Halliburton, MODEC’s Shape Digital set on enhancing digital asset performance

June 29, 2026, by Melisa Cavcic

U.S.-headquartered oilfield services player Halliburton has joined forces with Shape Digital, a spin-off of Japan’s MODEC, to advance digital asset performance management by integrating subsurface and surface intelligence through a unified asset view.

FPSO; Source: MODEC — FPSO illustration; Source: MODEC

The duo’s strategic collaboration is set on combining Halliburton Landmark’s Digital Field Solver (DFS) decision system with Shape Digital’s applied AI portfolio, including Lighthouse, Aura, and Reef, blending trusted data, domain science, operational expertise, and applied artificial intelligence (AI) to support predictive, asset-level decision-making across the full asset lifecycle.

Since integrated reservoir, well, and production network models are connected with surface-operations intelligence, covering equipment reliability, energy efficiency, and safety, such a connection is said to support more consistent decision-making across three areas: integrated production planning, alignment of energy efficiency with production objectives, and safety and asset integrity.

Tony Antoun, Senior Vice President of Landmark Software and Services at Halliburton, emphasized: “At the core of this collaboration is the ability to connect decisions throughout the production system. The integration of subsurface and surface intelligence helps our customers plan with confidence, adapt to change, and execute more consistently throughout the asset lifecycle.”

According to Shape Digital, effective production planning depends on visibility into how reservoir behavior, well performance, facilities constraints, and equipment condition interact over time; thus, evaluating these elements together allows production plans to stay aligned as conditions change.

Through this collaboration, the company will apply AI to evaluate live and historical equipment behavior, while Landmark provides the system context to understand effects on flow, constraints, and production targets to help teams identify constraints earlier, respond more quickly to variability, and maintain alignment as operating conditions change.

Felipe Baldissera, CEO of Shape Digital, underlined: “Together with Halliburton, we bring operational intelligence and applied AI into the context of real production systems. This collaboration supports better planning, more efficient operations, and stronger safety outcomes at scale.”

MODEC explains that it applies digital solutions in areas directly tied to business value, grounded in decades of operational expertise developed across floating production, storage, and offloading (FPSO) engineering, procurement, construction, and installation (EPCI), leasing, and operations and maintenance.

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The Asian giant is adamant that each solution reflects real-world lessons learned from resolved operational challenges, translating hard-won field experience into measurable gains in efficiency, reliability, and competitiveness.

MODEC underlined: “Shape Digital serves as MODEC’s dedicated platform for scaling this knowledge beyond our own fleet, delivering applied AI and operational intelligence solutions to the broader energy industry.

“In parallel, in addition to applying Shape Digital’s solutions, including predictive maintenance, AI-enabled digital twins for GHG reduction, and digital barrier management, MODEC continues to advance its internal Digital & Analytics capabilities to address our unique challenges, transforming operational data into actionable insights that drive safer, more reliable, and more cost-effective operations.”

The firm claims that these digital initiatives represent a strategic differentiator not only in improving its own performance but also in positioning it as a trusted partner for the energy industry’s digital transformation.

MODEC underscored: “As production systems grow more complex and interconnected, operators face increasing pressure to make faster, more consistent decisions. Production performance improves when teams manage reservoirs, wells, networks, equipment, and safety systems as one connected asset.

“When teams integrate engineering models with operational data in context, they gain a clearer system-level view and support more consistent decision-making throughout production operations.”