Refining Blog

Refiners’ Guide to Digital Transformation

Jim Cahill — Fri, 01 Dec 2023 20:45:17 GMT

Refineries make the fuels that make our way of life possible. Turning crude oil into usable fuels is a highly energy-intensive business. And it’s an industry that provides excellent opportunities for digital transformation. Emerson’s Jonas Berge spoke at the Asian Downstream Summit 2023. His presentation, The refiner’s guide to digital transformation, shared how plant transformations in driving improved safety, sustainability, reliability, and quality performance can help refiners overcome operational challenges.

Automation is an essential enabler for these transformations. Here are some highlights from Jonas’ presentation. Jonas opens by asking the attendees to imagine a digitally transformed refinery—a data-driven refinery, an intelligent refinery with:

No surprise equipment failures and no manual data collection – in the name of reliability and maintenance
No hidden equipment fouling
No undetected loss or flaring – in the name of sustainability
No surprise loss of containment
No undetected leaks or spills – in the name of safety, health, and the environment
No manual valves in the wrong position
No non-uniform temperature profiles – for production

Today, many challenges that refineries face are rooted in manual work processes. That includes manual data collection and the interpretation of that data. This data is related to health, safety & environment (HSE), sustainability, energy efficiency & emissions, reliability, maintenance & integrity, and production & quality. Sampling may be done daily, weekly, monthly, or even yearly. This data frequency can lead to slow responses, excessive energy consumption and emissions, equipment failure, and off-spec production.

An essential strategy to address these challenges is automation: threat monitoring, performance monitoring, condition monitoring, and process monitoring & valve remote control. Some use cases with wireless sensor monitoring in occupational health and safety include emergency safety shower and eyewash stations, manual valves, flammable gas, toxic gas, and tank overfill.

In sustainability and energy, some everyday use cases include steam traps, pressure relief valves, air-cooled heat exchangers, cooling towers, and heat exchangers. These are but a few of the many areas where wireless monitoring can help drive sustainability-related performance improvements.

In reliability and maintenance, common use cases include pumps, air-cooled heat exchangers, cooling towers, pipe corrosion and erosion, manual inspection rounds, control valves, heat trace systems, and breather relief valves (PVRV).

In production, everyday use cases include field operator rounds, offsite tank farm storage tanks, wellhead and control panels, temperature profiles, local control panels, offsite standby pumps, and consumables inventory.

Jonas provided recommendations to the refiners in attendance. First, look for ready-made apps that can be applied rapidly with the required capabilities at a low cost. For example, Plantweb Insight applications are modular and available for many plant assets. These assets include steam traps, pumps, heat exchangers & air-cooled heat exchangers, cooling towers, corrosion and erosion monitoring, safety showers, inspections, and lighting.

Embedded industrial analytics in these applications enable maintenance and reliability engineers to put them to use immediately. No data science or support tasks are required, such as importing historical data, cleansing the data, selecting the correct algorithm, and training & testing the algorithm.

Applying the technologies transforms operations and drives results.

Visit the Refining and Industrial Internet of Things sections on Emerson.com for more on the technologies and solutions to drive improved operational and business performance.

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AFPM Lifetime Achievement Award–Tim Olsen

Jim Cahill — Mon, 09 Oct 2023 15:07:15 GMT

Congratulations to Tim Olsen for achieving an AFPM Lifetime Achievement Award at the 2023 AFPM Summit meeting in Dallas, Texas. The American Fuel & Petrochemical Manufacturers (AFPM):

…is the leading trade association representing makers of the fuels that keep us moving, the petrochemicals that are the essential building blocks for modern life and the midstream companies that get our feedstocks and products where they need to go.

Tim has 33 years of experience in the refining industry and has been an integral part of the AFPM organization for more than 20+ years. He has been participating in many the Reliability and Maintenance conferences as well as the planning for Operational Planning, Controls & Automation Technology Committee, Summit Steering Committee, and the Technical Committee on Leadership.

He also leads the development of important safety documents on abnormal situation management and continues to encourage active exchange of knowledge across the refining and petrochemical industries. Tim also willingly shares his knowledge and experience as a mentor to many in the industry.

Here is the presentation of the award and Tim’s remarks in accepting it.

Congratulations and well deserved, Tim!

