnacle team ran new risk analyses for their fixed equipment, including pressure vessels, piping, and tanks. The results of the new risk analyses were then compared to the results from the manufacturer’s original IDMS, and the team identified numerous scenarios where the risk differed. For these scenarios, the Pinnacle team dove into the various factors that contributed to the differing results and were able to identify the drivers behind these risk differences. In several cases, these differences were due to inconsistent data management practices and approaches across the five sites. Because Pinnacle had access to all five sites’ data, as opposed to siloed information, these variations were recognized, and appropriate actions were taken at a corporate level.

Results

After implementing Predix APM, corporate and site leadership recognized a multitude of benefits:

Connection of Predix APM to EAM System

The integration of Predix APM with the manufacturer’s EAM system provides facility leadership with more access, visibility, and control of site-specific data within a centralized location. Additionally, the integration of the manufacturer’s business systems gives the manufacturer the capability to automate work scheduling and generate service requests in the EAM system directly from Predix APM, which assists in maintaining compliance and developing reliability work plans.

Improved Quality of Data

During the data migration, inspection tasks that were redundant with the EAM system’s preventive maintenance (PM) tasks were identified and removed. The team identified the gaps between how the sites were populating critical data fields and made recommendations to corporate on how to populate these fields moving forward. Furthermore, users gained an immediate boost of confidence in their program by consolidating disparate, siloed data sources into one source of truth.

Data-Driven Program Management

Corporate and individual site leadership now has increased visibility into the processes, performance, and financials of multiple sites through the use of key, role-based dashboards that were tailored to the individual sites and corporate level. Additionally, since data is no longer restricted to the systems’ administrators, users at one site can easily create, export, and share reports with other sites to highlight any lessons learned. The manufacturer’s corporate leadership experienced a step-change in the level of access they had to the sites and was able to access critical data for all five sites in a single location.

Improved Program Capabilities

During the data migration, the manufacturer was able to eliminate wasted inspection spending through the consolidation and cleanup of all inspection tasks and the refinement of their risk-based inspection program. The manufacturer also established work processes and dashboards for managing Class 4 piping and relief valves. Predix APM’s ability to integrate well with data loggers was utilized for gathering Ultrasonic Testing (UT) data, which drastically reduced clerical work and the risk of human error that can occur when recording thickness measurements.

Customized Training

As a part of the overall project, Pinnacle developed customized, role-based training to ensure employees from all sites understood how to use Predix APM for all of their work processes.

Conclusion

After having provided the solution above, the Pinnacle team continues to support the manufacturer by providing reports and continuous improvement across RBI and MI initiatives. This includes adding additional asset types, processing management of change and capital projects, and identifying other opportunities to reduce mechanical integrity risk and optimizing spend while ensuring compliance.

The Evolution of Data Management in Mechanical Integrity: Spring 2022 “Meeting of the Minds”

*As seen in Inspectioneering Journal’s July/August 2022 issue.

Earlier this year, Inspectioneering and Pinnacle co-hosted their 9th “Meeting of the Minds” (MOTM) roundtable discussion in Chicago, Illinois. This bi-annual meeting brings together a select group of leading mechanical integrity (MI) experts to discuss pertinent topics related to fixed equipment reliability and share their personal experiences and opinions. As with previous meetings, participants come from various sectors of the industry, including refining, petrochemicals, offshore production, and chemical processing.

Previous MOTM recap articles have summarized key takeaways from our discussions covering topics like emerging technologies, corrosion under insulation (CUI) programs, integrity operating windows (IOWs), corrosion control documents (CCDs), risk-based inspection (RBI), the effects of the Covid-19 pandemic on mechanical integrity programs, piping RBI, and most recently, MI project hit lists. The theme of this meeting was data; in particular, data collection, data organization, and data analysis.

Data Collection and Organization

Drones

We opened the discussion on data collection by asking the participants to share their experience with robots and drones and whether they thought this technology will be used to automate data intake instead of humans in the next decade.

It was clear that all of the participants have used robotics and/or drones to help monitor the condition of their assets; some more than others. One individual from the refining industry stated that he has “seen a tremendous amount of improvement in drone technology over the last several years.” He shared that they were now using drones to take 3D scans of their assets, build models, take UT readings with magnetic sensors, and fly them inside difficult-to-access spaces like tanks and columns. While he was adamant that the technology is assisting his inspection program, he remains concerned about the quality of the data/readings. “I’m just not sure if it’s an adequate replacement for a seasoned inspector actually getting out there and looking at a piece of equipment with their own eyes,” he stated.

Another participant from the refining industry stated that they have a fairly robust drone program across their facilities and that their IT group has been instrumental in building the infrastructure to store the immense amounts of information coming in. “We’re building out a process right now to determine exactly how that data goes from that device to a server, wherever it may be; as well as the ability to tag it, timestamp it, and make sure we can go back and know exactly what we were looking at and where it’s located,” he added.

