Beyond Limits will be exhibiting with our partner Enexsa at POWERGEN on January 26-28th in Dallas, Texas.

POWERGEN is the largest network and business hub for electricity generators and solution providers engaged in power generation. Power producers, utilities, EPCs, consultants, OEMs, and large-scale energy users gather at POWERGEN International to discover new solutions as large, centralized power generation business models evolve into cleaner and more sustainable energy sources.

Come see the Beyond Limits and ENEXA teams at booth 5338 to learn how our AI software solutions optimize production, save fuel, and decrease operating costs. 

If you’d like to set up a meeting before the event, you can contact us here or download our solution brief here.






Petroleum Economist will be hosting a virtual roundtable on November 9th at 12:00 pm Greenwich Mean Time.  
Beyond Limits CEO AJ Abdallat will join a panel of AI experts from Reliance Industries Limited and Boston Consulting Group to discuss:
REGISTER HERE for the event.
Join our industry leaders in AI and refining to learn about the rise of Cognitive technology in refining by registering here.
The refining industry is undergoing a digital transformation to drive new business value and overcome optimization & profitability challenges. While traditional automation technologies such as advance process control and optimization have attempted to close the commercial gap, many refiners continue to meet varying levels of success between planned objectives and actual performance results.
Artificial Intelligence technologies for refinery optimization are entering a new phase beyond the limitations of data-centric machine learning models. Join industry leaders in AI and refining to learn how cognitive technologies can complement your traditional process by improving stakeholder decisions, capturing expert knowledge, and driving economic optimization opportunities based on actual process conditions.
How far can Cognitive AI take us? Join us on November 17th and 18th to hear from refinery experts and industry leaders as they deep-dive into a new product proven to close the commercial profitability gap at your refineries, presented by Beyond Limits, ARC Advisory Group and bp.
You’ll learn more about:
+ How to close the profitability gap in refinery operations by adding AI software-based Advisors
+ How bp achieved remarkable savings and seamless operator adoption of this new software system
+ How your expert refinery knowledge can live on in the organization to better standardize processes
We’re going live at 3 time slots to accommodate our global viewers:
+ November 17 at 1pm CST for North America & Latin America
+ November 17 at 3pm GMT for Europe & Middle East
+ November 18 at 10am SGT for Asia-Pacific
Register here for our free webinar.

AIDTSEC will be taking place October 27-28 at the King Hussein Bin Talal Convention Center in Jordan.

AIDTSEC paves the way for industry makers to spark motivation and inspire decision makers of the Defense, security, and governmental sectors. This helps to expand the capacity in order to address current and future challenges, place strategies in a global context, and position forces for high performance. This event is an opportunity for AI Defense Technology and Cyber Security solution providers to exhibit and demonstrate their latest achievements, most advanced technologies, and state-of-the-art innovations.” (AIDTSEC)

Don’t miss Beyond Limits CEO AJ Abdallat’s presentation on “Leveraging Cognitive AI to Accelerate Digital Transformation & Industrial Evolution” on October 27th at 9:30am EEST.

Beyond Limits Chief Data Scientist Hussein Al-Natsheh will also be in attendance speaking on “Leveraging AI to Understand Unstructured Data for Defense and Civil Security Applications on October 27th at 11:45am EEST.

REGISTER HERE for the event. 




On September 8th, Beyond Limits CEO AJ Abdallat joined a talented lineup of industry experts from NVIDIA and bp for a TechCrunch webinar to discuss how advanced artificial intelligence (AI) software solutions are playing an important role in the energy sector’s path to digital transformation, helping the industry boost operational efficiency, reduce carbon emissions, and decrease costs.
Check out the talk to learn more about:
  • The latest advances in AI and emerging technologies for energy efficiency 
  • What challenges the energy industry faces on its journey to becoming more efficient, reliable, and sustainable
  • How the human side of digital adoption will impact the energy transition



The Latin American Refining Technology Conference is being held virtually on September 21-23.

Digital technologies and AI are becoming crucial for refiners to improve margins and reduce costs. However, while there is a desire to achieve higher profitability by moving quickly, resistance and inefficiency persist at the plant operations level from uncertainty in how to practically apply a solution, and at a personnel level from a lack of trust in novel digital technologies.

Join industry leaders in AI and refining to explore how cognitive technologies are leading the way to digitize refinery campaign processes from planning to operator action and how operations teams can begin building trust in AI technologies.

Don’t miss Beyond Limits’ presentation being held September 23rd at 8am CST.

You will learn:


REGISTER HERE for this unmissable refining and petrochemical event.






