Unlocking the next wave of innovation in US shale

Igniting a new wave

Upcoming challenge: Risk of breakeven costs rising amid flat-to-lower oil and gas prices, impacting competitiveness

Cost and tariff headwinds are mounting—upstream costs are slated to rise by 4% to 20%¹⁰—while the structural weakness in oil markets (absent conflicts and supply disruptions) may persist. Against this backdrop, a third, digital-led innovation cycle could help accelerate performance gains and reduce the breakeven gap with low-cost global counterparts (figure 2). This third wave of innovation should consider three aspects.

1. Infrastructure activation: Rebuilding exploration capability and monetizing the broader midstream infrastructure build-out
2. System optimization: Leveraging smart, connected operations to reduce operating expenditure (opex) and lift netback
3. Workforce amplification: Prioritizing scalable, field-first use cases that can be deployed quickly

Infrastructure activation

Opportunity: Potentially reduce breakeven costs by US$1.5 to US$1.75 per barrel

By enhancing exploration’s digital capability and strengthening end-to-end reliability across the infrastructure buildout, the industry could potentially realize savings of up to US$1.75 per barrel.¹¹ Maintaining a balance between production and midstream takeaway capacity could help keep the system well-supplied and dependable.

• Digital-led exploration growth: Exploration spend as a share of US upstream spend has fallen by 50% to US$10 billion.¹² However, rebuilding exploration muscle may not be able to follow older strategies that leaned on classic wildcatting, geoscience-led sweet-spotting, acreage shape and contiguity, and static decline-curve assumptions. Instead, exploration should include a digital backbone as much as geoscience: integrated subsurface-to-surface data for better prospect ranking; analytics and AI to continuously recalibrate decline curves and operational constraints (for example, water, power, and infrastructure); and data-powered workflows that improve capital allocation and repeatability. AI and machine learning can help accelerate seismic analysis from months to weeks, while improving seismic interpretation quality by up to 40%, increasing effectiveness by US$0.15 to US$0.25 per barrel of exploration capex.¹³
• Capitalizing integrated infrastructure expansion: Midstream capex, which directly supports the growth of upstream operators and downstream refiners, has seen its share of total US O&G capex nearly double since 2015.¹⁴ The midstream buildout has enabled a reduction in natural gas flaring and venting, which equates to roughly US$0.4 per barrel on a gross value basis.¹⁵ Similarly, an optimal and connected midstream buildout around the Permian Basin, relieving Waha congestion, could bring roughly US$0.9 to US$1 per barrel in value lift when spread across total US crude output.¹⁶ Realizing and sustaining this value should include treating the midstream buildout as a flexible, data-enabled platform that can improve flow assurance, monitor and manage key constraints, and enable deeper risk-based inspection and maintenance.

System optimization

Opportunity: Potentially reduce breakeven costs by US$7.25 per barrel

Breakevens can fall when both sides of the financial equation are optimized: value chain optimization improving the “in-between” netbacks from production to sales and smart operations optimizing opex spending across day-to-day operations. Integrated, they can drive a step-change in project economics of nearly US$7.25 per barrel.¹⁷

• Value chain optimization: Misaligned handoffs between a company’s assets or business units can reduce total value captured. For example, when upstream oil cargo timing or quality shifts but refinery nominations and tankage cannot adjust fast enough, the refinery may run suboptimally and excess barrels can get pushed into the spot market at a discount, often with added storage and handling costs. Similarly, refiners can lose significant value when their linear programming models rely on weekly or monthly assumptions, while price structures and supply constraints shift daily, and when their trading or hedging strategies rely on generic 3‑2‑1 crack spreads that don’t reflect the refinery’s actual yield slate (figure 3).
  
  A large integrated player in the Permian Basin, for instance, faced fragmented decision-making across its upstream, midstream, and commercial functions. By integrating financial, operational, commercial, and market data, the company enabled dynamic linear programming-based optimization, faster scenario simulation, tighter collaboration between schedulers and traders, and constraint-aware decision-making from production through sales. As a result, netbacks improved by US$1 to US$1.75 per barrel within the first six months, driven by better flow assurance, commercial alignment, and end-to-end profitability.¹⁸

However, results may depend not only on operating performance, but also on infrastructure positioning and the decision-making structure.

• Smart, connected operations: A large share of operational expenditure often stems from overmanagement, inefficient execution, and suboptimal allocation of resources across repeatable operational events. These can include late failure signals and avoidable callouts driven by poor-quality alarms and sensors, reactive full-system shutdowns, and manual workarounds such as handwritten logs. Over time, these issues can compound into production deferment, excess field visits, and higher energy and materials consumption (figure 3). Several digital programs over the years have improved visibility but not outcomes for organizations—for instance, dashboards without a defined closed-loop response and analytics that aren’t embedded in frontline workflows.¹⁹ Closing the gap should include smart operations that hardwire insights into day-to-day execution, converting “information value” into “operational value.”
  