It’s no secret that the refining industry seems to be behind other industries when it comes to integrating new technologies like drones into business operations. A participant from the upstream O&G industry commented that they had been using drone technology to inspect their offshore assets for many years. He went on to share that they are actually using satellites now to effectively monitor methane emissions from onshore assets in the U.S. They are testing this technology on offshore assets as well, but it’s a little trickier getting accurate readings over water. So, they are using their drones to verify the satellite emission readings from their offshore assets as well.

When asked how their inspectors felt about incorporating new technologies like drones and robotics into their existing programs, one participant estimated that approximately 50% of his inspectors are resistant, stating that they want to put their hands on the equipment and “taste the metal.” The other 50% is probably split between “I don’t really care” and “heck yeah, let’s do it.” Everyone seems to understand that this transition is coming though. The role of the inspector has drastically changed over the last 20 years, and it will undoubtedly continue to evolve as technology keeps advancing and we bring in more and more data about the condition of our assets.

Permanently Mounted Sensors

As hardware becomes more economical and industrial facilities recognize the value of continuous monitoring to better understand the true condition of their equipment, interest, and installation of permanently mounted sensors has significantly increased. One participant shared that they’ve installed thousands of single sensor probes across all their sites with plans to install more. “The future is continuous monitoring, and I think we’re just now scratching the surface of the benefits it can provide. We’re seeing it already though; some of the data that’s come back has alerted us to issues with our equipment that we realistically wouldn’t have known for 5-10 years based on traditional modeling,” he said. However, he did note that there is just so much data coming in on a daily basis, you really need to have management systems in place to determine who reviews it, when they review it, and how they review it. They’re currently building modeling capabilities to alert key stakeholders when there is an issue that someone needs to take a look at.

Another individual said his company has been installing sensors across their downstream facilities for several years, but they do not monitor them daily. “We use our estimated corrosion rates and then go pull the data to make sure we’re still where we want to be,” he said.

One participant from the refining industry emphasized the importance of understanding the scope of your sensors. He went on to share an experience where they had a mix point in a sulfuric alky unit that failed, so they put a sensor at that precise location and shortly thereafter experienced another failure 1.5” away from the sensor. “We gave ourselves a false sense of security because we thought monitoring the location of the previous failure was sufficient,” he said. “We’re currently trying to put systems in place right now to better analyze the data coming in,” he added.

Another participant stated that they use a lot of permanently mounted sensors and are getting a ton of data from them, but currently, none of them integrate with his IDMS, which, as he put it, “is what we kind of hang our hats on in terms of our CMLs and corrosion rates.” So it’s become yet another system that they have to manage and interrogate, and it’s getting to the point of “Where do we start? When an inspector or corrosion engineer shows up in the morning, what is he or she supposed to look at? None of these sensor systems are notifying us of any red flags, so we all have to go on this fishing expedition every morning to query our IDMS, query the sensor data, query the IOW data, etc.” This is presenting a significant challenge for them. “We bring all of this technology together and it’s really not integrated under one roof, so it just becomes more difficult on the human to actively find and interpret all of that information,” he said.

Others at the table agreed that all of these new data acquisition tools are fantastic, but it is crucial to ask the right questions upfront, before you start implementing any new technologies. What are you going to do with the incoming data? Who’s going to monitor it? How does this change your work processes? How is the data going to be analyzed and leveraged?

Data Challenges

When asked what some of the biggest challenges were the participants faced when it came to managing their equipment data, there were three common issues raised. The first major challenge is data silos within facilities and organizations. At any given facility, there are many different systems simultaneously gathering good data, yet they aren’t effectively communicating with each other. Unfortunately, this leads to a lot of data being rendered useless when it comes to making significant integrity and reliability gains.

One participant from the upstream industry commented that they are working to address this issue by combining their data silos into a centralized information repository (i.e., a data lake), and getting input from each of the various stakeholder groups (inspection, maintenance, operations, etc.). They ask, “how does this data interact?” and use predictive analysis based on experience and certain assumptions to train their model to provide outputs that are useful to their inspectors, engineers, and maintenance personnel.

The second challenge raised is the fact that currently in our industry there is no standardization of data outputs, data quality requirements, or data interactivity. The participants agreed that there is a strong need for governance on how the diverse types of data being gathered are incorporated into mechanical integrity programs. “The industry needs to come together and set up what that governance looks like. We need to review examples, outputs, successes/wins, failures/losses, and then put that governance in place,” said one participant.

The last challenge raised is the “shiny new thing” trap. “There are a lot of cool new things on the market that could have a place in our toolbox, but we can’t forget there are still a lot of fundamental things we should be constantly improving and solidifying,” said one participant. Owner-operators must make sure their teams remain disciplined and ensure that their programs are built on a strong foundation. For example, get your work processes optimized and nailed down before bringing in a shiny new tool that may or may not fit within your programs.

Closing

The goal of integrity programs is to be able to look at your risk profile and determine where your biggest risks are and how to best mitigate them. When you can effectively do that, you get more production uptime, more efficient operations, and more reliable predictions. Better data acquisition, organization, and analysis is an integral part of building a world-class mechanical integrity program. We hope that sharing some of the insights from our “Meeting of the Minds” discussion helps you in your journey as a mechanical integrity professional.

