ORIGINALLY PUBLISHED: 27 SEPTEMBER 2021
AUTHOR: SCOTT CLARK FOR CMSWIRE
Los Angeles, CA
“The next frontier of AI is the growth and improvements that will happen in Explainable AI technologies. They will become more agile, flexible, and intelligent when deployed across a variety of new industries. XAI is becoming more human-centric in its coding and design. We’ve moved beyond deep learning techniques to embed human knowledge and experiences into the AI algorithms, allowing for more complex decision-making to solve never-seen-before problems — those problems without historical data or references. Machine learning techniques equipped with encoded human knowledge allow for AI that lets users edit their knowledge base even after it’s been deployed. As it learns by interacting with more problems, data, and domain experts, the systems will become significantly more flexible and intelligent. With XAI, the possibilities are truly endless.”
ORIGINALLY PUBLISHED: AUGUST 2021
AUTHOR: VIDYASAGAR ANANTHAN & OTHERS FOR OILFIELD TECHNOLOGY
Los Angeles, CA
“Appraising the preservation of hydrocarbons within discovery fields is a critical aspect during exploration. This involves detailed seismic surveys, geostatistical analyses and subsequent high-resolution simulations involving geological models or digital twins representing the natural subsurface strata. In order to understand the practical production limit of a field, it is necessary to find the best possible drilling locations, trajectories and control strategies given practical constraints – constituting the field planning process. Optimal placement and control of wells within such a greenfield development is a sequential decision-making problem of spatiotemporal nature.”
Originally Posted: 24 August 2021
Author: Leonard Lee
Los Angeles, CA
“Intentional AI implementation and smart city technologies are rapidly becoming recognized as the not-so-secret ingredient helping urban regions accomplish the initiative of lowering greenhouse gas emissions by up to 270k kilotons, creating 1.2M new jobs, and generating cost-of-living savings between US$9bn and US$16bn.”
Originally Posted: 9 September 2021
Author: AJ Abdallat for Smart Industry Forum
Los Angeles, CA
“When it comes to energy innovation, artificial-intelligence solutions are leading the pack as organizations chart out their digital-transformation blueprints. Acceptance and execution shouldn’t scare away any company; there are those that will dive in headfirst and reap the rewards.”
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: 12 JULY 2021
Author: Ken Silverstein for Forbes
Los Angeles, CA
“Nothing we build is designed to replace a person,” says Michael Krause, Senior Manager for Oil and Gas at Beyond Limits. “People need to make decisions. But AI can remove that mundane component of their work and allow managers to focus on the value-added part. There are millions of potential strategies for humans to pursue — each one a function of intelligence and experience.”
Originally Posted: 27 JULY 2021
Author: AJ ABDALLAT
Los Angeles, CA
“AI is adept at helping with operate-to-plan objectives, scheduling optimal combinations of renewable and conventional power supplies as necessary. This is because AI can take numerous variables into account, then provide timely recommendations that support changing consumer needs while simultaneously managing opt-in demand-response programs that cut demand during high-load periods using alert systems and/or shutdowns.”
Originally Posted: 21 JULY 2021
Author: JEFFERY BURT FOR THE NEXT PLATFORM
Los Angeles, CA
“For the practices that you have relied on a human expert to come up with a framework and [to] solve a problem, it is important for them that whatever system you build is honoring that and can digest that. It’s not only data, it’s also that knowledge that’s human. How do we incorporate and then bring this together? For example, how do you make the knowledge that your engineer learned about from the data or how do you use the physics as a constraint for your AI? It’s an interesting field.”
“At Beyond Limits, Farhadi has spearheaded a new approach to optimizer development that leverages some of the latest breakthroughs in reinforcement learning and deep convolutional neural networks. Deep learning approaches are able to work with, and learn from, much larger pools of data than traditional machine learning algorithms.”
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.”