Why are Halliburton and PETRONAS Carigali collaborating on next-gen reservoir modeling in Malaysia?

Halliburton Company (NYSE: HAL), the American oilfield services major, announced on June 21, 2025, a strategic collaboration with PETRONAS Carigali Sdn. Bhd., the upstream exploration and production subsidiary of Malaysia’s national energy firm PETRONAS. The partnership will implement Halliburton Landmark’s DecisionSpace® 365 Geosciences Suite and its Unified Ensemble Modeling solution across PETRONAS Carigali’s field assets in Malaysia. The move is positioned to unify real-time subsurface workflows, accelerate exploration-to-production cycles, and boost confidence in reservoir forecasts using artificial intelligence-driven earth modeling.

The deployment marks a significant shift in how PETRONAS Carigali will approach greenfield developments and mature reservoir revitalization, relying on live-earth digital twins and probabilistic ensemble modeling to improve forecast reliability, geological accuracy, and institutional confidence in volumetric estimation.

Halliburton’s latest suite allows exploration and development teams to co-author models simultaneously on a single digital environment, facilitating faster project maturation and tighter integration between seismic interpretation, static modeling, and dynamic forecasting.

How does DecisionSpace 365 change conventional reservoir modeling methods used by national oil companies?

Historically, most upstream operators, including national oil companies, relied on deterministic, grid-based reservoir models built through segmented workflows. These processes required manual handoffs between geoscientists, reservoir engineers, and production analysts—often leading to delays, data mismatches, and rigid model structures. Halliburton’s DecisionSpace® 365 Geosciences Suite, deployed in the cloud, eliminates many of these bottlenecks by enabling AI-assisted, probabilistic workflows that dynamically incorporate basin-scale and field-level geology into an evolving earth model.

The Unified Ensemble Modeling component automates scenario generation and incorporates real-time flow data to adjust forecasts on the fly. According to institutional observers, this shift towards “living reservoir models” reflects a wider global trend among upstream operators prioritizing speed-to-market and decision quality over static modeling cycles.

Tony Antoun, Senior Vice President of Landmark Software and Services at Halliburton, emphasized that the integrated modeling framework brings together exploration and development teams in a unified digital loop, reducing time-to-first-oil while maximizing asset yield.

What are PETRONAS Carigali’s strategic goals in adopting AI-powered ensemble modeling?

PETRONAS Carigali’s deployment of these tools is directly linked to its push for faster field monetization and enhanced operational certainty across Malaysia’s upstream sector. The state-backed energy operator is leveraging Halliburton’s suite to implement a harmonized earth model across both greenfield and mature assets, significantly improving continuity between exploration, appraisal, and development planning phases.

Hazli Sham Kassim, Senior Vice President of Malaysia Asset and CEO of PETRONAS Carigali Sdn. Bhd., stated that integrating DecisionSpace 365 into core workflows is essential for meeting the company’s aggressive project delivery benchmarks. The Malaysian upstream operator sees a unified, AI-supported workflow as key to streamlining its reservoir maturation pipeline and ensuring early intervention opportunities in asset lifecycle planning.

The strategic technology rollout follows a comprehensive benchmarking exercise conducted by PETRONAS across its field operations. The benchmarking revealed significant optimization opportunities in how reservoir models were generated, stress-tested, and updated, particularly in light of increasingly complex geology and shorter development windows.

What are the technical advantages of ensemble modeling compared to deterministic forecasting systems?

Ensemble modeling introduces a probabilistic layer to traditional reservoir simulation, enabling teams to generate multiple geological and petrophysical scenarios rather than relying on a single “best-case” forecast. In Halliburton’s framework, these models are not only produced faster but are continuously refined by feeding in real-time field data—including well test results, seismic updates, and production histories.

By applying this method, PETRONAS Carigali aims to drastically reduce modeling cycle time and enable more dynamic well placement strategies. Analysts believe that ensemble modeling’s ability to quantify uncertainty with greater granularity gives institutional stakeholders stronger confidence in capital allocation decisions and net present value (NPV) forecasting for new wells.

Additionally, DecisionSpace 365 allows asset teams to retain geological fidelity from basin-scale assessments to individual wellbores, ensuring model consistency across regional and field-specific planning.

How do institutional investors and analysts view Halliburton’s Landmark technology deployment in Southeast Asia?

While Halliburton did not disclose financial terms of the agreement, institutional sentiment toward its software and services division—especially Landmark—has been increasingly positive. Landmark is viewed as a key growth driver in Halliburton’s digital portfolio, particularly amid rising upstream digital transformation investments in Asia and the Middle East.

Analysts broadly interpret this deal with PETRONAS Carigali as a strategic signal that Halliburton’s next-gen subsurface technology is gaining traction with national oil companies. For PETRONAS, this collaboration also reinforces its status as a digitally progressive operator, positioning it alongside global peers pursuing AI-based decision models in upstream development.

Given PETRONAS’ scale and its global production footprint of over 2 million barrels of oil equivalent per day (boepd), any successful application of this modeling architecture could have significant spillover effects into other joint ventures and international operations.

What future applications could emerge from this Halliburton-PETRONAS technology partnership?

As PETRONAS Carigali integrates DecisionSpace 365 and ensemble modeling into its upstream ecosystem, future applications could extend into unconventional reservoirs, marginal field redevelopment, and carbon capture and storage (CCS) feasibility models. Halliburton’s AI-assisted tools are already being considered for EOR simulation, digital twin reservoir monitoring, and even portfolio-level risk analysis.

Institutional expectations suggest that, if the deployment meets PETRONAS’ field targets, other national oil firms in Southeast Asia could follow suit—especially in Indonesia, Brunei, and Vietnam—where mature field redevelopment faces similar geological and economic constraints.

For Halliburton, successful execution in Malaysia could solidify Landmark’s positioning as the preferred upstream modeling platform for national oil companies seeking to unify exploration, development, and production planning into a single digital continuum.

How does this deployment align with Halliburton’s broader strategy in energy digitalization?

Halliburton has consistently emphasized the importance of digital innovation in oilfield operations, especially in reducing environmental footprint, accelerating time to revenue, and enhancing asset decisioning. The deployment with PETRONAS Carigali fits within its broader effort to provide scalable, interoperable digital solutions tailored to complex upstream environments.

Founded in 1919 and headquartered in Houston, Halliburton remains one of the world’s largest oilfield services providers, operating in more than 70 countries with over 40,000 employees. Its software division, Landmark, has become a strategic pillar in the company’s portfolio, contributing to non-traditional revenue streams and increasing recurring software-as-a-service (SaaS) income.

By enabling customers like PETRONAS Carigali to deploy AI-native solutions for real-time reservoir management, Halliburton is positioning itself as not just a services provider, but as a long-term digital transformation partner in the upstream sector.

What is the timeline for PETRONAS Carigali’s full integration of DecisionSpace 365 across field assets?

While PETRONAS has not provided a specific timeline for full-scale rollout, initial implementation is expected to begin in key Malaysian offshore assets by Q4 2025. The deployment will be phased to include greenfield projects first—where uncertainty quantification is most critical—followed by applications in mature fields requiring infill drilling or re-evaluation of enhanced recovery options.

Analysts anticipate measurable operational benefits to emerge within the first 12–18 months, especially in reducing subsurface modeling turnaround time, improving confidence in reservoir deliverability, and accelerating field development plan (FDP) approvals.

With this partnership, both Halliburton and PETRONAS Carigali are signaling a broader commitment to data-driven reservoir engineering—an area that continues to define competitiveness in the next chapter of upstream oil and gas.