Inspectioneering and Pinnacle would like to thank all of the participants for sharing their insight and experiences. We sincerely appreciate your participation in these discussions and your dedication to educating and advancing the Inspectioneering community.

From Increasing Shareholder Pressure to Global Wars: The Ongoing Challenges of Being a Refiner

Whether facing the increasing pressure to transition to environmentally friendly operations or navigating the fluctuating supply of crude oil, the decisions of refinery management teams carry greater weight than ever. However, despite the ongoing challenges that the industry is facing, refiners are in a unique position to capitalize on the current market.

Interestingly, many refiners are not capitalizing on this opportunity. Regardless of the major tailwinds that typically result in large profits, refineries that do not operate reliably are not as profitable as they could be.

How much of an impact does reliability have on the profitability of refineries? To investigate, we analyzed the 2017 – 2022 financial and operational data of 19 downstream companies in our second Economics of Reliability Report for the refining industry. Additionally, we sat down with Jace Thurman, Market & Data Analyst at Pinnacle, and Jennifer Lawrence, Lead at Pinnacle, to discuss the report and get their thoughts on how refiners can pivot their operations to combat fluctuating supply and demand.

How is the Russia/Ukraine war impacting the refining industry, specifically the production of crude and natural gas? Are there any specific factors that this war is impacting besides feedstock? How can refiners pivot their operations to combat fluctuating supply and demand?

JL: With limited feedstock available to the refining industry due to the Russia/Ukraine conflict, the US has been offering millions of barrels of oil from its Strategic Petroleum Reserve. However, the reserves’ releases are scheduled to stop at the end of October, at which time the reserve will shrink to a 40-year low. Obviously, the world can’t keep relying on the US strategic reserve to keep oil prices in check and meet demand.  We have a finite amount of available crude oil, and the depletion of the reserve poses a risk to our national security. It’s also worth noting that while any barrel of crude is better than no barrel of crude, not all crude is the same. What has been sold off from the reserve is mostly what is known as medium-sour crude, a fan favorite for domestic refiners. Russia was a major contributor of this medium-sour crude, and this type of crude could run out in the next four to five months if we keep selling it at the current rate beyond the October threshold. Without the reserve or Russia to supply this type of crude, refiners could be left with heavier, albeit cheaper, crude.  With a steady diet of heavier, cheaper crudes, refiners will have to pivot by potentially investing in upgrading their processes to produce the same higher-value products they can get from using the lighter crudes. The costs and payback period for these upgrades can potentially be offset by improving the overall reliability of the assets by increasing availability and throughput. While many refiners have perfected reliability in their traditional forms to maximize asset performance and life cycle costs, a new evolution in reliability is warranted – one we’re calling data-driven reliability. This approach to reliability offers facilities a framework that can help them achieve additional performance improvements and pivot to meet demand utilizing a less than perfect feedstock.

JT: The price of petroleum products has, as drivers are well aware of every time they fill up their gas tanks, steadily increased since November 2020. Increasing consumer demand and overall economic inflation were the root causes of higher prices; when Russia invaded Ukraine in February of 2022, the global trade flow for crude oil was disrupted. Russia is a significant exporter of crude oil and natural gas, contributing 8.3% of crude exports in 2021 and 8.2% of liquified natural gas exports in 2020 (Statista, BP World Factbook). In response to the military action, foreign governments and oil corporations responded by imposing sanctions on Russia and ceasing operations in the state. Some countries banned the imports of Russian oil products. This impact on the global oil trade added tailwinds to already increasing crude and natural gas prices, and refineries have been forced to pay higher prices for crude feedstock. Interestingly, even though refiners are forking over more cash for their feedstock, higher petroleum derivatives pricing and demand have led to wider margins and larger profits. Outside of the fact that refineries have been paying higher prices for crude, procuring barrels of oil has been more of a challenge. Import restrictions in the US and other countries have forced refineries to rethink their crude purchasing strategy. For example, refineries on the west coast of the US have historically imported Russian crude; they are now shifting their purchases to Canadian and Latin American imports. The opposite problem is actually occurring in Russia; refineries in Russia have ramped down production because of a supply gut of domestic crude oil.

The current energy market conditions are incentivizing refineries to maximize utilization and production. The past three years, however, have been turbulent for oil supply and demand; having reliable operations can help refineries combat lower and higher demand. Being able to reliably and efficiently turn production up and down based on market conditions will allow refineries to minimize expenses and capture wide margins.

As corporations face increasing pressure – both from their stakeholders and the global economy – to transition to environmentally friendly operations, how does reliability play a role in this transition?

JL: It will be a long while (if ever) before we get completely away from fossil fuels. With that being said, there is no runway ahead for continued increases in fossil fuel demand. The demand for fossil fuels has risen continually since the first refineries were built more than one hundred years ago, and that demand could peak soon if it has not already.  Because of this, some refiners are retrofitting traditional refining assets to produce renewable diesel and other biofuels.  Reliability will certainly play a role in these asset conversions to help align assets to new performance objectives.  Reliability will also pave the way for increased throughput and capacity to meet existing demand in a limited refining asset base as data-driven reliability methodologies are adopted to enhance traditional methods.

