08 June 2021
Los Angeles, CA
Beyond Limits has harnessed the power of NVIDIA’s platform to solve one of the most substantial problems in the upstream oil and gas industry. Read the full case study HERE.
The Upstream Sector’s Greatest Challenge: Field Planning
Upstream endeavors normally demand an extensive team of geologists, petro-physicists, reservoir engineers, mathematicians and more, working together in order to construct models that take several months, or even years, to complete. It’s a necessity for such models to capture expert input, as well as statical and dynamic data from considerably high-value assets. Historical human knowledge, experience, and expertise are crucial at almost every stage of interpreting historical performance and data.
One of the greatest challenges for the upstream oil and gas sector is the optimization of well placement in oil and gas reservoirs (field planning). As an example, and to give a sense of the scope of the challenge, a game of chess has nearly five million possible moves after the first five. Optimal well placement paints a similar picture. Well placement in a small reservoir can have as many as one hundred trillion possible combinations within only five sequential, non-commutative choices of vertical well-drilling locations. This game of choice is on a level all its own.
Luckily for everyone involved, Beyond Limits is rewriting the rulebook when it comes to solving the well placement optimization problem at scale. By leveraging NVIDIA A100 Tensor Core GPUs, Beyond Limits is developing a deep reinforcement learning (DRL) framework that provides high-performance computing (HPC) infrastructure to support novel AI frameworks making the strategic moves necessary to simplify this intricate field.
Inside Industry Solutions: The NVIDIA x Beyond Limits Approach
Beyond Limits and NVIDIA set out to solve the computational challenge currently facing many companies across the upstream oil and gas sector by developing a new solution that elevates field planning workflows based on a DLR framework with a primary objective to maximize net present value (NPV), i.e., projected dollar value for production capabilities of any given field with a specified number of wells.
Unavoidable additions of well assets inherently result in both higher drilling costs and increased risk for negative environmental impacts. Therefore, simultaneously maximizing returns while minimizing drilling is a capability that’s paramount to the energy sector. Adopting cutting-edge AI solutions is becoming increasingly essential for upstream companies to successfully reduce waste while maximizing productivity and profitability over the projected lifetime of an asset as essential as their most valuable wells.
“Beyond Limits has used the power of the NVIDIA platform to solve one the most substantial problems in the upstream oil and gas industry.” -NVIDIA
GATHER EVERY DETAIL ABOUT THE NVIDIA & BEYOND LIMITS FIELD PLANNING CASE STUDY HERE.
Beyond Limits AI Solution for Reservoir Management Accelerated by NVIDIA GPU’s
Beyond Limits AI solution for reservoir management is just one example of an application that supports operators to dramatically accelerate data integration and analysis for pinpointing drilling opportunities, weighing opportunity versus risk, and speeding up time to decisions.
Beyond Limits’ NVIDIA-GPU accelerated reinforcement learning framework enhances the solution with high-performance AI capabilities to optimize well placement decisions by identifying several thousand combinations, reduced from over one hundred trillion possible combinations (mentioned at the outset). Adoption of this advanced solution yields over 250% algorithmic performance improvement in a typical reservoir, leading to an additional 10% improvement in NPV for vertical wells.
Even the smallest enhancements can make a huge impact. Seemingly minor adjustments help solve challenges at an accelerated speed and increases scale thus reducing well placement (in typical reservoirs) timelines down from months to hours, yielding millions of dollars in additional value and revenue.
WATCH BEYOND LIMITS’ ON-DEMAND NVIDIA GTC TALK FOR MORE TECHNICAL INSIGHT INTO THE CASE STUDY HERE.
