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Houston energy expert asks: Who pays when AI outruns the power grid?

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Scotty Nyquist discuss the growth in AI data centers and the strain on the system. Photo via HARC report

For most of the past 20 years, U.S. electricity policy relied on predictable trends in demand. Electricity use, in most regions, increased gradually, forecasts were stable, and utilities adjusted the system in small steps. Power plants, transmission lines, and substations were generally added to reflect shifts in load, rather than growth, and costs were recovered through modest adjustments to customer bills.

Growth in AI data centers has disrupted this model. A single facility can add as much electricity demand as a small town. That demand comes all at once, runs continuously, and has little tolerance for outages. If electricity service drops even briefly, computation stops, and services shut down. Ironically, data centers need reliable service, a point that their emergence is driving concern around for the rest of the grid.

What the numbers say

The International Energy Agency projects global electricity consumption from data centers to double by 2030, reaching roughly 945 TWh, nearly 3 percent of global electricity demand, with consumption growing about 15 percent per year this decade. McKinsey projects that U.S. data center demand alone could grow 20–25 percent per year, with global capacity demand more than tripling by 2030.

After years of roughly 0.5 percent annual demand growth, many forecasts now place total U.S. electricity demand growth closer to 2–3 percent per year through the mid-2030s, with much higher growth in specific regions. In Texas, some forecasters are saying electricity demand could double over the next five years, a staggering 10 percent per year growth rate. What sounds incremental on paper translates into a major challenge on the ground. Meeting this pace of growth is estimated to require $250–$300 billion per year in grid investment, about double what the system has been absorbing.

Where the system starts to strain

The strain appears first in the interconnection queue. It shows up as long waits, backlogs, and delays for connecting new loads and new generation.

Before new generators or large load customers can be connected, a study is required to assess their impact on the grid, whether it can physically handle the added load, and whether upgrades are required. With AI-driven data centers, utilities face far more connection requests than they can realistically support. In ERCOT, large-load interconnection requests exceed 200 gigawatts, most tied to data centers. That amount exceeds historical norms, and it is several times larger than what can be practically studied or built in the near term.

To be clear, public utility commissions are required to study these requests because they must manage system capabilities to ensure minimal disruption. This means engineers spend time evaluating projects that may never be built, while other more commercially viable projects may wait longer for approvals. This extends timelines and makes infrastructure planning less reliable.

Why policymakers are rethinking the rules

Utilities and their regulators must decide how much generation, transmission, and substation capacity to build years before it comes online. Those decisions are based on expected demand at the time projects are approved. When it comes to data centers, by the time infrastructure is completed, they may end up deploying newer, more efficient chips that use less power than originally assumed. This can result in grid infrastructure built for a higher load than what actually materializes, leaving excess capacity that still must be paid for through system-wide rates.

That’s the central dilemma. If utilities build too little capacity, the system operates with less reserve margin. During periods of grid stress, operators have fewer options, increasing the likelihood of curtailments or outages. However, if utilities build too much, customers may be asked to pay for infrastructure that is not fully used.

In response, policymakers are adjusting the rules. In some regions, regulators are moving toward bring-your-own-power approaches that require large data centers to supply or fund part of the capacity needed to serve them or reduce demand during system stress. At the federal level, permitting reforms tied to datacenter infrastructure increasingly treat electricity as a strategic economic input.

As Ken Medlock, senior director at the Baker Institute Center for Energy Studies (CES), explains:

“Many of the planned data centers are now also adding behind-the-meter options to their development plans because they do not anticipate being able to manage their needs solely from the grid, and they certainly cannot do so with only intermittent power sources.”

Behind-the-meter (BTM) refers to power that a consumer controls on its side of the utility meter, such as on-site gas generation or a dedicated power plant. These resources allow data centers to keep operating during grid-related service. Most facilities remain connected to the grid, but the backup BTM generation serves as insurance for operating their core business.

This shifts responsibility. Utilities traditionally manage reliability across all customers by maintaining an operating reserve margin, or spare capacity. Increasingly, large-load customers manage part of their own electricity reliability needs, which changes how infrastructure is planned and how risk is distributed.

