Smart Digital Solution for Field Development Planning Optimization

MSCA (Marie Skłodowska-Curie)HORIZON-TMA-MSCA-PF-EFID: 101111369
EC Contribution
€2,268
Consortium Size
1 orgs
Start Year
2023
Summary

To meet the world's energy demands specifically with “easy oil” reservoirs depleting, it is important to optimize production and field development planning (FDP). This will be even more pronounced in the years to come if pore space is to be used to store CO2 or hydrogen in large-scale decarbonized energy solutions. Traditional modeling practices are known for high computational demand, and workflows for optimizing management strategies tend to be manual due to the complexity of the models. In this project, the goal is to develop an advanced optimization procedure that will serve as a smart decision support tool, which can be used to choose the best field development plan while handling properly the technical, economic, and environmental constraints. This tool integrates automated simulation with artificial intelligence and metaheuristic algorithms in one self-adaptive optimization framework and will provide possibilities to deal with complex optimization tasks in the development and management of reservoirs under uncertainty. The expected outcomes of this project are a new generation of solutions that can enhance and optimize the recovery of hydrocarbons and can also be customized to address complex optimization issues in natural energy resource development, CO2 sequestration and in other disciplines.The project will be performed in three steps: i) digital formulation of FDP tasks under complex constraints, ii) development of a smart solution for FDP optimization and iii) user-friendly tool for decision-making. The multidisciplinary aspects of the project include simulation, optimization and data science. The researcher will combine his previous research experience within these areas and develop new skills to perform the project. The host institution will provide infrastructure and supervision of different aspects of the project by integrating the researcher in a strong team in reservoir modeling and optimization that also provides collaboration with industry.

Consortium (1)

Project Results (7)

Source: CORDIS, the EU research results database.

Publications (4)
A Hybrid Model of ANN and KNN for Predicting Reservoir Properties in Geothermal Resource Development
86th EAGE Annual Conference & Exhibition· 2025DOI
K. Redouane, V. Hatleli, V. Rafael de Freitas and A. Jahanbani Ghahfarokhi
Flow Rate Prediction in a Real Oil Field Using Random Forest Algorithm
85th EAGE Annual Conference & Exhibition· 2025DOI
K. Redouane, A. Jahanbani Ghahfarokhi, M. Benamara, M. Boussaber, Y. Guidoum, M. Sedoud
Hybrid Optimization Framework for Well-Placement Using Gradient-Free Algorithm and Physics-Informed Artificial Intelligence
SPE Reservoir Simulation Conference· 2025DOI
Kheireddine Redouane, Ashkan Jahanbani Ghahfarokhi
Accurate Prediction of Bottom-hole Pressure in Vertical Wells of Algerian Fields using A New Hybrid Intelligent System Based on Neural Network -Fuzzy Logic and PSO Algorithm
3rd Edition of International Conference on Oil, Gas, and Petroleum Engineering· 2024
Kheireddine Redouane; Ashkan Jahanbani Ghahfarokhi; Benamara Mustapha; Zeraibi Nourddine
Deliverables (2)
Other Results (1)
Periodic Reporting for period 1 - Smart_FDP (Smart Digital Solution for Field Development Planning Optimization)