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Improving Terminal Throughput and Efficiency

Jim Cahill — Wed, 27 Sep 2023 20:58:52 GMT

Yesterday, we highlighted many technologies to improve loading and unloading operations. But what about the commercial and logistical sides to enhance efficiency and throughput? Emerson’s Kevin Niles and Sandy Tiu explore this question in a Tanks & Terminals article, Don’t Just Go With The Flow (pp. 19-22).

They open the article by noting how increases in LNG shipments and crude oil imports and exports have increased demands for terminals. The growth to meet these demands has introduced challenges.

As companies introduce new products into their terminals and acquire new assets – or even attempt to do more with what they already have – they must find ways to optimise those assets to expand operations without needing to grow or overtax their workforce.

Digitalization is one way companies are addressing this challenge by:

…using software to increase throughput and efficiency – ultimately increasing standardization, safety, and performance while simultaneously delivering higher profitability.

Offloading efficiency is a vital consideration when selecting a terminal.

If one terminal can turn a vessel around in 12 hours and another takes 18, this time difference will be a significant factor in facility choice, as customers can use the extra time to turn their vessel around, get more product into it, and send it elsewhere.

An essential component in this efficiency increase is order-to-cash software:

…which digitalises operations by collecting the information surrounding a customer’s order for the movement of product into, out of, or within the facility.

Emerson’s Synthesis order-to-cash software is a liquid logistics and commercial management application used by companies that store or transport liquid hydrocarbons to manage their entire order-to-cash cycle. Using standard APIs and SOA, Synthesis allows enterprises to integrate tightly and extensively with any other applications that are touch points between nominations and invoicing.

While order-to-cash applications have existed for a while:

…many organizations are just getting started on their digitalisation journey… Once a team has a vision and an automation software solution in place, the terminal – or even series of terminals – can operate as a cohesive, interconnected ecosystem for increased efficiency.

Kevin and Sandy share some advantages:

Improved visibility and efficiency
Efficiently navigate external hurdles
Improved safety

One example of improved visibility and efficiency is in planning movements.

Built-in algorithms track the products, bringing in a batch, splitting it into different pieces, and moving those pieces through different tanks – avoiding mixing where necessary, and automatically mixing where desirable.

External hurdles can include situations like customs delays.

As a batch is processed through a terminal, order-to-cash software automatically updates status and documentation, allowing the vessel to depart whether clearance was granted in the middle of the afternoon or in the dead of night.

Safety can be improved by eliminating paper-based safety checklists by automating these safety procedures and performing the checks in real-time, electronically documenting the checks and results.

Read the article for more on how automation combined with highly advanced order-to-cash software, such as Synthesis, to improve operational efficiency and terminal profitability. Visit the Software for Energy Transportation and Storage on Emerson.com for more ways to establish a more efficient supply chain.

The post Improving Terminal Throughput and Efficiency appeared first on the Emerson Automation Experts blog.

Accurate Level Measurements in Boiling Hydrocarbon Applications

Jim Cahill — Tue, 15 Aug 2023 13:00:29 GMT

The stated mission of our blog is to connect you with the experts here at Emerson from around the globe. Occasionally, I get copied on communications between a visitor to the blog and one of our experts. In the case of one I saw this morning. I wanted to share a generic version of the exchange and highlight some key points from a presentation shared.

The blog visitor asked:

I’m currently working in the Permian Basin for [company] and I’m having trouble with a radar that’s off. The process is liquid propane and I noticed it’s pretty bubbly in the sight glass. They are using [other supplier] radars but my question is, can we fix this problem with some 5300 series?

Emerson’s John Butler replied:

I can’t speak to the [other supplier] unit because I don’t know their capabilities that well, but this sounds like something we deal with fairly frequently and can usually solve.

This would be considered a boiling hydrocarbon application, which uses more of an advanced feature in the radar, called PEP (Probe End Projection). Attached is a presentation that was done back in 2010 on this subject at our Emerson Exchange.

Take a look at it and let me know if this sounds like what you are seeing.

The presentation John shared was titled Measuring Levels in Highly Dynamic Petroleum Processes. It highlighted some highly dynamic hydrocarbon processes such as boiling/vaporizing hydrocarbons, off-gassing hydrocarbons, and processes with rapid level changes.

Measurement technologies that can address these challenging applications include advanced guided wave radar for fast response, probe end projection to stabilize the level output, and special considerations for bridle design. Together, this approach can help to stabilize level output and run without process upsets.