Bottom line

AI-driven load growth is arriving faster and in more concentrated places than the power system was built to accommodate. Utilities and regulators are being forced to make decisions sooner than planned about where to build, how fast to build, and which customers get priority when capacity is limited. The effects extend beyond data centers, showing up in system costs, reliability margins, competition for grid access, and pressure on communities and industries that depend on affordable and dependable power. The issue is not whether electricity can be generated, but how the costs and risks of rapid demand growth are distributed as the system tries to keep up. How regulators balance these decisions will determine who pays as AI demand outruns the power grid.

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Scott Nyquist is a senior advisor at McKinsey & Company and vice chairman, Houston Energy Transition Initiative of the Greater Houston Partnership. The views expressed herein are Nyquist's own and not those of McKinsey & Company or of the Greater Houston Partnership. This article originally appeared on LinkedIn.

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Collide has rolled out RIGGS, a large language model for energy professionals. Photo via Getty Images

Houston AI startup rolls out platform to reshape oil and gas workflows

AI for energy

Houston-based Collide is looking to solve AI issues in the energy industry from within.

Co-founded by former oil roughneck Collin McLelland, the company has developed AI software for operators and field teams, shaped by firsthand oilfield experience. Its AI-native platform “retrieves and synthesizes data from authoritative sources to deliver accurate, cited, and energy-focused insights to oil and gas professionals,” according to the company.

“Oil and gas has a graveyard full of technology that was technically impressive and operationally useless,” McLelland tells Energy Capital. “The reason is almost always the same: the people who built it didn't understand what they were actually solving for. When you're an outsider, you see workflows and try to automate them. When you're an insider, you understand why those workflows exist—the regulatory constraints, the physical realities, the liability concerns, the trust dynamics between operators and service companies.”

Collide’s large language model, known as RIGGS, performed well in recent benchmarking results when taking a standardized petroleum engineering (SPE) exam, the company reports. The exam assesses understanding from conceptual terminology to complex mathematical problem-solving.

According to Collide, RIGGS achieved a score of 67.5 percent on a 40-question subset of the SPE petroleum engineering exam, outperforming other large language models like Grok 4 (62.5 percent), Claude Sonnet 4.5 (52.5 percent) and GPT 5.1 (4 percent).

RIGGS completed the test in 15 minutes, while Grok took two hours. Collide hopes over the next few months, RIGGS will receive a score between 75 percent to 80 percent accuracy.

The software could potentially help oil and gas companies produce accurate outputs and automate trivial workflows, which can open up valuable time for engineers and teams to work on other pressing matters, according to McLelland.

“Collide exists because we sat in those seats — we were the engineers, the operators, the field guys,” he says. ”RIGGS scoring higher on the PE exam versus the frontier labs isn't a party trick. It's evidence that the model understands petroleum engineering the way a petroleum engineer does, because it was built by people who do.”

RIGGS was trained on Collide’s Spindletop hardware and is supported by a vast library of information, as well as a reasoning engine and validation layer that uses logic to solve problems.

“Longer term, we see RIGGS as the intelligence layer that sits underneath every operator's workflow — not a chatbot you open in a browser, but something embedded in the tools engineers already use,” McLelland says. “The goal is to give every engineer the knowledge and pattern recognition of a 30-year veteran, on demand."

According to McLelland, Collide is already building toward reservoir analysis and production optimization, automated regulatory compliance (Railroad Commission filings, W-10s, G-10s), workover report generation, and engineering decision support in the field for near-term use cases. In March, Collide and Texas-based oil and gas operator Winn Resources announced a collaboration to automate the time-intensive process of filing monthly W-10 and G-10 forms with the Texas Railroad Commission, completing what’s normally a multi-hour task in under 30 minutes. Collide reports that Winn’s infrastructure now automates regulatory filings and provides real-time visibility into data gaps, which has reduced processing time by over 95 percent.

“Before Collide, I'd spend hours manually keying in filings,” Buck Crum, director of operations, said in a news release. “(In March), we had 50 wells to file and I was done in 20 minutes. It does the majority of the heavy lifting while keeping me in control. That human-in-the-loop approach saves meaningful time and gives us greater confidence in our compliance and reporting.”