Field Planning for Deep Reinforcement Learning: The Net Zero Impact
AI will play a key role in helping the energy industry achieve net zero ambitions by making operations more efficient, increasing productivity, and reducing waste. AI applications such as Beyond Limits’ NVIDIA-GPU reinforcement learning framework can support these initiatives with carbon capture and sequestration, reducing drilling of new wells, and transitioning to low-carbon energy sources. Examples of intentional efforts toward accomplishing those goals include identifying the best CO2 injection candidates across depleted fields, providing optimal planning for existing fields, minimizing drilling length, converting between injection and production weeks, and sequential planning for novel energy use cases broader than field planning.
More Benefits of AI in Upstream: From Deep Reinforcement Learning to Cognitive AI
Beyond Limits advanced AI technology has the ability to help support entire upstream strategies, streamlining processes, and optimizing entire operations. Several benefits for implementing and adopting this technology in the sector include:
+ Capturing Institutional Knowledge & Business Logic
This AI solution bridges the knowledge-loss gap for providers by capturing and encoding veteran operator knowledge then distributing that essential expertise, best practices, and business logic across an entire organization so it’s never lost and easily transferrable to newer, up-and-coming operators within the sector.
+ Reducing Uncertainty when Data is Limited
This technological approach combines expert knowledge with advanced data-driven techniques to overcome limited or incomplete data. By modeling hypothetical paths using advanced conventional machine learning in combination with symbolic methods, Beyond Limits AI is better equipped to more accurately predict scenarios or outcomes and then propose optimal courses of action, yielding more confident decisions even under less-than-ideal data circumstances.
+ Increasing Prognostic Accuracy
Advanced artificial intelligence’s predictive capabilities balance out the inherent uncertainties associated with operating under inaccurate or incomplete planning models. This solution helps mitigate risks from unforeseen, potentially hazardous, workforce and asset incidents by increasing prognostic accuracy.
Beyond Limits Cognitive AI for Well Health
Beyond Limits Cognitive AI for Well Health is another great example of an artificial intelligence solution making everything easier for the industry. Keeping industrious, valuable wells in optimal health is of the utmost importance. Executing superior diagnosis and prognosis, detecting critical errors, and predicting future problems are vital capabilities for the sector.
More often than not, a narrow field of principal experts is depended on to fill the aforementioned responsibilities, make crucial modifications, and disentangle any and all concerns. However, this is not a scalable answer when each vital well demands day-to-day expert decisions and mediation. Unexpected issues from wear-and-tear or otherwise, that go undiagnosed over a span of time, have huge potential to harm equipment and processes. This innately leads to downtime, drops in production, and surging maintenance costs.
Beyond Limits’ solution is a cognitive decision support system designed to assess data-driven, physics-based material in conjunction with human expertise and best practices. It can translate domain expertise into ideal plans and recommendations to prevent formation damage and ensure well integrity by forecasting and moderating risk while helping stakeholders uphold production objectives. Such capabilities lead to pointedly reduced downtime, optimal well operation, streamlined production planning, and decreased costs.
A Partnership to Keep Your Eye on in this Era of Digital Transformation
High-performance AI fast-tracked by GPUs encourages energy companies to enhance strategies to maximize financial returns, accelerate time to decision, improve decision-maker confidence levels, and optimize well productivity while helping to reduce the environmental impact and hazards caused by drilling.
The adoption and implementation of such AI workflows represent both the vision and the outlook for the upstream oil and gas industry. More importantly, the framework built by Beyond Limits, in partnership with NVIDIA, will continue developing exponentially within this space. With applications that have use cases across the downstream sector, and the energy industry as a whole, alongside power/utilities/grid management, as well as medical/healthcare fields – and a host of others – a partnership as powerful as the combined prowess of these two technological giants has the potential to help almost any enterprise look far beyond its limits.
TAKE A DEEPER LOOK AT THE NVIDIA & BEYOND LIMITS FIELD PLANNING CASE STUDY HERE.
ORIGINALLY POSTED: 3 MAY 2021
AUTHOR: ANITA HAWSER FOR GLOBAL FINANCE
Los Angeles, CA
- The safeguards and governance frameworks that need to be put in place to ensure AI models don’t contain biases towards certain loan candidates.