In the presentation, John and the customer shared a case study of a gas plant’s receiver economizer processed propane at 55 psig and 10 degF at a 50% setpoint. The process was challenging to control due to 3 interacting loops, very rapid level changes, and boiling fluid upon pressure drops. Traditional guided wave radar level measurements occasionally lose the level and fail high, causing a process trip.

The solution was to use a Rosemount 5300 series guided wave radar (GWR) level transmitter. This technology is based on the TDR (Time Domain Reflectometry) technology which is also called “contacting radar” or “radar on a rope.” The level is measured by low-power nano-second microwave pulses guided down a probe suspended in the process media. When a radar pulse reaches media with a different dielectric constant, part of the energy is reflected back to the transmitter. The time difference between the transmitted reference pulse and the reflected pulse is converted into a distance value from which the level is calculated.

Using ultra-rapid three-nanosecond direct switch technology between transmitter and receiver gives a better signal-to-noise ratio, a better margin to handle disturbing factors as objects close to probe, coating, foam, vapor, and turbulence and makes it able to manage long measuring ranges and low dielectric (low reflective) media also with the single probe. Probe end projection is used to manage the lowest dielectrics on longer measuring ranges. The probe end is used when the transmitter sees thru the media to calculate the level.

Microwaves slow down in process fluids at a rate in relation to the fluid’s dielectric constant. Since hydrocarbons such as propane, in this case, have low dielectric constants, the receiver can see to the end of the probe, which is a fixed, known distance. As process fluid is added, the end of the probe will appear to be farther away since the time of flight is longer due to this increase (apparent distance).

With a known product dielectric (propane fluid – 1.6 ε₀ at 0° C), the level can be calculated by comparing the known distance to the apparent distance. This results in better measurement availability.

Correct sizing of the bridle where the measurements occur is essential since gas bubbles rising in small-diameter bridles tend to lift the fluid level. In contrast, bubbles break out in large bridles without causing a level rise.

For these types of applications, it is important to insulate the bridles. The temperature in the bridle should be as close to the vessel temperature as possible. Since bridles have much less fluid mass than the vessels, they heat and cool faster with ambient temp changes. With different temperatures, bridles will show a different level than the vessel.

Visit the Rosemount 5300 Level Transmitter section on Emerson.com for more on how this transmitter provides great reliability and safety features for challenging liquid and solids level applications.

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Monitoring Corrosion and Erosion in Carbon Capture Applications

Jim Cahill — Wed, 03 May 2023 13:00:16 GMT

In the process and hybrid manufacturing and production industries, fluids flowing through piping can cause corrosion and erosion over time. In a 4C Health, Safety & Environmental Conference presentation, Corrosion & Erosion Relates to 56% of Losses with Piping. Overcoming These Challenges While Increasing Carbon Capture., Emerson’s Justin Vasquez described the challenges and solutions to address these conditions.

His presentation focused explicitly on carbon capture projects essential to sustainability initiatives in the upstream, midstream, and downstream hydrocarbon sectors. Justin explained that these projects can potentially remove 90-99% of a facility’s carbon emissions. In these carbon capture projects, amine absorption is one of two concern areas for corrosion and erosion.

Corrosion is the primary cause of CO₂ pipeline failures, primarily from the liquefication phase. Removing water is essential in avoiding risk. The cost of corrosion-resistant piping is typically not economically viable, and traditional corrosion monitoring methods are unsuitable. Infrequent manual measurements often have poor repeatability and accuracy. Calculating corrosion rates is challenging and unreliable. Informed decision-making is difficult given these challenges.

Dense-phase CO₂ leaks are violent and incredibly dangerous. Large sections of piping can be damaged with a crater created. This risk must be mitigated to protect personnel, the surrounding community, the environment, and the company’s financial viability.

An effective solution to mitigate these risks is to install Rosemount Wireless Permasense Corrosion & Erosion transmitters for continuous, real-time measurements that feed built-for-purpose operational analytics in the Plantweb Insight Non-Intrusive Corrosion application. Data from these transmitters are delivered securely to the end user’s desk, providing visualizations and analytics to assess the impact of corrosion and erosion.

Follow the links above for more on these technologies to identify corrosion and erosion before it affects safe and sustainable operations.

The post Monitoring Corrosion and Erosion in Carbon Capture Applications appeared first on the Emerson Automation Experts blog.