International Refining and Petroleum Conference (IRPC) Operations is being held virtually on September 21-22.

Software-based optimizers and advanced control have traditionally been the primary tools for refinery units and, in some cases, refinery-wide optimization. However, the commercial gap between plan and actual is still elusive across many refineries. At the same time, inconsistencies across shifts persist, with Commercial Managers and Optimization Engineers relying heavily on spreadsheets to communicate the specifics around the linear plan to Operators. 

If you’re looking for a better approach in this digital age, join our talk to discover how cognitive, hybrid intelligence is helping to address the optimization gap by focusing on problems that require interpretation and complex reasoning between the scheduler, process engineer, and operator. We’ll share how a safe open-loop AI solution can help you optimize your plant and continuously improve production, especially at times when control systems alone cannot. 

How can you implement AI today? We’ll show you by deep diving into a new system that uses Cognitive AI technology to provide expert advice to operators when they need it and where they need it. Learn how you can optimize around constraints and bring operations back into your target margins. During this in-depth demonstration, you’ll see a product that does exactly this and discover how easy it is to learn and use within your organization.

Don’t miss Beyond Limits’ presentation September 21 at 2:05pm CDT.


Refiners won’t want to miss this! Join us virtually at the IRPC Operations Conference, REGISTER HERE.





Join us for this live event hosted by SPE Data Sciences & Engineering Analytics Organization by registering here.
Recent advances in autonomous learning and artificial intelligence algorithms have allowed for breakthrough calculations in a number of fields – particularly excelling at efficient data-driven forward modeling and solving computationally intensive inverse modeling problems.
Join Beyond Limits and NVIDIA September 16th at 9am CST as we present an overview of state-of-the-art reinforcement learning strategies and GPU-accelerated computational frameworks. We will briefly cover applications of these methods to model problems including mathematical puzzles, mining optimization and path planning, followed by a deep dive into the industrial problem of well placement optimization. Here, reservoir simulations are coupled to a Soft-Actor-Critic reinforcement learning technique that predicts optimal locations and temporal steps to drill wells to maximize the Net Present Value of cumulative production.
The optimal results obtained will be shared for a benchmark reservoir model. Subsequently, tangible breakthroughs enabled by deep reinforcement learning over conventional numerical strategies, as well as the future of HPC and AI in the energy sector will conclude the presentation.
REGISTER HERE to attend.

The energy industry quite literally powers our modern world – but advancements in new technologies and sustainability initiatives from local and international organizations are dramatically re-shaping how businesses think about, generate, and distribute energy around the world.

Artificial intelligence technologies are playing a pivotal role in the energy industry’s digital transformation, increasing operational efficiencies, lowering carbon emissions, and cutting costs. At the same time, widespread transformation remains hindered by a lack of trust in traditional black-box AI algorithms and misconceptions surrounding the technology’s capabilities and limitations.

How far can AI take us? We are partnering with TechCrunch for a webinar on September 8th at 9am PDT with AI experts and energy leaders to examine these topics and more, presented by Beyond Limits, an industrial-grade Cognitive AI technology company. 


During this webinar, we’ll be discussing:


REGISTER HERE to attend.








Beyond Limits will be presenting at The Connected Plant Conference in Austin, Texas from August 30th-September 1st, 2021. Experience the dynamic world of artificial intelligence (AI) and machine learning to enable technologies driving advanced connectivity and data analytics in the power generation and chemical process industries.

Beyond Limits’ Director of Product Management for Power Generation/Grid Management, Stephan Kwan will be speaking on The Nexus of AI and Human Knowledge in Plant Operations – Monday, August 30th at 10:30 am CT.

Beyond Limits’ Refinery & Process Manufacturing Product Manager, Leslie Rittenberg, joins Martin Gonzalez, bp’s Discipline Leader of Intelligent Operations, for a talk on Harnessing Cognitive Technologies in Refining Wednesday, September 1st at 1:15 pm CT.

The presentations will be located in the main conference room.



Join the conversation with us at the Connected Plant Conference – REGISTER HERE.





09 June 2021
Los Angeles, CA
Beyond Limits Refinery & Process Manufacturing Product Manager, Leslie Rittenberg joined a stellar International Refining and Petroleum Conference (IRPC) line-up with industry experts from BASF, Shell, Dow, ENI, Tupras, Schneider Electric, and more to discuss Harnessing Cognitive Technology in Refining to Accelerate Digitization.
Check out the talk to learn how refiners like bp are using AI to close the profitability gap and operate closer to plan. Watch this recording or read the transcript below.





