NOV opens applications for unique energy tech startup pilot program in Houston

calling all innovators

The five-month program establishes a significant relationship between the 20 selected startups and NOV, beginning with paid pilot programs. Photo via NOV.com

Houston-based NOV is launching a new growth-stage startup accelerator focused on the upstream oil and gas industry.

NOV, a provider of oil and gas drilling and production operations equipment, has announced its new NOV Supernova Accelerator in collaboration with VentureBuilder, a consulting firm, investor, and accelerator program operator led by a group of Houston innovators.

Applications to the program are open online, and the deadline to apply is July 7. Specifically, NOV is looking for companies working on solutions in data management and analytics, operational efficiency, HSE monitoring, predictive maintenance, and digital twins.

The five-month program establishes a significant relationship between the 20 selected startups and NOV, beginning with paid pilot programs.

"This is not a traditional startup accelerator. This is often a first-client relationship to help disruptive startups refine product-market fit and creatively solve our pressing enterprise problems," reads the program's website.

Selected startups will have direct access to NOV's team and resources. The program will require companies to spend one week per month in person at NOV headquarters in Houston and will provide support surrounding several themes, including go-to-market strategy, pitch practice, and more.

“The NOV Supernova Accelerator offers a strategic approach where the company collaborates with startups in a vendor-client relationship to address specific business needs," says Billy Grandy, general partner of VentureBuilder.vc, in a statement. "Unlike mergers and acquisitions, the venture client model allows corporations like NOV to quickly test and implement new technologies without committing to an acquisition or risking significant investment.”

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UH Professor Vedhus Hoskere received a three-year, $505,286 grant from TxDOT for a bridge digitization project. Photo via uh.edu

Houston researcher earns $500,000 grant to tap into digital twin tech for bridge safety

transportation

A University of Houston professor has received a grant from the Texas Department of Transportation (TxDOT) to improve the efficiency and effectiveness of how bridges are inspected in the state.

The $505,286 grant will support the project of Vedhus Hoskere, assistant professor in the Civil and Environmental Engineering Department, over three years. The project, “Development of Digital Twins for Texas Bridges,” will look at how to use drones, cameras, sensors and AI to support Texas' bridge maintenance programs.

“To put this data in context, we create a 3D digital representation of these bridges, called digital twins,” Hoskere said in a statement. “Then, we use artificial intelligence methods to help us find and quantify problems to be concerned about. We’re particularly interested in any structural problems that we can identify - these digital twins help us monitor changes over time and keep a close eye on the bridge. The digital twins can be tremendously useful for the planning and management of our aging bridge infrastructure so that limited taxpayer resources are properly utilized.”

The project began in September and will continue through August 2026. Hoskere is joined on the project by Craig Glennie, the Hugh Roy and Lillie Cranz Cullen Distinguished Chair at Cullen College and director of the National Center for Airborne Laser Mapping, as the project’s co-principal investigator.

According to Hoskere, the project will have implications for Texas's 55,000 bridges (more than twice as many as any other state in the country), which need to be inspected every two years.

Outside of Texas, Hoskere says the project will have international impact on digital twin research. Hoskere chairs a sub-task group of the International Association for Bridge and Structural Engineering (IABSE).

“Our international efforts align closely with this project’s goals and the insights gained globally will enhance our work in Texas while our research at UH contributes to advancing bridge digitization worldwide,” he said. “We have been researching developing digital twins for inspections and management of various infrastructure assets over the past 8 years. This project provides us an opportunity to leverage our expertise to help TxDOT achieve their goals while also advancing the science and practice of better developing these digital twins.”

Last year another UH team earned a $750,000 grant from the National Science Foundation for a practical, Texas-focused project that uses AI. The team was backed by the NSF's Convergence Accelerator for its project to help food-insecure Texans and eliminate inefficiencies within the food charity system.

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This article originally ran on InnovationMap.

Nick Purday, IT director of emerging digital technology for ConocoPhillips, presented at the Reuters Events Data-Driven Oil and Gas Conference 2023 to help dispel any myths about digital twins. Photo courtesy of Shuttershock.

The secret to unlocking efficiency for the energy transition? Data management

SAVING THE BEST FOR LAST

As Nick Purday, IT director of emerging digital technology for ConocoPhillips, began his presentation at the Reuters Events Data-Driven Oil and Gas Conference 2023 in Houston yesterday, he lamented at missing the opportunity to dispel any myths about digital twins given his second-to-last time slot of the conference.

He may have sold himself short.

No less than a hush fell over the crowd as Purday described one of the more challenging applications of digital twins his team tackled late last year. Purday explained, “The large diagram [up there], that’s two trains from our LNG facility. How long did that take to build? We built that one in a month.”

It’s been years since an upstream oil and gas audience has gasped, but Purday swept the crowd with admiration for the swift, arduous task undertaken by his team.

He then addressed the well-known balance of good/fast/cheap in a rare glimpse under the hood of project planning for such novel technology. “As soon as you move into remote visualization applications – think Alaska, think Norway – then you’re going to get a pretty good return on your investment. Think 3-to-1,” Purday explains. “As you would expect, those simulation digital twins, those are the ones where you get huge value. Optimizing the energy requirements of an LNG facility – huge value associated with that.