Advanced Pipeline Leak Detection Podcast

Jim Cahill — Thu, 15 Dec 2022 15:35:28 GMT

Pipelines are instrumental in moving energy around the globe. Offshore Technology cites some statistics.

The total length of the global trunk/transmission pipeline network is 2,034,065.0 km (with start years up to 2023), according to GlobalData’s latest report.

Of this total length, crude oil pipelines constitute 379,000.4 km [235,500 miles], petroleum products pipelines constitute 267,289.6 km [166,086 miles], natural gas pipelines constitute 1,295,563.6 km [805,026 miles] and NGL pipelines constitute 92,211.8 km [57,298 miles].

It is paramount to continuously monitor these pipelines for safe, reliable, and sustainable operations. In this Emerson Automation Experts podcast, I speak with Emerson’s Greg Morrow to discuss how real-time transient models (RTTM) in the PipelineManager software application help pipeline companies maintain high-performance levels.

Listen to the podcast and visit the Software for Energy Transportation & Storage section on Emerson.com for more on advanced leak detection technology to help you achieve safer, more sustainable operations.

Transcript

Jim: Hi everyone, this is Jim Cahill with another “Emerson Automation Experts” podcast. Today we’re discussing the importance of models and modeling in making transportation via pipelines safer and more reliable. I’m joined by Emerson’s Greg Morrow to discuss why this is so and how to drive improvements in your operations. Welcome, Greg.

Greg: Hi Jim. Glad to be here.

Jim: Well, it’s great having you here. Well, let’s jump right into it and let me ask you to share your background and path to your current role with us here at Emerson.

Greg: Okay. Well, I got my doctorate in physics a while back. I did my work in particle physics up at Fermilab in Chicago and after that I got a job working in pipelines, pipeline simulation. And I’ve been with Emerson, or our predecessor company working with RTTMs for a long time now, 25 years. It doesn’t feel that long every day, but that’s how long it’s been and my role is really as leak detection subject matter expert.

Jim: Well that’s great background. Thank you so much for that. Well, let’s get into it about, you had mentioned RTTM, What exactly is RTTM?

Greg: Okay, that stands for real-time transient model and let’s unpack that. Model is a representation of something. I can get very philosophical about what all that actually means, but at its core, a model is a representation of something. In this case, it’s a sophisticated physics and mathematical representation of a pipeline, in some context, this is called a digital twin.

Transient means, that it takes into account that things are changing. And this contrasts with steady state, which assumes that everything is constant. And real-time means that it’s based on measurements from instruments in the field, which can be live or recorded. And it’s really important part of a good RTTM, that you’re able to play back that recorded instrument data for tuning purposes and analysis.

Jim: So how does the RTTM fit into our PipelineManager software application?

Greg: So it’s the core of our high-performance leak detection system. And so the key to that is it’s an accurate representation of exactly what’s happening on the pipeline. So in addition to leak detection, it’s also used to manage the pipeline and that’s features like batch tracking or scraper tracking, DRA [drag reducing agents] tracking, hydraulic monitoring like MAOP [maximum allowable operating pressure] alarms, hydrate formation warnings, and natural gas systems, and so on from there.

Jim: So is the PipelineManager application something to be used with gas or liquid pipelines?

Greg: Both. So the key there is the equations of motion are the same regardless. The only difference is the equation of state. The equation of state is a relationship for a fluid where you determine the density in other properties, from the pressure and temperature, and some defined parameters for the fluid. We have different equations of states for all sorts of fluid, from the API correlations for crude and refined products to NGLs, to GERG 2008 for natural gas, that’s well known as the most accurate equation of state for natural gas. So, both liquids and gases, anything you’ve got.

Jim: Well, that’s great. Covers the whole gamut. So how difficult is this application to apply?

Greg: So the RTTM is very complete. So it does have a lot of things you can modify or fine-tune, ground thermal properties, instrument filters and so on, and so forth. But what’s key to understand is that the defaults are widely applicable. So we ship with a bunch of different types of ground and you can use one of those, and it’ll be pretty good. Out of the box, your leak detection system’s going to be accurate, sensitive, reliable and robust, but it also rewards deeper attention to detail. And we call this tuning.

Jim: So for this application, what’s required from an instrumentation standpoint?