Video transcript:
Welcome, I’m Leslie Rittenberg, the Refinery and Process Manufacturing Product Manager from Beyond Limits. Today, we’re going to be talking about harnessing cognitive technology in refining to accelerate digitization.
I think we’ve been on some great digital journeys over the last couple of years and improved in many spaces; everybody would like to know how to continue to use AI as we operate closer to plan. 
We’ve used machine learning and AI applications as they relate to availability and optimization; this talk is going to be focused on a discussion in the optimization space as it relates to refining.
When optimizing, what do we strive for? We certainly strive for better raw material yields, wanting faster and more confident decision-making by our operators. We want to always improve our product quality without too much product giveaway. We want to be able to respond to the constraint management challenges and bottlenecks we face in our plants. We postulate that, if we use AI, it’s going to help us start to significantly improve in all of these areas.
What have been some of our challenges? 
I know many of us have done a significant amount of proof of concepts, trying to deploy new software products. In all of those journeys, what we’re trying to do is capture our work and knowledge then encode and digitize that information as fast as possible. This is a race to accelerate and digitize across a business. We want to accomplish this as effectively as possible without facing an extreme amount of programming.
We have also found that we don’t want a black box solution. We want to understand how our models, AI, and advanced analytics come to their conclusions and give us the recommendations that we can trust. 
Finally, humans still need to be kept in the loop with the ability to continue making context-rich decisions. If we do not have consistent and trustworthy results from our AI models, then we have difficulty in deploying and using them.
Here’s a diagram that shows a little bit of the journey we’ve been on. We certainly have improved our process data. We’ve brought a lot of that data into the cloud and spent a lot of time cleaning up data quality. In many cases, we’ve deployed new sensors for even stronger confidence in our numeric solutions.
We’ve also deployed numeric AI – which has helped us see things faster or understand certain relationships that we didn’t previously understand, training them on a lot of historical data. We are now alerting and visualizing messages to be more proactive in our plants, as opposed to reactive.
However, many numeric AI programs still give us false positives in several cases. Again, this goes back to the level of trust that we have and the amount of work needed to dismiss the false positives; we have a lot of work, in terms of model breakdown, and in sustaining those models, to give us the best solutions.
With anything, because of the safety-critical nature of all of our businesses, we really want our operators to buy into the solution, so they can trust it and take the optimal course of action.
So, what can we do about this?
We can start to insert what Beyond Limits is recommending: symbolic AI. It’s a more effective hybrid – or composite solution – that is going to start closing the gaps and deficiencies we’ve been experiencing with solely numeric AI solutions. Symbolic AI has human-like reasoning and solving capabilities that can help us with the deficiencies we’ve been seeing in numeric AI.
What do we want it to do? 
We wanted to improve that decision support package for the humans in the loop, predominantly our operators. The solution can recommend classifications, give us confidence scores, and provide recommendations. Most noteworthy, the solution can act as a glass box, providing cognitive traces that explain how it came to its conclusions. We are also able to interact with the solution, increasing operator trust and reducing uncertainty; ultimately, arriving at a faster time-to-decision and upscaling our workforce simultaneously.
Now let’s get deeper into refinery-specific challenges.
Over the years, especially in the space of optimization, we’ve been innovative – and with most of us utilizing advantage feedstock programs. We’ve improved our profitability by buying cheaper feedstocks and crudes, and they generally have more challenging needs when processing them in our refinery; having higher sulfur and are heavier crudes by far.
Also, especially with last year’s pandemic, we’ve seen a large amount of our experienced workforce depart. Many of the major oil and gas companies offered severance packages with the challenging P&L operations, and a lot of experience was lost. 
Finally, with product demand challenges that we saw result from the pandemic (and cyberattacks), large volatility in our refinery margins is a persistent problem. We’ve responded well over the years by incrementally improving our margins. Many of us have invested in the front end of our kits, modifying our crude units, and began the process of major capital investments. 
It’s not unusual to be faced with new bottlenecks and constraints that show up downstream of your refinery. When faced with those constraints, they present new operational challenges when it comes to executing a commercial plan. They can create volatility in plant operations, often changing the predictability of catalyst life, as well as instigate unplanned maintenance and downtime. We’ve all seen these challenges, knowing that our operators always need assistance and support from engineering experts.
Here’s a diagram as we start to think about how we execute our refinery commercial plans. As you can see, on the bottom level, we have some very strong systems and control processes. We’ve invested heavily over the years to automate and to have a high level of confidence in the performance of that equipment. 
On the top level, we’ve clearly invested in our planning and scheduling processes. We’ve improved our models in that space, we have very capable staff in that space, and we have high expectations that we’re going to deliver a very executable and profitable plan when we process our different crude feedstocks.
Now, if we look at the middle section, we have improved our operations staff over the years through simulator training and obviously have turnover in that space, providing good training when we bring on new staff. 
But if we think about it in all honesty, how we hand over the plan that we want them to execute flawlessly each time, has not changed tremendously over the years. We still experience, even though we have definitely improved levels one, two and four, we still have a gap between our plan and actual execution when we carry out a commercial plan. 
Beyond Limits felt we could place an advisor in this space to close that profitability gap, serving as an assistant to operations in real-time and identifying plan versus actual performance with full transparency as one source of the truth. This would provide the ability to execute closer to plan. 
The advisor also works to encode expert engineering knowledge, actually helping operators solve the gap problem in real-time. It deploys an AI reasoner that looks at process constraints and recognizes the best commercial options for an operator to utilize in order to adjust the plant and achieve a higher level of profitability. It iterates and tells the planning and scheduling organization whether their plan was as achievable as they thought it would and/or where the gaps for improvement exist. 
Over time, we are seeing an improvement in adherence-to-plan as well as the increased ability to iterate across an entire organization and fundamentally improve the capacity to deliver solutions that shrink plan gaps.
We have deployed our solution at a very large complex refinery in Indiana; bp’s Whiting refinery is within the top 10 of the largest, most complex refineries in the US. Before implementing our solution, they were struggling in a couple of places.
For example, when they were doing feedstock campaign changes, they would have inconsistent operations and a larger than average unsteady state during those changes. They were faced with competing priorities in their constraints and, at times, operators did not fully understand the instructions or the priorities that were coming from the commercial group. Due to this, they would have uncertainty in their decision-making leading to flawed commercial execution.
The solution we deployed had a no-code SaaS application in the cloud. It allowed bp to optimize according to the plan, closer to 100% of the time. The unsteady state that they were experiencing during campaign changes was reduced, and they upgraded to higher-value products. Overall, operator agility was accelerated with increased confidence leading to faster decision-making.
Another incredible thing around the solution’s deployment was the adoption time. I’ve been involved in software deployment packages over the years in many different plants; bp’s Whiting team was successful in adopting this program in one month. They were able to engage with their entire process and optimization engineers and create over 200 complex refinery objectives to represent their commercial plan. They represented this with no code-in language, with which operators were very familiar.
After deployment, we monitored their ability to meet the plan and we saw a 17% improvement in operating to plan. We also saw that they used over 2000 real-time sensors to help the operators evaluate and prioritize.
Beyond Limits is excited to bring these AI products to many different industries and within the oil and gas sector.
The example I just gave you was just one of our solutions – our Refinery Operations Advisor package. We also have offers in the well production space with well infill and well health solutions. Well infill is focused on improving overall production and helping production teams better understand where to drill while well health manages the health and asset monitoring around wells. 
Our Cognitive Formulation Advisor is also helping the lubrication portion of our business create more economical formulations, faster.
In power and water, we also have sensor placement solutions – while in healthcare, we have a smart patient monitoring solution. We offer investment solutions to the finance industry as well.
Thank you for your time; I’m looking forward to answering any questions you may have.