Collide was originally launched by Houston media organization Digital Wildcatters as “a professional network and digital community for technical discussions and knowledge sharing.” After raising $5 million in seed funding led by Houston’s Mercury Fund last year, the company said it would shift its focus to rolling out its enterprise-level, AI-enabled solution.
This are heating up for Fervo. Photo via Fervo Energy

Fervo taps new geothermal site and more energy transition news to know

Trending Topics

Editor's note: We're looking back at the biggest energy transition headlines from the second half of February, including Fervo's hottest well to date and the future of data centers in Texas. Below are the five most-read EnergyCapital stories from February 16-28, 2026.

1. Fervo taps into its hottest-ever geothermal reservoir

Fervo Energy has unlocked multigigawatt potential from a new geothermal energy site. Photo courtesy Fervo Energy.

Things are heating up at Houston-based geothermal power company Fervo Energy. Fervo recently drilled its hottest well so far at a new geothermal site in western Utah. Fewer than 11 days of drilling more than 11,000 feet deep at Project Blanford showed temperatures above 555 degrees Fahrenheit, which exceeds requirements for commercial viability. Fervo used proprietary AI-driven analytics for the test. Continue reading.

2. Texas could topple Virginia as biggest data-center market by 2030, JLL report says

A new report shows the role Texas could play as the data-center sector enters "hyperdrive." Photo via JLL.com.

Everything’s bigger in Texas, they say—and that phrase now applies to the state’s growing data-center presence. A new report from commercial real estate services provider JLL says Texas could overtake Northern Virginia as the world’s largest data-center market by 2030. Northern Virginia is a longtime holder of that title. Continue reading.

3. Texas claims No. 1 spot on new energy resilience report

Texas outpaced the rest of the country in a new energy resilience report, despite grid challenges and rising AI demand. Photo courtesy of ERCOT

A new report by mineral group Texas Royalty Brokers ranks Texas as the No. 1 most energy-resilient state. The study focused on four main sources of electricity in hydroelectric dams, natural gas plants, nuclear reactors and petroleum facilities. Each state was given an Energy Resilience Score based on size and diversity of its power infrastructure, energy production and affordability for residents. Continue reading.

4. Texas' oil and gas foundation could boost its geothermal future, UH says

A new UH white paper says that Texas is poised to lead advanced geothermal due to its oil and gas skills and capacity. Photo via UH.edu.

Equipped with the proper policies and investments, Texas could capitalize on its oil and gas infrastructure and expertise to lead the U.S. in development of advanced geothermal power, a new University of Houston white paper says. Continue reading.

5. HETI leader reflects on four years focused on the energy transition

Jane Stricker reflects on four years at HETI. Courtesy photo

It’s hard to believe only four years have passed since I joined the Greater Houston Partnership to lead the Houston Energy Transition Initiative. We talk about COVID years feeling simultaneously like just yesterday and a lifetime ago, and my time at HETI feels quite similar. The energy and climate landscape has evolved dramatically over the last few years, but one constant has endured…Houston remains at the heart of the energy industry. Continue reading.

Merab Momen, founder of AI CTO Services. Courtesy Photo

How this Houston expert helps startups turn AI hype into real impact

now streaming

Artificial intelligence is now everywhere. It is mentioned in every startup pitch deck, and every corporate roadmap claims to use it. However, many early-stage businesses struggle with the simple question, “What does AI actually mean for my business?”

In a recent podcast episode of EnergyTech Startups, Merab Momen, founder of AI CTO Services and a long time AI practitioner, explains why most founders misunderstand AI, how startups can practically apply it and why Houston is quietly becoming a serious hub for AI-driven innovation.

Filling the AI Leadership Gap

Merab’s career has spanned decades of technology transitions. He worked on neutral networks in the 1990s, constructed computer vision systems long before they were common, and helped install AI solutions inside huge industrial companies. However, he noticed a huge problem when generative AI started to explode into the mainstream-The requirement of a real partner by the founders for AI integration but inability to rely on a full-time CTO and project-based consultants.

“I really needed something which is much more engaging where I can give that partner-level advice to the founders,” he said. By giving firms on-demand access to high-level AI knowledge and expertise, his methodology enables them to analyse tools, steer clear of cost blunders and eventually transition to a permanent technology leader when the time is right.