Greg: So the RTTM has a minimum set of required instruments and for our purposes, it’s basically pressure, and flow at every inlet, and outlet, and pressures it pumps, and regulators that can change the pressure from the other side of the pipeline, but more instrumentation is better. So in the case of pressures, putting a pressure instrument on an intermediate valve at a river crossing or something like that is helpful. Smaller segments tend to make the model more sensitive. Sensor quality is also a factor. If your pressures report by exception at 0.1 bar, which is a pretty big step, you’re not really going to get good results, modeling slow drifts and sharp transients. Temperatures are also very important depending on the fluids you transport. Some of them like gas can be extremely sensitive to temperature. So good temperature measurement is important.

Can also have fluid property sensors like density or viscosity, or real-time composition measurements like gas chromatographs that tell you, for example, this batch of fluid has a lot of extra ethane in it or something like that. Then you also can use instruments to support other features. Like if you’re doing scraper tracking, you’re gonna need scraper sensors to tell you when the scraper is launched and where it passes, and so forth. So all of those things play into the development of the model. And one of my remarks is often, I won’t turn down extra instrumentation. More instrumentation is almost always better, but again, out of the box, the RTTM is gonna work with the instrumentation you have as long as you meet that minimum set.

Jim: Now, you had mentioned that more measurements can help with the tuning of these models. So what role does tuning play in the models?

Greg: So, again, I could wax philosophical about this. You can catch me offline and I’ll be happy to talk with you about it. But for just very briefly, tuning is changing the parameters of the model to achieve greater correspondence with reality. So, you look for places where the model doesn’t show what’s happening in reality. So for, you know, something that’s not unusual is when you turn on a pump, get a pressure surge, and the fluid reacts in the model slightly differently than the fluid reacts in reality. So, you do something like modify the fluid composition or the pipe wall thickness or the thermal conductivity of the ground or some other parameter to make the model correspond better in that place where it’s not.

So, as a practice, a lot of tuning is actually understanding the instrumentation. That’s both the instrument quality itself, as well as the SCADA data acquisition properties like the “Report by Exception” that I mentioned, and also, what part of the pipeline the instrument applies to. For example, if a pressure’s upstream of pipeline equipment versus downstream of some pipeline equipment, like I said, the valves or something like that, that can make a difference in part.

And understanding that helps you get the model accuracy to match reality. Because the RTTM is the most sophisticated model of the pipeline possible, you can get it extremely close to reality, which helps your leak detection achieve the best sensitivity, reliability, robustness, and accuracy. And this can be an ongoing process built into your process of continual improvement.

Jim: Well, that’s interesting. I noticed that that’s the second time you talked about sensitivity, reliability, and some of those other things. Is there a reason for that?

Greg: So, those are terms from API 1130, which is a document that discusses computational pipeline models or CPM, like the RTTM. And they’re particularly useful terms for evaluating leak detection systems. Sensitivity is how small a leak you can detect and how fast. Robustness is your ability to detect a leak no matter what pipeline conditions there are, like, steady-state or transient, shut-in, slack, supercritical, and so forth.

Reliability is how much you trust the system’s alarms. If it gives a lot of false positive alarms or misses true events it should have caught, it’s not as reliable as if it’s an alarm is always completely correct. And accuracy is how accurate the system is in determining things like leak size and location. The transient part of RTTM, Real-Time Transient Model, is the biggest part of the robustness of the leak detection system because modeling things as they’re changing is the biggest part of ensuring that you get sensitivity regardless of what the pipeline is doing.

How sophisticated and well-tuned the model is, determines how sensitive it can be. Sensitivity and reliability are often in a bit of a trade-off so if there’s a certain amount of uncertainty built into the model that just because the models cannot be perfectly accurate. If you push on the sensitivity, you’re gonna push yourself in the direction of that uncertainty and you’re going to generally get more false positives.

On the other side, if you say, I cannot tolerate any false positives and some customers, that’s the rule, then in order to make sure that you’re above that sort of underlying irreducible systematic uncertainty, then your sensitivity is gonna be somewhat higher. And this trade-off is really exacerbated by the statistics of small numbers. So, if a leak is one in a million and you’re 99.99% reliable, you’re still going to have 100 false positives for every time you have a real leak. Reliability is a big part of our ongoing R&D. Machine learning and statistical models can really help here.