JT: Recent focus on refinery throughput and capacity has put a spotlight on oil and gas management teams. COVID-19-related capital discipline and political and stakeholder pressure to transition to clean energy and renewable fuels have led corporations to limit their investment in new refinery expansions and upgrades. Investors are keenly aware that the world is pushing toward environmental initiatives. This awareness has influenced corporate strategy and even led management teams to provide financial incentives for executives who successfully make ESG-related changes. The economic cost of intense investments in refineries is not as attractive as other opportunities due to the long-term return on investment and uncertain market conditions. Reliability is an effective tool that refineries can use to ensure that operations run smoothly and effectively. Since refineries are not expanding or investing large amounts of capital into assets that will increase throughput, management teams should focus on ensuring that current assets have an efficient and effective maintenance program to ensure reliable operations.

The graph below shows WTI crude price and downstream capital expenditures for the 19 companies we studied in our report on a quarterly basis. Crude prices in the first quarter of 2022 have continued the upward trend experienced since the low in the second quarter of 2020. Capital expenditures in the first quarter of 2022 did increase compared to the prior year but are still below the levels reported for the first quarter of 2019 and 2020. Because of the complexity of refining operations, management teams would benefit from employing a data-driven approach to identify the most effective and efficient use of future capital.

In April, LyondellBasell announced that it would cease operations at its Houston Refinery, one of the largest refineries in the US, by the end of 2023. Plans to convert the refinery to a plastics recycling facility are reportedly being discussed. Any thoughts/ideas as to why LyondellBasell made this decision?

JL: I am not surprised that this 100-year-old refinery, requiring a 1-billion-dollar investment to keep operating beyond 2023, was put on the market. Future demand will flatten to some extent as cleaner energy replaces everyday uses such as home heating/power and passenger transport. Seeing the returns for a $1B investment is probably just too risky for Lyondell or any other owner/operator who intends to keep refining. Lyondell has officially taken the refinery off the market and recently announced consideration of a very large investment in its place. They are making good progress on their molecular recycling technology, a version of plastics recycling, and this could be the location that will host the process. The redevelopment of this facility makes sense. This approach is more in line with Lyondell’s carbon emissions goals and also helps the industry move toward a circular plastics economy by helping Lyondell take a step away from producing plastics from “virgin” resources. Additionally, the location is prime property. This facility sits more inland and at a higher elevation than other coastline plants, making it less vulnerable to the impacts of notorious Texas hurricanes.

JT: The Houston refinery has struggled to perform reliably and safely for a while, and this has impacted its profitability. The refinery reported operating losses for the past six years (Houston Chronicle). This year’s market conditions have made the facility profitable, but LyondellBasell is still pursuing plans to cease operations. One potential reason is that the refinery was built to be a supplier of their petrochemical operations, which is the main source of revenue for the company and its strategic focus. The fact that the refinery is seemingly not a priority has led to underinvestment; the plant would require significant investment to bring it to a state-of-the-art facility. Executives at the company have said they are considering turning the refinery into a plastic recycling site to facilitate their chemical portfolio.

For further insight into the impact of reliability on the refining industry, download our Economics of Reliability Report or watch the below clip from our Economics of Reliability Roundtable.

SMRP’s 30th Annual Conference

We will be at SMRP’s 30th Annual Conference!

Join Pinnacle at SMRP’s 30th Annual Conference in Raleigh, North Carolina! Visit us at our booth or at one of the below presentations. Check back regularly for updates on the booth location and presentation date/times. 

Save the Date

We can’t wait to see you there.
  • Booth #211

  • Monday, October 17 – Thursday, October 20

  • Raleigh Convention Center in Raleigh, North Carolina

For more information, please visit SMRP’s 30th Annual Conference event page. 

Presentation Topics

Click on the topics for more information

Tuesday, October 18 at 9:45 AM

How to Eliminate Data Silos to Drive Better Reliability Decisions at Your Facility

Sean Rosier

Many industrial facilities have design, operations, process, asset condition, and risk model data stored in variety of different repositories, creating data silos. Regardless of whether the data is a hardcopy, stored in spreadsheets, or software, the solution is not simply integrating everything into one software. The key to building a strong reliability program is to correctly bring your data together and properly contextualize it by feeding it into the right models. In this presentation, presenters will discuss how facilities can approach solving common data challenges to build a strong reliability program. 

Wednesday, October 19 at 11:00

Establishing Reliability as a Part of Your Capital Projects

Sean Rosier

Today’s projects have become more complex and require an ever-increasing integration into multiple areas of customer operating organizations due to the large volumes of engineering and operational data required to effectively operate and maintain a facility over its expected design life. Additionally, increasing government regulation and financial performance have required owners to have all operating systems and information in place prior to start up or the awarding of an operating license, making operational readiness a critical component of achieving facility goals in the design phase. In this presentation, presenters will discuss a case study example of how a wastewater treatment facility undergoing an estimated $1.7B capital expansion was able to recognize an estimated $100MM in cost savings over the life of the facility by applying Reliability Centered Design (RCD) and Reliability Centered Maintenance (RCM) principles from front-end engineering design all the way through commissioning. Attendees will walk away with a better understanding of how they can leverage operational readiness to improve design, optimize capital and operational expenditures, and streamline operations and maintenance at their facilities. 