AI is Older than Most People Think

Despite its recent rise in popularity, AI is nothing new. AI actually began in the 1950s. Merab in his conversation explained how he worked on his first AI project back in the year 1996 that worked perfectly, but the processing power wasn’t just there to make it practical. He continued how he utilized the swarm intelligence models to optimize supply chains, now referred to as MLPOs and data engineering.

From Language Models to Physical World

Much of the public conversation about AI revolves around chatbots and text generation. But Merab sees far greater potential in AI’s interaction with the physical world, especially in industrial settings. He emphasized edge computing and vision language models (VLMs) as significant advances in manufacturing and energy. This physical shift is opening doors for new opportunities for robotics, automated inspections, and industrial safety applications. Merab added that Houston is uniquely positioned for this transition.

Why Houston has an AI Advantage

Silicon Valley may dominate the AI headlines, but Merab believes Houston’s advantage lies beneath the surface. The city doesn’t lag in AI utilization; it just operates in industries where results show differently.

Machine learning isn’t new to Houston’s core industries. Energy companies, manufacturers, logistics providers, and healthcare systems have been using advanced analytics for decades. The difference lies in them innovating in industrial sectors rather than consumer technology.

What’s Next

With the AI CTO Services growing, Merab is working with startups across industries to deploy AI in practical, business-first ways.

He is more interested in assisting founders in finding answers to critical issues than following new trends.

For Houston’s energy and climate tech community, it needs to transform AI enthusiasm into real-world impact.

Listen to the full conversation with Mehrab Momin on the Energy Tech Startups Podcast to learn more.

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Energy Tech Startups Podcast is hosted by Jason Ethier and Nada Ahmed. It delves into Houston's pivotal role in the energy transition, spotlighting entrepreneurs and industry leaders shaping a low-carbon future.


A new report shows the role Texas could play as the data-center sector enters "hyperdrive." Photo via JLL.com.

Texas could topple Virginia as biggest data-center market by 2030, JLL report says

data analysis

Everything’s bigger in Texas, they say—and that phrase now applies to the state’s growing data-center presence.

A new report from commercial real estate services provider JLL says Texas could overtake Northern Virginia as the world’s largest data-center market by 2030. Northern Virginia is a longtime holder of that title.

What’s driving Texas’ increasingly larger role in the data-center market? The key factor is artificial intelligence.

Companies like Google and Microsoft need more energy-hungry data centers to power AI innovations. In a 2023 article, Forbes explained that AI models consume a lot of energy because of the massive amount of data used to train them, as well as the complexity of those models and the rising volume of tasks assigned to AI.

“The data-center sector has officially entered hyperdrive,” Andy Cvengros, executive managing director at JLL and co-leader of its U.S. data-center business, said in the report. “Record-low vacancy sustained over two consecutive years provides compelling evidence against bubble concerns, especially when nearly all our massive construction pipeline is already pre-committed by investment-grade tenants.”

Dallas-Fort Worth has long dominated the Texas data-center market. But in recent years, West Texas has emerged as a popular territory for building data-center campuses, thanks in large part to an abundance of land and energy. Nearly two-thirds of data-center construction underway now is happening in “frontier markets” like West Texas, Ohio, Tennessee and Wisconsin, the JLL report says.

Northern Virginia, the current data-center champ in the U.S., boasted a data-center market with 6,315 megawatts of capacity at the end of 2025, the report says. That compares with 2,423 megawatts in Dallas-Fort Worth, 1,700 megawatts in the Austin-San Antonio corridor, 200 megawatts in West Texas, and 164 megawatts in Houston.

UH researchers have developed a thin film that could allow AI chips to run cooler and faster. Photo courtesy University of Houston.

Houston researchers develop energy-efficient film for AI chips

AI research

A team of researchers at the University of Houston has developed an innovative thin-film material that they believe will make AI devices faster and more energy efficient.

AI data centers consume massive amounts of electricity and use large cooling systems to operate, adding a strain on overall energy consumption.

“AI has made our energy needs explode,” Alamgir Karim, Dow Chair and Welch Foundation Professor at the William A. Brookshire Department of Chemical and Biomolecular Engineering at UH, explained in a news release. “Many AI data centers employ vast cooling systems that consume large amounts of electricity to keep the thousands of servers with integrated circuit chips running optimally at low temperatures to maintain high data processing speed, have shorter response time and extend chip lifetime.”