One of the interesting challenges is, of course, because of those statistics of small numbers where false positives are just sort of inherently more likely than true positives. You can, if you do it naively, accidentally train your system that any potential alarm is false and just throw it away. You’ll be right 99 times out of 100, but you also won’t have a functioning leak detection system. So, this is one of the interesting problems that we’re investigating. As scientists, interesting problems are the ones that really get us into work in the morning.

Jim: Well, it’s fascinating that trade-off and that the numbers involved in that where you can still have all those false positives even with that level of reliability. So, given the criteria that established in some of those standards, how does the RTTM measure up?

Greg: Very good question. Among CPM systems, the RTTM is sort of universally understood to have the overall best score. That’s not to say that other systems don’t have their advantages. Other systems may excel in one area, negative pressure wave or NPW systems are by far the most accurate for leak location, for example. But NPW systems are not particularly robust or reliable. The RTTM is a standout for covering all four corners thoroughly. It’s also good to have complimentary systems. In fact, it’s often required by regulatory bodies.

And PLM [PipelineManager] includes several complimentary systems like RuptureSentinel, and it can also integrate with third-party complementary systems. So, whatever your needs are, we’re likely to help meet them. PLM also helps you develop key performance indicators, KPIs, for your system as well. One of our apps is specifically aimed at this, the leak detection performance analyzer. So, we’re really there to support your Leak Detection Program Management.

Jim: Now, I know we’re not the only RTTM available in the marketplace. So, how does our PipelineManager application stand out from others in the industry?

Greg: Not all RTTMs are the same. They differ in what’s included in the model and the mathematical method used to solve the model equations. Basically, the details that I’m not going into here. A really simple one is just how you calculate the transfer of heat from the pipeline to the ground. You can do that a bunch of different ways and the RTTMs vary in that sort of details. They offer differ in what you do with the output of the model.

So, the output of the hydraulic model is an exact representation of what’s happening on the pipeline. And what you do with that can also vary how, for example, you determine whether there’s a leak alarm or how the batches are moving through the system, etc. So, RTTM stands out for its thoroughness. We’ve used as much physical rigor as possible to ensure the greatest accuracy possible in the hydraulics.

It stands out for our experience and expertise. We’ve been doing this for a long time, and that’s given us a lot of opportunity to hone the performance of the model as well as the services we provide implementing PipelineManager to meet your needs. And it stands out in terms of performance. We’ve won a number of head-to-head competitions where we’ve demonstrated greater performance in those four API criteria.

And it stands out in terms of features. It’s not enough to have “batch tracking” you have to provide batch tracking that meets the pipeline operator’s requirements, whether that’s calculation of interface volume or providing actual volume corrections for commercial applications. It’s not just batch tracking, of course, we have the widest selection of pipeline management features no matter what your needs might be.

Jim: Well, that’s a really good overview. I liked how it started that it could be applied right out of the box and then you have the flexibility to improve the accuracy of the model just based on how you’ve instrumented it. I guess before we close things down, do you have any final perspectives to share with our listeners about RTTMs?

Greg: So, as you just said, out of the box, PLM’s gonna give you good leak detection. And the reward of a continual improvement process is world-class leak addiction performance in all four sectors of sensitivity, reliability, robustness, and accuracy. And even though leak detection is very important, you’re not going to be dealing with leaks every day, or if you are, you have other problems than the software.

You’re going to be operating your pipeline every day. Your controllers are gonna be busy doing controller things, shipping fluid to this location or that location. PipelineManager helps you do that. Whatever it is that you’re doing, we’ll help you understand what’s going on your pipeline better than anybody else in the market.

Jim: Well, I know we’re only able to scratch the surface in this podcast. So where can our listeners go to learn more?

Greg: So, we have a four-part webinar series and anybody can go to www.emerson.com/leakdetectionwebinars. And you’ll be able to go through all of those sessions and get a more in-depth view of our products and what they can do for you. You can also visit www.emerson.com/scadaforenergy to access more information on PipelineManager, as well as our entire suite of energy, transportation, and storage software offerings.

Jim: Well, that’s great. And I’ll add hyperlinks around those in our transcript that we include with the podcast. Well, Greg, I wanna thank you so much for sharing your thoughts and your expertise with our listeners today.

Greg: It’s always a great pleasure to talk to people about this. And again, feel free to contact me offline. I’m happy to discuss all of this. And you can see me at conferences and especially our Flow User conference every year.

-End of Transcript-

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