Periodic Reporting for period 1 - Smart_FDP (Smart Digital Solution for Field Development Planning Optimization)
Reporting period: 2023-09-01 to 2025-08-31
The Smart-FDP project was launched in response to one of the most pressing challenges in the global energy sector: maximizing the value of existing hydrocarbon fields while reducing their environmental footprint and supporting both digital transformation and the transition to sustainable energy systems.
With ‘easy oil’ reserves dwindling and energy consumption increasing, the need to optimize field development planning (FDP) is paramount in meeting the world’s energy demands. This challenge intensifies with carbon-neutral economy ambitions and the integration of hydrogen storage into a decarbonized energy system. Traditional FDP relies on numerical reservoir simulations using approaches that are either based solely on engineering intuition or automated alternatives that require prohibitive computational effort. These approaches often fail to quickly identify truly optimal development scenarios under complex technical, economic, and environmental constraints in large, heterogeneous and mature reservoir systems.
The Smart-FDP project addresses these challenges by developing a next-generation digital solution for fast, reliable, and environmentally responsible field development planning. Its core vision is to combine AI and metaheuristic algorithms into automated simulations. This self-adaptive optimisation framework tackles complex optimization tasks in reservoir development/management, fostering efficient hydrocarbon recovery with reduced cost, risk, and environmental impact. The conception of the automated optimization tool begins with digital formulation, followed by smart optimizer development and culminates in a user-friendly decision-making tool enabling industrial and research exploitation for both fossil and renewable energy applications.
The approach adopted in this project directly aligns with EU strategic goals by supporting the European Green Deal, digital transformation of the energy sector, and sustainable subsurface use, including CO2 storage and geothermal energy production.
With ‘easy oil’ reserves dwindling and energy consumption increasing, the need to optimize field development planning (FDP) is paramount in meeting the world’s energy demands. This challenge intensifies with carbon-neutral economy ambitions and the integration of hydrogen storage into a decarbonized energy system. Traditional FDP relies on numerical reservoir simulations using approaches that are either based solely on engineering intuition or automated alternatives that require prohibitive computational effort. These approaches often fail to quickly identify truly optimal development scenarios under complex technical, economic, and environmental constraints in large, heterogeneous and mature reservoir systems.
The Smart-FDP project addresses these challenges by developing a next-generation digital solution for fast, reliable, and environmentally responsible field development planning. Its core vision is to combine AI and metaheuristic algorithms into automated simulations. This self-adaptive optimisation framework tackles complex optimization tasks in reservoir development/management, fostering efficient hydrocarbon recovery with reduced cost, risk, and environmental impact. The conception of the automated optimization tool begins with digital formulation, followed by smart optimizer development and culminates in a user-friendly decision-making tool enabling industrial and research exploitation for both fossil and renewable energy applications.
The approach adopted in this project directly aligns with EU strategic goals by supporting the European Green Deal, digital transformation of the energy sector, and sustainable subsurface use, including CO2 storage and geothermal energy production.
Over the course of the MSCA fellowship, Smart-FDP has successfully combined applied research, tool development, and industrial engagement, achieving several key scientific and technical milestones.
- Designed and implemented a generic FDP formulation framework that flexibly incorporates technical, economic, and environmental constraints, along with robust objective function definitions, ensuring valid optimization scenarios. Integrated the framework into a graphical user interface for intuitive problem setup and user-friendly input.
- Built and validated a self-adaptive surrogate modeling process using constrained Design of Experiments (DoE) to efficiently sample feasible FDP scenarios.
- Developed a hybrid optimization workflow that combines Artificial Neural Networks (ANN) and Genetic Algorithms, reducing simulation costs by up to 60% compared to traditional methods while identifying optimal scenarios that maximize hydrocarbon recovery.
- Designed and developed an advanced software tool integrating a high-performance optimization engine with an intuitive graphical interface, enabling efficient and user-friendly decision-making.
- Designed and implemented a generic FDP formulation framework that flexibly incorporates technical, economic, and environmental constraints, along with robust objective function definitions, ensuring valid optimization scenarios. Integrated the framework into a graphical user interface for intuitive problem setup and user-friendly input.
- Built and validated a self-adaptive surrogate modeling process using constrained Design of Experiments (DoE) to efficiently sample feasible FDP scenarios.
- Developed a hybrid optimization workflow that combines Artificial Neural Networks (ANN) and Genetic Algorithms, reducing simulation costs by up to 60% compared to traditional methods while identifying optimal scenarios that maximize hydrocarbon recovery.
- Designed and developed an advanced software tool integrating a high-performance optimization engine with an intuitive graphical interface, enabling efficient and user-friendly decision-making.
Smart-FDP goes beyond current industrial and academic practices by providing a generalized and self-adaptive digital framework for energy field development:
- Scientific impact: Introduces a new generation of hybrid surrogate-based optimization workflows adaptable to oil & gas, geothermal, and CO2 storage applications.
New framework for adequate formulation and handling of various FDP constraints in a way to facilitate their simultaneous treatment inside automatic optimization.
- Technical impact: Delivers real-time decision support with significantly lower computational cost than traditional methods. Demonstrated the methodology on benchmark reservoir models and early real-field cases (UNISIM-I-D), achieving ~60% reduction in total optimization time while maximizing recovery factor.
Consideration of constraints in the decision variables for risk reduction and handling of economic, technical and environmental requirements.
- Industrial impact: Enables real-time decision support in industrial environments by integrating simulation, AI, and optimization into a single platform.
New generation of simulation-based optimization solutions, which enhance the efficiency of tackling complex problems under wide specter of considerations in real field development projects.
- Societal and environmental impact: Contributes to the European Green Deal and UN SDGs (7, 9, 13) by enhancing the digital capabilities of energy companies for safer and more efficient development of subsurface resources, supporting energy security, cost reduction and transition to low-emission recovery systems.
Smart-FDP creates a foundation for industrial uptake through licensing or a spin-off company, with commercialization pathways and IPR coordinated by NTNU Technology Transfer Office (TTO). Its methods are transferable to other domains requiring expensive simulations, such as aerospace and renewable energy planning.
- Scientific impact: Introduces a new generation of hybrid surrogate-based optimization workflows adaptable to oil & gas, geothermal, and CO2 storage applications.
New framework for adequate formulation and handling of various FDP constraints in a way to facilitate their simultaneous treatment inside automatic optimization.
- Technical impact: Delivers real-time decision support with significantly lower computational cost than traditional methods. Demonstrated the methodology on benchmark reservoir models and early real-field cases (UNISIM-I-D), achieving ~60% reduction in total optimization time while maximizing recovery factor.
Consideration of constraints in the decision variables for risk reduction and handling of economic, technical and environmental requirements.
- Industrial impact: Enables real-time decision support in industrial environments by integrating simulation, AI, and optimization into a single platform.
New generation of simulation-based optimization solutions, which enhance the efficiency of tackling complex problems under wide specter of considerations in real field development projects.
- Societal and environmental impact: Contributes to the European Green Deal and UN SDGs (7, 9, 13) by enhancing the digital capabilities of energy companies for safer and more efficient development of subsurface resources, supporting energy security, cost reduction and transition to low-emission recovery systems.
Smart-FDP creates a foundation for industrial uptake through licensing or a spin-off company, with commercialization pathways and IPR coordinated by NTNU Technology Transfer Office (TTO). Its methods are transferable to other domains requiring expensive simulations, such as aerospace and renewable energy planning.