In a report recently published in ACS Nano, Karim and a team of researchers introduced a specialized two-dimensional thin film dielectric, or electric insulator. The film, which does not store electricity, could be used to replace traditional, heat-generating components in integrated circuit chips, which are essential hardware powering AI.

The thinner film material aims to reduce the significant energy cost and heat produced by the high-performance computing necessary for AI.

Karim and his former doctoral student, Maninderjeet Singh, used Nobel prize-winning organic framework materials to develop the film. Singh, now a postdoctoral researcher at Columbia University, developed the materials during his doctoral training at UH, along with Devin Shaffer, a UH professor of civil engineering, and doctoral student Erin Schroeder.

Their study shows that dielectrics with high permittivity (high-k) store more electrical energy and dissipate more energy as heat than those with low-k materials. Karim focused on low-k materials made from light elements, like carbon, that would allow chips to run cooler and faster.

The team then created new materials with carbon and other light elements, forming covalently bonded sheetlike films with highly porous crystalline structures using a process known as synthetic interfacial polymerization. Then they studied their electronic properties and applications in devices.

According to the report, the film was suitable for high-voltage, high-power devices while maintaining thermal stability at elevated operating temperatures.

“These next-generation materials are expected to boost the performance of AI and conventional electronics devices significantly,” Singh added in the release.

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This article originally appeared on our sister site, InnovationMap.

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Greentown names 5 climatech startups to manufacturing accelerator

Catalyst Cohort

Greentown Labs has named five climatech startups to its Go Make 2026 cohort, including one from Houston.

Greentown Go Make 2026 is in partnership with Shell Catalysts & Technologies and Technip Energies. Startups will be able to collaborate with leadership from Shell and Technip and have opportunities to work directly with their process engineering teams and develop potential partnerships, pilots and demonstrations, according to Greentown.

This year's manufacturing cohort focuses specifically on process technology and catalytic innovations, which, according to Greentown, have the potential to be a "critical enabler of the global energy transition." Greentown shares that 90 percent of chemical processes depend on catalysis, but traditional methods rely on fossil fuels and consume significant amounts of energy.

“Catalysis underpins the majority of industrial chemical processes, which together account for a significant share of global emissions, making it a critical lever for reducing carbon intensity while improving performance,” Georgina Campbell Flatter, CEO of Greentown, said in a news release. “Greentown Go Make 2026 is designed to close the gap between breakthrough innovation and industrial deployment. By connecting startups with Shell and Technip Energies’ technical expertise and global scale, we’re helping accelerate solutions that improve efficiency and drive industrial decarbonization.”

The five Greentown Go Make 2026 companies include:

  • Houston-based Biosimo, which makes scalable biochemicals from ethanol
  • Missouri-based Catalyxx, which transforms bioethanol into drop-in, cost-competitive, carbon-negative chemicals
  • Sydney, Australia-based HydGene Renewables, which produces low-carbon hydrogen and industrial chemicals from waste biomass
  • Switzerland-based TreaTech, which turns waste into renewable gas, water and minerals through catalytic hydrothermal gasification
  • California-based Unifuel, which has developed a chemical technology platform to make sustainable aviation fuel, renewable gasoline and other renewable chemicals

The cohort will be celebrated at a kickoff event in Houston at The Ion on June 9.

In addition to Greentown Go Make, Greentown also runs its Go Move (transportation), Go Energize (energy and electricity), Go Build (buildings), and Go Grow (food and agriculture) cohort-based programs. The climatech incubator announced its Go Build 2026 cohort in March. Read more here.

Houston developer launches AI-powered water platform to boost efficiency

eyes on AI

Houston real estate company McCord Development has launched an artificial-Intelligence-run water management platform, MizuWatch.

MizuWatch aims to help operators, districts, and municipalities detect leaks faster, reduce water loss and improve efficiency, according to the company. MizuWatch pulls data from supply sources, smart meters, historical usage and maintenance records, and combines them into a single platform. The AI system also uses visual mapping and digital twin technology to deliver near-real-time system insights.

