NVIDIA’s AI push finds an oilfield ally, as SLB and Jim Cramer spotlight a long-running partnership

NVIDIA’s growing presence in industrial computing again came into focus on June 18, 2026, when SLB Chief Executive Olivier Le Peuch sat down with CNBC host Jim Cramer. The exchange centered on the technology company’s role alongside SLB, the oilfield services provider, in areas tied to drilling and field operations.

The segment drew attention to the companies’ long relationship. According to the report that surfaced the discussion, SLB and NVIDIA have collaborated for roughly two decades. The framing suggests the partnership has moved beyond a one-off technology trial into a continuing working relationship aligned with SLB’s operational and analytics needs.

While the post does not lay out engineering specifics, the core idea presented is straightforward: drilling is data-heavy, and the systems that help model rock, plan wells, and manage performance increasingly depend on high-performance computing. In that context, NVIDIA’s hardware and software stack, widely used in AI training and accelerated computing, becomes a platform that can be applied to industrial workloads.

The June 18 coverage also positions the collaboration as a “next huge bet” for the broader intersection of AI and industrial services. That characterization matters because it points to a strategic narrative competing with the more familiar consumer and data center AI themes. In industrial settings, AI ambitions are often constrained less by research novelty and more by integration, reliability, and the ability to translate analytics into operational decisions.

SLB’s participation is notable given its place in the energy supply chain. As a drilling and field-services company, SLB operates where operational constraints are immediate and measurable, including turnaround times, well performance, and the cost of downtime. When such a player highlights a technology partner on a mainstream business broadcast, it indicates that the use case is not purely experimental, at least from the perspective of senior management messaging.

For NVIDIA, partnerships like this reinforce a broader pitch to enterprises: that accelerated computing can power advanced simulations and analytics across industries. NVIDIA also maintains a large newsroom presence through its corporate blog, where it regularly discusses AI in sectors ranging from data centers to robotics and other industrial applications, although the June 18 reporting itself emphasizes the SLB angle rather than providing new technical disclosures.

Still, the public details available in the June 18 report are limited. The post referenced the CNBC segment and the duration of the relationship, but it does not specify contract terms, named products, measurable performance improvements, or whether any new deployment was announced. It also does not quantify how much of SLB’s computing or AI work depends on NVIDIA, nor does it describe what drilling-specific algorithms or datasets were involved.

What to watch next is whether additional disclosures emerge from either company, such as references to specific software platforms, deployment scale, or third-party confirmation of outcomes tied to drilling workflows. In particular, readers may want to track whether NVIDIA and SLB provide more concrete milestones beyond the general message of a deep partnership, because industrial investors and partners tend to respond to measurable operational impact rather than broadcast-level anecdotes.