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Leveraging Data Science and Machine Learning to Improve Your Reliability and Mechanical Integrity Programs

Pinnacle & Inspectioneering Webinar: Leveraging Data Science and Machine Learning to Improve Your Reliability and Mechanical Integrity Programs

Today’s industrial facilities have access to immense quantities of data. If properly leveraged, this data can enable the facility to improve safety performance, optimize maintenance and inspection tasks, and decrease overall spend. While humans are often unable to derive the full benefits of the available data, machine learning and artificial intelligence (AI) can strengthen our natural limitations, resulting in faster data analysis and better insights. Machine learning models can quickly sort through, organize, and clean massive amounts of input data such as process, operation, and design information, enabling facility leaders to make better-informed operational decisions

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Can Reliability Help Midstream Operators Overcome the Global Energy Crisis?

As the global supply and cost of energy continue to fluctuate, and a potential recession looms in the near future, many are looking to the performance of the oil and gas industry to get some sense of how the future economy will perform. Global challenges such as Russia’s ongoing threats to shut down critical natural gas pipelines connected to Europe have highlighted the global dependency on the midstream segment of the oil and gas industry. Additionally, in May 2022, the U.S. Department of Transportation’s Pipeline and Hazardous Materials Safety Administration (PHMSA) released a final rule which requires pipeline operators to report safety information for all gas gathering lines. This final rule further increased the industry’s focus on pipeline safety.

As midstream operators face increased pressure to transport and store available commodities, the reliability of their assets has become even more critical to the success of the industry and global economy. With this heighted focus on the midstream industry, we released our first Economics of Reliability Report-Midstream Industry. In this report, we analyze the operational and financial data of publicly traded midstream operators headquartered in the US and Canada.

We sat down with Jace Thurman, Market & Data Analyst at Pinnacle, and Austin Laskey, Partner at Pinnacle, to further explore the report and discuss how reliability impacts the midstream industry.

What impact have you seen reliability have on midstream operators? When reliability is or isn’t being prioritized, what does an operator in the midstream industry experience?

AL: Having strong reliability foundations in place from start-up is critical to maintaining sustainable, efficient operations. We’re currently working with a midstream service provider as they prepare to get one of their greenfield facilities up and running. This company is now investing in many new facilities and wants to ensure its assets are operating as efficiently and effectively as possible from start-up. Additionally, this company is currently spending a large amount of its reliability budget on sustaining capital investments. While we’ve seen this type of heavy investment into reliability initiatives pay off for our customers with greenfield facilities, facilities need to be careful that they are not wasting money on inefficient reliability programs. Facilities looking to have more efficient reliability programs should identify the highest value tasks and eliminate routine processes that only happen because the programs were historically set up that way.

How does the performance of the midstream operators we studied in the report compare to one another?

JT: In our Economics of Reliability report for US and Canadian Midstream Oil & Gas, the scatter plot shows two things, with all data averaged from a 3-year period from 2019 to 2021. First, the y-axis shows the fraction of reliability spend that is capitalized. A portion of companies breaks out their capital expenditures between “growth” and “sustaining” capital. Growth capital expenditures are those that are expected to increase production or revenue. Sustaining capital expenditures are those that maintain current levels of production or revenue. We define sustaining capital expenditures as one type of “reliability spend,” with the second type of reliability spend being expensed. The further up you go on the y-axis, the higher the fraction of reliability spend that is capitalized rather than expensed. This is intended to show the financial reporting methodology of the various companies. Second, the x-axis shows the total reliability spend relative to service revenue. Many midstream companies derive a significant portion of their annual revenue from the sale of hydrocarbons; to focus on revenue that is generated from productive assets, we stripped out any non-service revenue. The further to the right you go on the x-axis, the higher the percentage of service revenue that a company spends on reliability measures, such as improving asset integrity or replacing aging pipelines.

AL: In our report, we highlighted 17 large, publicly-traded US and Canada-based midstream operators. On average, these companies spend 19% of service revenue on reliability initiatives. While most of the companies fall within a small range on either side of this average, a few companies significantly diverge from the average. ONEOK, Plains All American, and DCP Midstream spend between 45-51% of service revenue on reliability programs; this is significantly higher than any other company in our report, with the 4th highest spender averaging ~27% of service revenue on reliability. These three companies most likely have some level of waste in their reliability initiatives and would benefit from examining their spending habits and identifying and eliminating this waste. Other companies, such as MPLX and Equitrans, have lower than average spend. This suggests that these companies have underinvested in their equipment, and this could have significant consequences in the near future, especially if upstream operators begin increasing production and exploration of crude.

