Operators face urgent challenges, including asset maturity, declining recovery, regulatory scrutiny, and the need to demonstrate value to investors and stakeholders. At the same time, the digital enablement of simulation workflows is rising rapidly. The lack of open data ecosystems and integrated service models remains a bottleneck for many organizations. The coming years will distinguish industry leaders from followers, with key factors including reservoir model precision, simulation turnaround time, data interoperability, effective management of subsurface uncertainty, and the commercialization of both conventional and low-carbon simulation technologies.
Turning Simulation into Value
Running a static reservoir model occasionally is no longer sufficient. For the upstream oil and gas sector, simulation extends beyond subsurface flows. It requires using well data, seismic reinterpretation, production history, injection scenarios, and full-field development options within a collaborative cloud-native platform. At the same time, untapped value often remains hidden in overlooked reservoir compartments, bypassed zones, or suboptimal well placement, as teams frequently find that legacy models underutilize new data. New simulation service models are emerging, including service-on-demand options, cloud-based execution, scenario libraries, open data contributions, and digital twins of reservoirs. The essential requirements are transparency, modularity, commercial alignment, and ecosystem maturity. The industry is also shifting from simply applying models to generating simulation value on a scale.
We envision a network of simulation platforms, open data ecosystems, and collaborative decision environments spanning geoscience, engineering, and finance. The digital transformation of reservoir simulation is a strategic priority that unites high-performance computing, machine learning, data management, and multidisciplinary workflows. At the same time, new technologies are reshaping the commercial value of the subsurface domain. Surrogate models, digital twins, AI-enhanced history matching, and real-time model calibration are no longer niche. Operators and service providers now contribute data, models, and analytics to shared ecosystems, enabling progress toward more data-centric operations.
Today, reservoir simulation advances through cloud-on-demand execution, open frameworks, collaborative portals, and modular service layers. These capabilities enable teams to simulate full-field scenarios and evaluate enhanced recovery workflows, carbon storage strategies, and low-carbon integration options, all assessed through economic, regulatory, and investor perspectives.