- Whether Cognitive AI provides increased visibility into credit and loan candidate identification, how that works, and some of the ethical/moral implications of using AI in that context.
- How companies can scale AI across the enterprise.
“While conventional AI techniques like machine learning, deep learning or neural networks define conventional AI approaches, their Achilles’ heel, says Yonatan Hagos, Chief Product Officer at AI software-engineering company Beyond Limits, is that they cannot explain how they arrive at an answer. Hagos says Cognitive AI solutions like the one Beyond Limits uses take large data sets, then apply a layer of human knowledge and business logic to provide more accurate recommendations.”
ORIGINALLY POSTED: 9 FEBRUARY 2021
CHEN CIYAN FOR DIGITIMES
Editorial Note: This article has been translated from Traditional Chinese
AI has gradually become an emerging technology gaining popularity around the world, allowing people to realize the impact of AI solutions on their lives, whether or not those solutions are visible or readily apparent in their day-to-day lives. This popularity has also driven many new creative teams in the market to invest in this field more frequently. Chen Chenfei, an analyst at DIGITIMES Research, pointed out that as AI technology becomes more mature, the focus around AI industry development is gradually shifting to lowering the threshold for enterprise development of AI applications. Due to the insufficient degree of solution customization launched by the majority of AI companies, some innovative companies with cross-domain AI solutions have emerged to close the gaps.
Startup Beyond Limits was established in the United States in 2014 with its core AI technology developed at Caltech’s Jet Propulsion Laboratory (JPL) for NASA space missions. Beyond Limits provides enterprise-level AI solutions. Since its establishment, it has achieved success in several industries including energy, power and natural resources, manufacturing, healthcare, and more. The market covers the Americas, Asia, the Middle East, etc., and will officially enter the Taiwan market in 2020. DIGITIMES interviewed David Liu, Executive Chairman of Beyond Limits Asia Pacific, inviting him to explain the establishment process, current outlooks and future layout of Beyond Limits, as well as expectations for the Taiwan market and observations of the AI industry as a whole.
Could you please explain the establishment process of Beyond Limits?
Beyond Limits is an AI company established in the United States in 2014. Its technology is derived from NASA and its affiliated Jet Propulsion Laboratory (JPL) out of the California Institute of Technology (Caltech). The AI system that helped NASA’s Mars Curiosity Rover on its journey in 2012 was built by the Beyond Limits team. AJ Abdallat, CEO of Beyond Limits – who previously served as the Head of Commercialization Strategy for JPL and Caltech – encouraged them to export IP for commercialization in 2014.
In the beginning, NASA built a toolbox for the Mars probe. Since there is a time gap difference of 15 minutes between Mars and the Earth the probe couldn’t be operated in real-time. Under these circumstances, the transfer of data could not be carried out using only numeric AI techniques. Therefore, it was necessary to design a new solution that included an element of human-like thinking (symbolic artificial intelligence) – this is how Cognitive AI came to be.
We chose the energy industry as the first sector with which to get involved. At the time, bp, a large multinational oil group, sought to reorganize their internal operations and required a company that could help them optimize the decision-making process. After several twists and turns, I was introduced to Beyond Limits. In the past, Beyond Limits had experience with NASA probes and solved many communication and system problems in the process. After some discussion, bp believed that Beyond Limits had the right technology to help solve some of the challenges behind their decision-making processes. Subsequent cooperation also led bp to determine that our technology was a good source of support; the company then became a two-time investor in both Beyond Limits’ Series-B and Series-C funding rounds.
As for the establishment of our business model, we will develop several new products in numerous industries and fields at the outset, eventually becoming SaaS modules. That is to say, we are an industrial, enterprise-grade AI software solution provider helping companies solve decision-making process challenges.