What are some practical takeaways from the report? How can midstream operators use this report?

JT: There are a few key takeaways from this report. First, the midstream industry is not investing in its productive assets at the rate expected, given the current price of crude oil. As crude prices increase, upstream operators typically increase the level of oil production and extraction. This incentivizes midstream operators to invest in their equipment to ensure reliable operations and increase the throughput ability of their asset base. Capital expenditures have remained significantly below 2019 levels, even though crude prices are much higher. Second, midstream industry margins are being compressed; even though revenues have increased significantly, inflation and labor/equipment shortages have led expenses to increase more rapidly than revenues. This margin compression should lead midstream operators to focus intensely on improving operations and reliability. Lastly, some companies in our report should increase their reliability spend, while others likely have a significant amount of wasted reliability spend. Midstream companies should examine their reliability initiatives through a microscope to identify any wasted financial resources or to determine whether they are spending enough on reliability measures. A data-driven reliability approach can help to ensure that midstream resources are being utilized at an efficient and effective rate.

Q1 reports were recently published – have you seen any notable trends? Has the Q1 performance of these midstream operators differed from 2021 performance?

JT: The first quarter of 2022 continued the recent trend in both capital expenditures and operating margin for the midstream industry. The first graph below shows midstream capital expenditures and average WTI crude price on a quarterly basis. One of the key takeaways from the report is the deviation between normally-correlated midstream capital expenditures and crude price. At the current crude price, one would expect midstream operators to grow their asset base to facilitate increasing supplies of crude from upstream operators. However, production and extraction of crude oil have not been increasing; therefore, midstream operators have not been investing in their asset base as they typically have in the past. This could have long-term effects on the reliability of assets.

AL: The second graph shows revenue, operating profit, and operating margin from the 20 midstream operators. Following the peak operating margin in Q1 of 2021, margins have been compressing, mainly due to increasing inflation and higher labor/equipment costs. Even with increasing revenue, midstream companies are finding their margins being squeezed and this trend has continued into the first quarter of 2022.

Curious how your company compares to the top performers in the industry? Download our Economics of Reliability Report to find out.

Case Study: Supermajor Uses QRO to Predict 94.22% Availability and Associated HSE Risk, Using Model to Drive Benefit-to-Cost Design and Maintenance Optimization

Learn how we helped a large energy producer drive a more proactive maintenance approach and quantify future risk and costs by simulating thinning and vibration scenarios through a QRO pilot.

Challenge

A 1.5 MMbd gas-oil separation and stabilization facility wanted a more quantitative reliability model for its stabilization and stripping section to forecast availability and optimize its maintenance costs.

Solution

In three months, Pinnacle piloted Quantitative Reliability Optimization (QRO) to model failure degradation on 56 of the facility’s fixed and non-fixed assets. LVC models were used to predict failure and simulate process condition changes for thinning and vibration scenarios.

Result

The model calculated a forecasted baseline availability of 94.22% for the 56 assets. The facility is able to drive a more proactive approach to maintenance by dynamically monitoring the impact of real-time facility data to understand its impact on availability, risk, and cost.

Introduction

A global super-major with an integrated portfolio of upstream and downstream assets wanted to better quantify its decision-making processes to maximize reliability across its fixed and non-fixed assets at one of its gas-oil separation facilities. The facility, which went into service about ten years ago, was an early adopter of technology and looked to remain at the forefront of the industry in reliability and maintenance digital transformation.

The Challenge

While the facility had implemented a risk-based inspection (RBI) program, the facility’s reliability and integrity programs operated in data silos. This siloed approach made it difficult to quantify maintenance priorities and left the leadership team with a qualitative approach to managing integrated downtime events and annual maintenance plans. This static, siloed program, coupled with the facility’s varying feed composition and rates, caused the maintenance teams to be in a constant reactive state and spend a significant amount of its budget on unplanned costs.

While management trusted their data, they were unable to quantify the future failure dates of the facility’s assets or predict how future equipment corrosion and damage across fixed equipment, rotating machinery, and instrumentation would affect the availability of the facility. Facility leadership recognized that to be at the forefront of the industry, they would need to adopt a more proactive and quantitative approach to managing assets and needed a solution that would provide three primary elements:

  • Scenario Comparisons:

    While the risk of failure was relatively low for the facility’s assets, leadership wanted the ability to predict failure dates and visualize the impact of future corrosion and machinery issues on the facility’s overall risk.

  • Risk Assessment:

    Facility leadership wanted to have a more comprehensive risk assessment of its assets and visualize the impact of its data over time.

  • Availability Forecast:

    Facility leadership could not predict its assets’ future availability.

Pinnacle’s Solution

The facility decided to pilot Quantitative Reliability Optimization (QRO) for its capability to visualize the impact of data over time. QRO is an evolution in reliability modeling that combines the best traditional reliability methods, data science, and subject matter expertise into a hybrid model. The QRO approach provided a framework for this facility to achieve its goal of bringing the best of digital transformation to its reliability and maintenance work processes, satisfying the three solution elements above.