“Independently, Forrester did some work recently and came up with a 4-to-1 return, so that fits exactly with our data set,” Purday continued before casually bringing up the foundation for their successful effort.

“If you’ve got good data, then it doesn’t take that long and you can do these pretty effectively,” Purday stated plainly.

Another wave of awe rippled across the room.

In an earlier panel session, Nathan McMahan, data strategy chief at CoP, commented on the shared responsibility model for data in the industry. “When I talked to a lot of people across the organization, three common themes commonly filtered up: What’s the visibility, access, and trust of data?” McMahan observed.

Strong data governance stretches across the organization, but the Wells team, responsible for drilling and completions activity, stood out to McMahan with its approach to data governance.

“They had taken ownership of [the] data and partnered with business units across the globe to standardize best practices between some of the tools and data ingestion methods, even work with suppliers and contractors, [to demonstrate] our expectations for how we take data,” McMahan explained. “They even went a step further to bring an IT resource onto their floor and start to create roles of the owners and the stewards and the custodians of the data. They really laid that good foundation and built upon that with some of the outcomes they wanted to achieve with machine learning techniques and those sorts of things.“

The key, McMahan concluded, is making the “janitorial effort [of] cleaning up data sustainable… and fun.”

The sentiment of fun continued in Purday's late afternoon presentation as he explained how the application went viral upon sharing it with 1 or 2 testers, crashing the email of the lead developer responsible for managing the model as he was flooded with questions and kudos.

Digital twin applications significantly reduce the carbon footprint created by sending personnel to triage onsite concerns for LNG, upstream, and refining facilities in addition to streamlining processes and enabling tremendous savings. The application Purday described allowed his team to discover an issue previously only resolved by flying someone to a remote location where they would likely spend days testing and analyzing the area to diagnose the problem.

The digital twin found the issue in 10 minutes, and the on-site team resolved the problem within the day.

The LNG operations team now consistently starts their day with a bit of a spark, using the digital twin during morning meetings to help with planning and predictive maintenance.

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4 Houston researchers awarded projects in DOE's Genesis Mission

federal funding

The U.S. Department of Energy has named the nearly 300 projects selected under the Trump Administration's Genesis Mission, which aims to address some of the largest science and technology challenges in the country. The group features four projects from Houston universities and companies.

The initiative aims to unite government, industry, academia and philanthropy to lead to breakthroughs in energy, scientific discovery and national security, according to a release.

The selected projects feature 87 led by DOE and National Nuclear Security Administration (NNSA) National Laboratories, 168 led by universities, 19 led by companies and 4 led by nonprofit organizations—totalling 342 participating institutions.

“America has no shortage of bold ideas or talented scientists, and the response to the Genesis Mission proves that,” U.S. Secretary of Energy Chris Wright said in a news release. “The 278 projects selected today represent the very best of our nation’s scientific enterprise. The remarkable number of high-quality proposals we received demonstrates that America’s innovation pipeline is strong, and it points to even greater opportunities for future investment and continued expansion of the Genesis Mission portfolio.”

Twelve Texas-based projects were selected among the 278. The Houston projects and their researchers include:

Caroline Ajo-Franklin

Ajo-Franklin recieved a Phase I grant for her project "Predictive AI to Map Point Mutation Effects on Protein Function: Measurement and Biosynthesis of Isoprenoids." Ajo-Franklin is a professor of biosciences at Rice University, a CPRIT Scholar in Cancer Research and member of the Rice Synthetic Biology Institute. The project aims to accelerate the engineering of microbes that can produce isoprenoids, which are natural compounds that could replace petroleum-derived fuels, solvents and materials.

“This project creates a continuous feedback loop in which AI guides experiments and each experiment generates more detailed data to better hone the AI model,” Ajo-Franklin said in a news release. “In addition, it demonstrates the extraordinary star power Rice has recruited in protein engineering and synthetic biology.”

Anastasios Kyrillidis

Kyrillidis recived a Phase I grant for his project "Cracking the VQA Optimization Bottleneck: AI Methods for Quantum Chemistry and Materials." Kyrillidis is the Noah Harding Associate Professor of Computer Science at Rice and a member of the Ken Kennedy Institute. The project aims to develop AI tools to resolve bottlenecks in quantum computing for chemistry and materials research.

“Our goal is to replace fragile, hand-tuned optimization methods with intelligent systems that can learn from quantum computations while still operating within frameworks that provide strong mathematical guarantees,” Kyrillidis added in the release.

Myoungkyu Lee

Lee received a nearly $750,000 Phase I grant for his project "Physics-Informed AI Surrogates for Turbulent Forced Convection in Energy System." Lee is an assistant professor of mechanical aerospace engineering at the University of Houston. Lee will collaborate with researchers from Lawrence Livermore National Laboratory and University of Pennsylvania on the project and develop artificial intelligence to accelerate the design of materials for advanced nuclear fission and fusion reactors.