In 2014, we discussed with bp exactly what challenges they needed solving, including oil exploration optimization, a very complicated matter. Solving the problem required the creation of an advanced AI solution. At the outset, we first looked at the business challenges bp was facing, provided a customized AI solution to help solve those problems, and finally productized the solution to make it a SaaS service.
With bp’s backing, we began by optimizing their work in upstream from oil exploration to maintaining and managing oil wells and assisting in the optimization of maintenance processes. When it comes to the refinery stage, because processes are very complicated, and in addition to optimizing those processes, we also provided solutions to support chemists in developing new formulation blends. From the refining process down to development work and final logistics, Beyond Limits provided one-stop AI solution services.
Can you briefly describe the characteristics of Beyond Limits’ AI technology?
Beyond Limits’ technology combines numeric symbolic AI, using two AI logics to process data and establish control variables, thereby creating Cognitive AI that provides explainable recommendations to human operators. This technology is also able to continuously learn and optimize using the feedback of personnel, ultimately reaching complementary/collaborative intelligence. One of the characteristics of our technical module is that it is interpretable. When our AI provides you with a suggestion, it will also provide the reasoning behind its recommendation. This is different from the “black box” AI provided by other industry players in the market. When AI cannot provide reasons behind their recommendations, it is difficult for humans to have a sense of trust in the solution.
AI is not a panacea, which is why interpretable solutions are so important. The existence of this feature can be regarded as a necessary element for establishing human trust in the system because people can analyze whether the provided advice is correct, as well as understand its logical inference. When an AI solution is transparent, it results in more certainty in the decision-making stage.
The biggest difference between the interpretable model and the black box is that the black box generally solely uses numeric AI techniques, which require a lot of data as a calculation base. In addition to data, interpretable AI also adds industry knowledge and human expertise. In addition, it can capture human actions against missing data and human thinking, making inferences based on past experience when there is missing or incomplete data, using accumulated knowledge bases to arrive at recommendations.
Presently, there are many new ventures in the market investing in the AI industry, but most of them propose solutions for specific processes. The technology Beyond Limits offers is unique in that we are a full-stack-oriented, one-stop solution provider. We are not a startup that thinks of relationships with other startups as competitive. Rather, we look forward to future cooperation with other specialty players in the space. For example, our AI could be used in coordination with OCR technology, chip makers, data platforms, and more to make on another’s technology that much stronger.
Do you have any layout plans for the edge computing market?
Beyond Limits has previous experience in edge computing. In the future, it will actively seek opportunities to cooperate with hardware manufacturers from all walks of life, potentially in the areas of 5G. Application scenarios of edge computing can be very diverse, such as maintaining the operation of various structures in the energy industry or placing solutions on sensors at the edge; edge computing is an important tool for us. It is not limited to wearable device applications but can solve many internal enterprise problems. Currently, edge computing products are still under development and we are especially interested in healthcare applications.
What is the current development status of Beyond Limits in the global market? Is there a strong demand for enterprise AI solutions?
In addition to the energy industry, there are also expansions to infrastructure, medical care, etc., with the Hong Kong office focusing more on the financial sector. The products we make will not be limited to specific markets – they will be globalized. Some financial solutions currently produced in Hong Kong will also be further promoted to the global market in the future.
The development of some AI chips and smart manufacturing solutions will be the same and we won’t just be selling to Taiwanese manufacturers. After building a good product model, we will then export it to the global market.
Beyond Limits’ Series-C funding round was finalized in 2020 for a total of US$133 million. That same year the company expanded into the United Arab Emirates (UAE) and the Asia-Pacific region simultaneously, with offices in Singapore, Hong Kong, Taiwan, and Japan. There are currently about 15 employees in the Asia-Pacific organization while the Taiwan market is already starting to recruit talent and establish initial interactions with customers as well.