20 MAY 2021
Beyond Limits Senior Machine Learning Scientist, Vidyasagar presented a technical session on GPU-accelerated Deep Reinforcement Learning for Field Planning at NIVIDA GTC 2021.
Check out the full GTC technical talk to learn about using reinforcement learning for the sequential decision-making process of well-placement optimization and how to maximize net present dollar value (NPV).
About this GTC Talk
Recently, GPU-accelerated reinforcement learning (RL) using deep convolution neural networks has gained significant traction. This presentation describes RL applied to the sequential decision-making process of well-placement optimization in the upstream energy industry.
High-fidelity multiphase porous media flow simulations of geological subsurface reservoirs are coupled with the placement of sources/sinks corresponding to wells; the goal of this process is to maximize net present dollar value (NPV) obtained through cumulative production.
Due to high-resolution reservoir grids and a combinatorial explosion in the number of possible spatial and temporal steps for placement of wells, the optimization routine is intractable and requires high-performance computing (HPC) strategies to solve realistic systems.
In this presentation, the advantages of RL over other conventional methods will be described, together with benchmark examples and results obtained on several reservoir models. The use of A100 GPUs to accelerate the learning and inference aspects of reinforcement learning will be shown to yield significant improvements in both performance and the best NPV solutions obtained by the optimization routine. Finally, the future of deep RL in the context of HPC and scientific simulation in energy will be outlined.