“The goal is to develop a tool that runs much faster than today’s most detailed simulations while keeping errors small,” Lee said in a news release. “If successful, the approach could support better heat-transfer predictions for molten-salt reactor design and provide a starting point for studying heat removal in fusion blankets. This is one contribution among many toward reliable, carbon-free energy.”

Amit Padhi

Padhi recieved a grant for his project "Probabilistic Inference of Subsurface Fracture Connectivity for Stimulation Control with Physics-Informed AI." Padhi is a scientific advisor for Halliburton.

The DOE first called for applications for the Genesis Mission in March. At the time, the DOE shared that it would grant approximately $293 million to the selected teams via Phase I awards, ranging from $500,000 to $750,000 for nine-month project periods, and Phase II awards, for $6 million to $15 million over a three-year project period.

Since then, however, the initiative has grown with 15 federal agencies now granting research awards and funding opportunities under the Genesis umbrella. The White House announced this week that it had secured more than $5 billion in federal commitments to expand the initiative.

SLB teams with Liberty Energy on modular power for AI data centers

ai alliance

Houston-headquartered SLB and Denver-based Liberty Energy Inc. announced a strategic agreement this month to support the rapid growth of new data center capacity.

Under the agreement, SLB will supply modular data center infrastructure and oversee large-scale execution, while Liberty will provide modular power generation systems and behind-the-meter power management technology for developers looking to add capacity. According to Reuters, the power will come from natural gas generation.

“The bottleneck in AI infrastructure is no longer just compute. It is the ability to deliver infrastructure and power on the timelines the market now demands,” Gavin Rennick, president of SLB’s New Energy and Industrial business, said in a news release. “By bringing together complementary infrastructure and power capabilities, we will help developers accelerate deployment of new data center capacity.”

The companies seek to specifically offer the modular technologies in areas without traditional grid connections or where grid capacity is limited.

They also aim to improve the "efficiency, flexibility and environmental performance of future data center energy systems," potentially through solutions like hybrid power systems and digital energy management, according to the news release.

Goldman Sachs estimates that U.S. data center capacity will more than double from 31 gigawatts in 2025 to 66 gigawatts in 2027. Other reports predict that Houston and Texas will be home to a significant portion of the data center boom, with capacity in the city and the state also expected to double in the next few years.

“The scale and complexity of AI energy infrastructure is fundamentally changing how power systems are built and deployed,” Ron Gusek, CEO of Liberty Energy, added in the release. “Liberty’s comprehensive power service platform is engineered to meet this transition, as customers increasingly prioritize tailored, integrated solutions. Building on our long-standing relationship with SLB, we are excited to bring power solutions that address immediate capacity constraints while supporting the next generation of energy systems.”

SLB sold its onshore hydraulic fracturing business in the United States and Canada to Liberty Energy in December 2020 in exchange for a 37 percent equity interest in the company.

New Rice study details how carbon capture could reduce AI data center emissions

by the numbers

A new study out of Rice University points to carbon capture and storage methods as pivotal solutions to addressing emissions from AI-driven data centers.

The study was authored by Hon Chung Lau, an adjunct professor in the Department of Chemical and Biomolecular Engineering at Rice University and founder of Low Carbon Energies LLC, and Steve C. Tsai, an energy transition consultant at Low Carbon Energies LLC, and published in the journal Energy & Fuels.

According to the study, U.S. data center power capacity could more than quadruple in five years, growing from 40 gigawatts in 2025 to 169 gigawatts by 2030. Without proper regulation of emissions, the report estimates that carbon dioxide produced by fossil-fuel power plants supplying electricity to data centers could grow at the same scale, increasing from 90 million metric tons to more than 404 million metric tons over the same time period.

The researchers analyzed publicly available data on announced U.S. data centers, which included energy sources, locations, and projected power capacity before estimating data center-related carbon emissions based on each state’s electricity mix. From there, they examined whether those emissions could be captured and stored underground in saline aquifers.

The team estimates that 34 states have enough saline aquifer storage capacity to store more than 100 years of projected data center-related carbon dioxide emissions beyond 2030. Aquifers could store an estimated 59 million metric tons of data center-related carbon dioxide, or about 66 percent of the sector’s emissions in 2025. However, that calculation could grow to 299 million metric tons, or about 74 percent of projected data center-related emissions by 2030.

The researchers found that more than 90 percent of data center-related carbon dioxide emissions could potentially be mitigated through carbon capture and storage when out-of-state storage options are included, even though they note that carbon capture isn’t the only solution.

“It does show that the geology exists to make a meaningful impact, especially in states where data center growth is strongest,” Lau said in a news release.

Rapid growth in states including Texas, Virginia, Pennsylvania, Ohio, Arizona, Colorado, Utah and Illinois was considered in the study. According to the findings, Texas would need to add 25 gigawatts of power capacity by 2030 to meet projected data center demand, as data centers require reliable electricity 24/7.

“Data centers are becoming one of the defining energy challenges of the AI era,” Lau added in the news release. “The question is not only whether we can build enough computing infrastructure, but whether we can power it in a way that is reliable, affordable and compatible with decarbonization goals.”

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