AI implementation often requires education, with awareness at the C-level being the most vital. The reason is that the industry must first recognize the need and necessity of introducing AI. Therefore, in addition to AI solutions, Beyond Limits now also offers digital transformation consulting, which may also become one of the entry points for entering the Taiwan market. We will first evaluate the progress of the digital transformation within a prospective company, and then observe the parts that need to be optimized in terms of business challenges. AI technology is the core of this optimization process. At present, digital transformation is being implemented relatively quickly in the UAE market, cooperating with local tier-one players to cover logistics, medical care, insurance, and more.
Based on current observations, the market demand for enterprise-level AI solutions is very large, which is very similar to the status of past software development. In the past, software changed internal operations and operating conditions for many companies; future applications of AI will similarly change the process of corporate decision-making – this being a common mainstream trend. When observing the process of AI introduction by companies in the Asia-Pacific region it would appear that large organizations in mainland China have introduced the technology very fast as they generally have a decent understanding of how AI will impact various processes in the future.
Can you talk a little about future layouts and planning for the Taiwan market?
As far as Taiwan is concerned, we will seek cooperation with relevant industry players in the fields we have entered such as energy. In particular, Taiwan’s manufacturing industry is very strong, and its management capabilities are also very good. Therefore, we will use Industry 4.0 and smart manufacturing as the entry point to find some partners in Taiwan.
Since entering the Taiwan market in 2020, many demands have actually been observed. In addition to the process and planning of Industry 4.0, the industry should also think about future development policies. I think our services for Taiwan’s manufacturing industry will be roughly divided into several parts. The first is supply chain management, which is a very important part of manufacturing and has a direct relationship with cost; the second is design for manufacturing.
As mentioned earlier, we have an AI platform, but what we lack is expertise in several industries. For example, the importance of bp to us lies in the fact that we were previously engaged in the space industry. By cooperating with tier-one players in the energy sector, like bp, we were able to capture essential expertise and further penetrate the industry. In summary, when we enter a new market, one of our primary goals is to do so with a partner who is involved in that industry. The main task in Taiwan is to find partners in manufacturing. What this means to us is not just about developing products – these industries with long histories often have a lot of important institutional knowledge that needs to be preserved, and this is what we are doing. Taiwan has a lot of management knowledge that is worth capturing and saving. After encoding this knowledge into the AI solution, the technology can play the role of monitoring and providing advice to ensure the smooth progress of processes.
Different manufacturing industries indeed have varying processes – but there are similarities among those processes as well; our system can be placed in various manufacturing processes. The key lies in the data captured by sensors and the human decision-making process. Optimizing the decision-making process is our core work.
In addition to actively looking for smart manufacturing partners in Taiwan, it is also a goal to combine our software technology with hardware applications. Past detector experience has given us edge computing technology, which can be miniaturized and/or work with low energy consumption characteristics; we can use this existing technology to find partners. Taiwan is famous for its manufacturing industry; this will be the best field in which to create more business opportunities and partnerships.
In addition to the above two factors, another reason for entering Taiwan’s market is that talents are also very attractive. We believe that Taiwan has a very good education and cultivation system, with the quality of engineers being top of the line as well.
There are many small and medium-sized enterprises in Taiwan. The solutions proposed by Beyond Limits seem to be mainly applied to large-scale enterprises. Under such circumstances, will small and medium-sized enterprises encounter any difficulties when introducing Beyond Limits or other AI solutions?
Indeed, many of our current solutions may be more suitable for larger companies. However, even for small and medium-sized enterprises, there will still be a decision-making process, and there will also be overlooked problems or fallacies in the process. No matter whether the scale is large or small, there will always be data that needs to be retrieved using a sensor. Keeping in mind the large number of small and medium-sized enterprises in Taiwan, there are many things that we can learn from Taiwanese companies with many opportunities to expand the application scope of Beyond Limits’ AI solutions in the future.
When we enter a new industry to develop customized solutions, our first priority is co-development with industry players. In Taiwan, where there are many small and medium-sized enterprises, the efficiency of development will also be at a higher level. This will be an asset that Taiwan brings to Beyond Limits while we will help industries continue to pass on and preserve the spirit and experience of essential expertise.