  For example, a US shale asset operated by a large integrated company realized benefits of up to US$5.5 per barrel by shifting to smart operations. These included agentic AI-powered monitoring, automated downtime coding, and exception-based operations with human intervention only when needed. Additional gains came from predictive failure detection, prescriptive maintenance, and integrated remote operations enabled by dynamic geospatial data.²⁰

Workforce amplification

Opportunity: Nearly 57% of task hours can be redeployed, but value may hinge on tight prioritization

In an unconstrained technology adoption scenario, nearly 57% of workforce task hours in the US O&G sector could be redeployed—34% via physical AI (for example, robotics and mechanical automation) and 23% via digital AI (for example, generative and agentic AI).²¹ This estimate is an upper-bound indicator of where tasks can be redesigned—not removed—with actual impacts varying by role design, task mix, site conditions, safety constraints, integration effort, and the pace of upskilling. In practice, adoption may be constrained by capital availability, integration complexity, and workforce readiness. Given the industry’s field-heavy cost base and large frontline workforce, companies may want to consider prioritizing field-first use cases that can deliver near-term value.

An analysis of about 40 field occupations across two dimensions—deployment speed (capital required, integration effort, and upskilling needs) and potential business impact (value-weighted capacity) adjusted for criticality of the occupation—highlights several “feasible and impactful now” targets (figure 4, top-right quadrant).²² In 2024, this quadrant represented around 95,000 workers—about half of on-field employment—whose frequent, high-risk tasks affect uptime or downtime and are well-suited to established technologies that require little integration or training.²³ Importantly, value can come not only from mechanizing tasks but also from redesigning the work around them—dispatch, sequencing, parts availability, and shift coordination. The top five occupations in this quadrant are:

• Roustabout: A hands-on role helps keep the site safe and running (rig-up and rig-down, basic maintenance, site readiness). Value can come from equipping roustabouts with better digital tools to work more safely and effectively, including mobile work management, digital checklists and job hazard analyses, digital permit and lockout or tagout capture, and tool and equipment tracking.
• Wellhead pumper: A frontline role that protects production uptime and asset integrity by performing rounds, making adjustments, and catching issues early. Improvement opportunities can focus on giving these professionals better visibility and faster access to actionable information through asset-linked digital rounds, alert-driven prioritization, and voice-to-text notes that auto-populate field logs.
• Material handler: An important role that helps keep throughput high and crews productive by staging the right parts, reducing delays, and preventing stockouts. Digitization can strengthen this role by improving material visibility and execution through barcode or RFID-enabled receiving and picking, digital chain-of-custody or load tickets, basic yard or staging visibility, and smarter reorder triggers.
• Rotary drill operator: This is an important role focused on drilling performance and safety, where small deviations can quickly cascade into nonproductive time and well-quality issues. Near-term gains could come from enhancing operator decision-making with better data connectivity, faster decision support, and more standardized reporting, including auto-capture of key events or parameters, alarm rationalization, guided procedures, and AI-assisted summaries.
• Welder: An important role for ensuring safety and compliance, where defects can create disproportionate rework and risk. Near-term task redesign should consider focusing on giving welders stronger quality and traceability tools, including digital weld packages, in-process checklists, photo-backed quality assurance and control, consumables tracking, and automated inspection-ready documentation.

Progress is a process: Toward a new wave of global competitiveness

The next wave of innovation could help shale operators reduce the US$8 to US$10 per barrel gap with their low-cost global counterparts and rewrite the US shale industry’s competitive model in the following ways.²⁴

• Compounding innovation gains: Shale rebuilds 60% to 70% of its asset base annually, allowing operators to roll cost and process improvements across all their wells within 12 to 18 months.²⁵ By contrast, conventional producers refresh only 5% to 10% of wells per year, limiting the impact of innovation on their total production.²⁶ Like regular software updates by a technology company, frequent rebuild helps keep shale operators improving year after year. Put simply, shale’s steep decline curves—often viewed as its weakness—could be a competitive advantage.
• Resilient supply: The US O&G industry is the largest and most integrated O&G industry in the world, offering demand and supply optionality across domestic and export markets.²⁷ As wellhead-to-customer and wellhead-to-terminal integration strengthens, US companies may have a greater cushion in their full-cycle breakeven to absorb price shocks, as opposed to others that are primarily guided by wellhead or half-cycle breakeven. Taken together, this could support viewing US shale as a more stable supply base, not a default swing producer.
• Smoother workforce cycles: US O&G workforce uncertainty should moderate at the margins as more work shifts toward tech- and data-centric roles (automation, remote operations, analytics, reliability), which are often less tightly tied to rig count. As US operators expand digitally enabled operating models and centralized monitoring or support, staffing needs can adjust with less uncertainty, making downcycles less volatile and upcycles less marked by rapid rehiring.