“MizuWatch brings the right data together daily, so teams can see what’s happening now, intervene earlier and focus their resources where they have the greatest impact,” Jerzy Wielgus, chief product officer for MizuWatch, said in a news release.

MizuWatch was built to “scale across geographies and system sizes to help assist with water scarcity, aging infrastructure, and operational complexity,” according to the company. It was developed at Houston’s Generation Park, McCord’s 4,300-acre master planned commercial district. McCord was able to pilot the platform onsite to help manage its complex, real-world water systems at scale.

“Resilient infrastructure is a key factor for the companies choosing Generation Park,” Ryan McCord, CEO of McCord Development and Founder & CEO of MizuWatch, added in the release. “We made the decision to deploy smart meters, but no one knew how to use the data they generate. This is an opportunity across all infrastructure where sensors are deployed. What started as an internal solution has become a platform we believe can help stakeholders everywhere be more efficient in their operations, investment, and compliance.”

Last fall, Eli Lilly and Co. selected Generation Park for its $6.5 billion manufacturing plant. More than 300 locations in the U.S. competed for the factory. Bristol Myers Squibb Co., another pharmaceutical giant, also announced it is considering Generation Park for a new manufacturing hub earlier this month.

Oil giant BP ousts new chairman over serious conduct concerns

Sudden Exit

BP has ousted its chairman over what it called serious concerns related to “important governance standards, oversight and conduct.”

The departure was abrupt and unexpected, with Albert Manifold having been appointed to the position late last year.

“Albert has helped bring a welcome focus and pace to BP’s transformation," Amanda Blanc, senior independent director, said in a statement Tuesday, May 26. "However, the board has been surprised and disappointed to learn of governance oversight and conduct issues it deems unacceptable and has taken decisive action.”

BP's board named Ian Tyler as interim chair, effective immediately.

BP, based in London and with North American headquarters in Houston, is a “supermajor,” one of the five largest oil production and exploration companies in the world when measured by revenue and profit.

Manifold, who had been the top executive at Dublin-based global building materials company CRH for 10 years, became the chair at BP in October. BP was looking for someone to revamp the oil giant and went with an industry outsider in Manifold, who had made major strategic changes at CRH.

After a new focus on renewable energy at BP in 2020, by 2025 the company was seeking a return to its roots. BP's hard reset was criticized by environmentalists, as well as some shareholders.

CEO Murray Auchincloss said last year that optimism over opportunities in renewable energy was misplaced, with the company moving “too far and too fast.”

Changes in leadership at BP in recent years has been tumultuous.

CEO Bernard Looney resigned in late 2023 after BP determined that he had misled the company over his past relationships with colleagues.

Auchincloss stepped down in December, and the company named Meg O'Neill as his successor.

Manifold’s was challenged almost immediately when shareholders defeated company resolutions this spring that would have allowed BP to reduce climate reporting requirements and move its annual meetings fully online. Some 18% of shareholders voted against Manifold’s election as chairman, a high level of opposition for an appointment that is generally rubber stamped by investors.

Legal & General, one of Britain’s largest insurers and investment companies, said at the time that Manifold was responsible for resolutions that would have had “a negative impact on shareholders’ insight into how the company is addressing financially material long-term risks, and seizing long-term value creation opportunities, associated with the energy transition,” the Times of London reported on April 23.

Glass Lewis, an influential shareholder advisor, urged investors to vote against Manifold’s election. It held that BP took “unprecedented action” by refusing to consider a resolution from a group of climate activists and pension funds hoping to force the board to create an alternative strategy should demand for fossil fuels decline, the Times reported.

Like other big oil companies, BP has struggled with falling demand in recent years.

BP’s 2025 earnings fell 16% from a year earlier to $7.49 billion as the price of Brent crude, a benchmark for international oil prices, dropped 16.9%. The company’s preferred measure of earnings is underlying replacement cost profit, which adjusts for one-time items and fluctuations in the market value of inventories. Net income plunged 86% to $55 million.

Last year there were media reports that British oil giant Shell was in talks to buy rival BP. Shell denied the reports at the time.

The search for a new chair is underway, BP said Tuesday. Shares of BP Plc slid nearly 5% in midday trading on the NYSE.

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