New tools are connecting production systems to make data more usable in operations

Oil and gas assets are aging, and operations are becoming more complex. Operators are rethinking how wells, facilities and pipelines are managed. New digital tools are emerging to connect these systems, turning fragmented production data into coordinated, actionable insight.

Across the energy industry, production systems generate enormous volumes of operational data. Yet much of that information remains difficult to translate into timely decisions. Engineers often rely on multiple, disconnected systems to monitor performance and make operational decisions.

As assets mature and operations grow more complex, operators are looking for ways to better connect those systems.

At SLB, engineers and digital specialists are developing technologies aimed at addressing the challenge. OptiFlow™ production assurance solutions, OptiSite™ facility, equipment and pipeline solutions and the Tela™ agentic AI assistant are designed to integrate data and workflows across production operations, from reservoirs and wells to facilities and pipelines.

Together, these technologies help operators connect data and workflows across reservoirs, wells, facilities and pipelines, allowing production systems to be managed with greater visibility and coordination.

From field operations to digital design

For Melody Cao, product manager for OptiSite solutions, the effort grew out of years working in field operations.

Cao began her career as a design engineer working on petrochemical and chemical plants before moving into construction and operations roles. She later worked on projects across China, the Middle East and Australia, including pipelines, offshore developments and production facilities.

During a gas development project in Yanbei, China, she encountered a problem common across the industry. Control systems were generating large volumes of data, but engineers still struggled to convert that information into timely operational decisions.

“The data existed, but extracting value from it could take too long,” Cao said.

The experience led her to explore digital technologies and predictive analytics. After joining SLB and relocating to London, Cao worked with digital teams to develop predictive models, including a system designed to anticipate compressor failures.

Bringing facilities, equipment and pipelines into focus

Those efforts developed into OptiSite solutions, with a focus on improving the performance and reliability of facilities, equipment and pipelines.

OptiSite solutions integrate operational data with simulation models and predictive analytics to help operators identify emerging issues before they lead to downtime. Rather than replacing existing control systems, the solutions work alongside them, combining data that would otherwise remain scattered across different systems.

The system builds on SLB’s long-standing engineering modeling technologies, including Olga™ dynamic multiphase flow simulator, Pipesim™ steady-state multiphase flow simulator and Symmetry™ process simulation software, which engineers use to simulate flow, wells and processing systems.

By combining those simulation foundations with real-time operational data and analytics, OptiSite solutions provide earlier insight into potential equipment and infrastructure issues.

Managing production as one system

Improving performance across the broader production system, including reservoirs, wells and production networks, is the focus of OptiFlow production assurance solutions.

Production assurance requires balancing multiple variables, including reservoir pressure, well performance, fluid flow and infrastructure constraints. Mahyer Mohajer, who goes by Matt and is product manager for OptiFlow solutions, said operators increasingly expect digital tools to simplify that complexity.

“Customers no longer want access to raw data alone,” Mohajer said. “They want insights that help them understand what is happening and what actions to take.”

OptiFlow solutions combine advanced simulation capabilities with AI, including generative and physics-informed AI, to monitor production systems and model possible outcomes. Engineers can test operational scenarios, detect problems earlier and adjust production strategies more quickly.

The objective is to connect parts of the production system that have traditionally been managed separately.

Reservoir engineers, well engineers and facility operators often rely on different tools and datasets, even though they work on the same physical system. By connecting these domains digitally, OptiFlow solutions and OptiSite solutions enable operators to manage production from reservoir to facility with greater coordination.

How AI changes interaction with production data

SLB is also integrating these systems with the Tela agentic AI assistant, designed to help engineers interact with operational data more easily. Instead of gathering information across multiple software platforms, engineers can use Tela to analyze trends, run simulations and generate operational recommendations.

For Cao, the shift recalls changes she witnessed growing up in rural China.

Harvesting wheat once required days of manual labor across entire fields. Today, modern machines can complete the same work automatically in a fraction of the time.

She believes production operations could undergo a similar transformation.

“In the future, engineers will not spend their time gathering data or running routine analysis,” Cao said. “They will begin the day with insights that help them focus on higher-value decisions.”

From monitoring to insight-led operations

As digital technologies mature, production operations are moving beyond monitoring individual assets toward managing entire systems in context.

By linking data, models and workflows across reservoirs, wells, facilities and pipelines, integrated digital solutions are enabling earlier insight, more informed decisions and closer coordination across disciplines. For operators facing increasingly complex production challenges, that shift could redefine how production systems are managed in the years ahead.