The QRO pilot included a select group of 56 assets within an oil train unit. This group of selected assets was critical to the success of crude oil production and included compressors, pressure vessels, heat exchangers, and pumps. The QRO pilot was completed over three months and had the following scope of work:

  • Data Collection:

    The Pinnacle team extracted data from the facility’s Process Flow Diagrams (PFDs), Piping and Instrumentation Diagrams (P&IDs), Corrosion Control Documents (CCDs), Corrosion Loop Drawings, SAP asset list, and Process Description Handbook. Additional data exports included an RBI program export, work order history export, and vibration monitoring. Because the facility has only been in service for about ten years, little to no corrosion issues were found for the selected group of assets. However, facility leadership still wanted to visualize the impact of future corrosion issues on facility performance despite this insight to mitigate risk proactively.

  • Data Organization and Analysis:

    The data collected during the first step of the process was then loaded into Newton™, a software that facilitates the QRO methodology. This data included the asset register and hierarchy, asset attribute data (material of construction and operating conditions), work order history, inspection and monitoring data (vibration and thickness readings), Probability of Failure (PoF) data (functions, failure modes, and failure mechanisms), and Consequence of Failure (CoF) data (representative fluids, volume, and production impact). During this step, Pinnacle conducted a work order history review to categorize each event into predictive, corrective, or preventive maintenance activities. This step was critical for identifying and understanding bad actors and their associated failure modes and frequencies.

  • System Model and Asset Risk Analysis (ARA):

    All assets were linked within the Newton™ system model. The system model is used for availability forecast calculations and shows how data from each asset impacts overall facility performance. After all available data was loaded into Newton™, an Asset Risk Analysis (ARA) was created. An ARA analyzes an asset’s function and specific performance requirements and creates causal links between the asset’s failure modes and potential failure mechanisms to calculate risk. This calculation also uses data science models to create Lifetime Variability Curves (LVCs) for each vibration and thickness monitoring point, which are used to accurately predict component failure dates. An LVC is a dynamic model that predicts the probability of failure (PoF) over time by applying data science principles, subject matter expertise, and historical plant data. These curves show how the likelihood of failure for each component changed over time and was used for each vibration and thickness monitoring point to predict component failure dates more accurately.

  • Calculated Availability:

    The Pinnacle team calculated the availability forecast for the oil train by leveraging the asset interdependencies from the system model with the dynamic LVC and PoF curves.

  • “What If” Scenario Comparison:

    The facility was able to run various “What If” scenarios for the oil train through the Scenario Comparison module in Newton™ to simulate the impact various failure modes have on an asset’s failure date. During this pilot, the facility modeled a severe thinning scenario on a dehydrator and an excessive vibration scenario on a pump.

  • Final Results:

    At the conclusion of the pilot, the facility received an availability forecast, risk results, and scenario comparisons, described in more detail below.

With QRO, the facility was able to model two “What If” scenarios based on current data and visualize the impact that specific measurements have on the long-term risk of the asset. Two of these “What If” scenarios have been detailed below, including a severe thinning scenario for a dehydrator and an excessive vibration scenario for a pump. With both these examples, management was able to quantitatively predict equipment damage and associated risk to enable better maintenance and inspection planning.

Scenario 1: Thinning

The first “What If” scenario that QRO modeled was a severe thinning scenario. Figure 1 is a thickness LVC for a dehydrator developed using the facility’s thickness measurements. Because the facility had low measured corrosion rates, the initial predicted failure date of the dehydrator was May 2100, and the PoF for this asset was 0%.

Figure 1: Thickness LVC for a dehydrator

However, the facility wanted to visualize what would happen if the dehydrator were to experience severe corrosion. To model this scenario, the Pinnacle team replaced the most recent thickness measurement with a lower value. Figure 2 shows the updated LVC with a new predicted failure date of March 2025 and an updated band of uncertainty, displayed in blue.

Figure 2: Modeled Severe Corrosion Scenario

To demonstrate the decision-making and planning functionality of Newton™, a repair task was planned for the dehydrator. The results of this plan can be seen in Figure 3, which displays the current and mitigated risk curves.  With the addition of a planned repair task, the “risk with plan” curve (dashed grey line) drops to zero.

Figure 3: Dehydrator Risk vs. Mitigated Risk Curve for Severe Corrosion Scenario

Scenario 2: Vibration

The second “What If” scenario that QRO modeled was a severe vibration scenario. Figure 4 is a vibration LVC for a pump bearing within the crude train created with the facility’s vibration data. The analysis did not show any immediate onset of damage with a predicted failure date of December 24, 2030.  However, due to the nature of the failure mode, there is a high degree of uncertainty displayed on the LVC by the blue band.

Figure 4: Vibration LVC for a Pump Bearing

The Pinnacle team added exponentially increasing vibration measurements to the model to visualize the impact vibration will have on the pump bearing. Figure 5 shows the updated LVC with a new predicted failure date of early 2022.

Figure 5: Excessive Vibration LVC

The Pinnacle team added exponentially increasing vibration measurements to the model to visualize the impact vibration will have on the pump bearing. Figure 5 shows the updated LVC with a new predicted failure date of early 2022.