ORIGINALLY POSTED: 7 MARCH 2021
WU YILUN FOR ECONOMIC DAILY
Editorial Note: This article has been translated from Traditional Chinese
Originally Posted: 12 Apirl 2021
Author: AJ Abdallat for Forbes Technology Council
Los Angeles, CA
Originally Posted: 24 & 29 March 2021
Author: JIM MAGILL FOR FORBES
Los Angeles, CA
“Another way in which AI could have helped alleviate the problems seen on the Texas grid in February would have been in providing improved long-term weather forecasts. This could have enabled the grid’s operators to determine in advance which units would have to go offline in order to protect the grid’s integrity, which in turn would have allowed electricity consumers more time to prepare for planned outages. Artificial Intelligence technology could also help match up power supply with power demand, down to a minute-by-minute basis, which would have been especially helpful to the ERCOT regulators during the crisis. Texas is in a unique situation because ERCOT isn’t connected to the western and eastern grid so there are fewer opportunities to make up for a shortfall.”
“Taking into account consumer behavior to ensure that supply matches demand as much as possible is a very large puzzle. This is a perfect application of artificial intelligence, because you can take into account many variables and be able to provide a recommendation in a very timely manner to support the changing needs of the consumer on a 15-minute basis. Using traditional physics-based modeling is inefficient or too slow.”
Originally Posted: 26 & 28 March 2021
Author: JIM MAGILL FOR FORBES
Los Angeles, CA
“Upstream oil companies are also using AI to optimize the storage of CO₂ for enhanced oil recovery. Beyond Limits, a Los Angeles-based industrial AI software company, has created an oilfield optimization application, in which captured CO₂ is pumped down a well bore to force more oil to the surface while ensuring the unwanted CO₂ remains trapped in the subsurface environment.”
“Just bringing that efficiency to the table, from exploration to bringing the first well to market, that gives not only monetary dividends, but also reduces the CO₂ footprint for every barrel of oil.”
Originally Posted: 24 March 2021
Author: OLIVIA MCCLURE for BUILT IN LA
Los Angeles, CA
Built-In-LA recently featured Beyond Limits, and our very own Leigh Yeh in a recent feature, How 3 Local Tech Leaders Use Machine Learning to Drive Innovation. The article spotlights three team members from local leading artificial intelligence/technology companies with a focus on how they are leveraging machine learning to elevate solutions, supporting customers to streamline entire processes and optimize operations at every level of their organization.
“At the end of the day, it’s great to see our products being used by customers and know that we’ve made their processes faster, more reliable and more interpretable,” said Yeh. “It’s so rewarding to build products with the power to make a difference.”
READ THE REST OF BUILT-IN-LA’S SPOTLIGHT HERE.
Originally Posted: 9 February 2021
Los Angeles, CA
“Indeed, AI has the potential to revolutionize the power generation domain, combining historical and real-time operational datasets with embedded deep subject matter expertise to result in explainable, trusted recommendations. Such accessibility is designed to maximize the efficiency and reliability of operations while simultaneously minimizing risk, meeting power generation demands, and achieving financial objectives.”
Originally Posted: 7 February 2021
Author: Darrell Proctor for POWER magazine
Los Angeles, CA
- How can the trend of decentralized power generation benefit from AI?
- How can AI be used in power trading, with regard to forecasts, etc.?
- Are there specific challenges for power plant operators that AI and ML can help solve?
Originally Posted: 11 January 2021
Author: Scott Matteson for Smart Industry
Los Angeles, CA
“AI is playing a critical role in operational efficiency across the energy value chain to optimize resource production, democratize domain expert knowledge, and increase value while reducing environmental risk. In the oil and gas sector, AI is enabling companies to optimize their production and improve asset maintenance in many ways, such as pinpointing drilling opportunities, inspecting pipes for problems with self-navigating robots, and predicting equipment wear and tear.”