Results

As a result of piloting QRO, the facility was able to visualize the impact of its data on failure and risk over time. The deliverables of the pilot included:

  • Scenario Comparisons:

    The most valuable result for the facility was its ability to model potential thinning and corrosion scenarios on all equipment types. By simulating various “What If” scenarios, facility leadership will be able to identify predicted failure dates and the associated PoF curves for both fixed and non-fixed assets within the platform.

  • Risk Assessment:

    The facility received a risk profile over time for each asset, allowing them to visualize the impact of historical and future activities and identify when assets cross various thresholds.

  • Availability Forecast:

    QRO calculated a forecasted availability of 94.22% for the selected group of 56 assets within the oil train, as shown in Figure 6. Previously, the facility was unable to forecast availability, but with QRO, the facility can now proactively predict availability and failure dates to better manage its assets. The primary drivers for the loss in availability were a lack of measured thickness data in a set of heat exchanger tube bundles and a lack of recorded maintenance history in a group of compressor seals. The lack of eddy current reports for the heat exchanger tube bundles resulted in an over-conservative estimated corrosion rate that increased the PoF.

Figure 6: Availability Forecast for 56 Critical Assets within the Oil Train

Conclusion

After completing the pilot for the oil train, the facility is moving forward with implementing QRO on the remaining assets within the oil train and other gas trains at the facility, which includes 2,000 fixed and non-fixed assets. The expansion of the QRO implementation is expected to result in a 14% total inspection spend reduction, 6% total maintenance spend reduction, and 2-3% total utilization improvement through reduction of loss of containment events and downtime.

At the conclusion of the expanded QRO pilot, the facility will receive:

  • 10-year availability forecast, which can be drilled down into PoF prediction for any equipment component

  • Top 10 contributors to unavailability and cost, which is updated as new data is uploaded into Newton™

Quantifying Refinery Reliability and Availability

Inspectioneering Journal, May/June 2022 Issue  

“Should we be doing more? Are we spending too much? Can we be certain that the actions we’re taking are worth the investment? How can we be more confident that our planned maintenance, monitoring and repair, replace, and upgrade activities are worth the investment and will ensure a change in availability?”

Plant leadership at a large international energy company asked these questions after experiencing a significant drop in plant-wide availability at one of its larger refineries due to a hydrocracker unit. While the plant had previously implemented a risk-based inspection (RBI) program and a reliability centered maintenance (RCM) study, these methodologies seemed subjective and overly conservative and ultimately, were not capable of quantifying results that would provide plant leadership with the confidence that they would realize the availability improvements they were seeking.

The plant decided to pilot Quantitative Reliability Optimization (QRO) to better evaluate equipment risk and predict future availability. The QRO pilot occurred in three phases:

  • Phase 1: A unit or complex that aligned with plant objectives was identified and leveraged to create a unit model. Baseline risk and availability for the plant’s current tasks were calculated.
  • Phase 2: The analysis was updated and modeled with future planned tasks to determine future reliability performance.
  • Phase 3: An optimized inspection, maintenance, and monitoring task and activity plan that met defined criteria for risk, availability, and cost was created.

Pinnacle Releases Economics of Reliability Report for the Refining Industry

Report highlights importance of reliability as refiners face pressure to expand capacity to meet increased demand for petroleum products

PASADENA, TEXAS (June 16, 2022)

Pinnacle, a reliability data analytics company, released its Economics of Reliability report for the refining industry today. The report, which is the seventh installment of Pinnacle’s Economics of Reliability report series, analyzes the impact that reliability has on the refining industry.

“US refiners are reporting record profits and are also running at well above average utilization levels,” said Jeff Krimmel, Chief Strategy Officer at Pinnacle. “This breakneck pace of activity puts real strain on US refining assets. There are important political and economic constraints that will prevent meaningful capacity addition in the US. As a result, domestic refiners have even more incentive to operate as efficiently and reliably as possible.”

The report leverages data from the US Energy Information Administration (EIA) and financial reports of 19 global refiners including ExxonMobil, Shell, and Chevron. Pinnacle analysts estimate that these companies, who are primarily based in the US, spent 2% of their downstream revenue on reliability and operated at an average utilization rate of 85% in 2021. As global demand for petroleum products skyrocketed, US refiners have expanded their utilization to account for the increase in demand. As of June 2022, US refiners are achieving near 95% utilization, a level that has only been exceeded about 10% of the time since 2001.

“Based on our analysis of these downstream operators, we observed that top performers typically achieve higher utilization while strategically targeting their reliability spending,” said Jace Thurman, Market & Data Analyst at Pinnacle. “Reliable operations and assets are imperative to maximizing utilization and capturing high profit margins. These top performers likely employ data-driven reliability programs that identify the most effective use of their capital. While current market conditions have translated to better earnings for downstream operators, optimizing reliability programs and spending will become a critical strategy for refiners to protect increased profit margins.”

The Economics of Reliability - Global Refining 2022