Integrated Production Optimization Framework Enhancing Development Planning Decisions In Heterogeneous Petroleum Reservoir Environments

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@article{1712852,
      author = {Lymmy Ogbidi, Benneth Oteh},
      title = {Integrated Production Optimization Framework Enhancing Development Planning Decisions In Heterogeneous Petroleum Reservoir Environments},
      journal = {Iconic Research And Engineering Journals},
      year = {2019},
      volume = {3},
      number = {5},
      pages = {345-366},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1712852.pdf},
      abstract = {In heterogeneous petroleum reservoir environments, effective development planning and production optimization are critical to maximizing hydrocarbon recovery while minimizing operational costs. This study proposes an Integrated Production Optimization Framework (IPOF) aimed at enhancing decision-making in the development planning phase of such reservoirs. The framework integrates advanced modeling techniques, real-time data analytics, and machine learning algorithms to optimize production strategies, accounting for reservoir complexities such as varying permeability, fluid properties, and geological features. The IPOF employs a multi-criteria decision analysis approach, combining geological, geophysical, and engineering data with economic and environmental considerations. This integrated approach allows for the generation of optimized production schedules and enhanced resource allocation, ensuring that the overall reservoir management strategy is both cost-effective and sustainable. Key components of the IPOF include reservoir simulation models for different production scenarios, optimization algorithms for well placement and production rates, and predictive analytics for forecasting reservoir performance. Additionally, the framework incorporates uncertainty quantification techniques to account for data gaps and model inaccuracies, ensuring more reliable decision-making. By combining both deterministic and stochastic methods, the IPOF offers a comprehensive solution for development planning in heterogeneous environments, where traditional models may struggle to provide accurate predictions. Through case studies and simulation results, the effectiveness of the IPOF in improving development planning decisions is demonstrated. The framework?s ability to integrate various reservoir characteristics and production variables enables operators to make informed decisions that lead to improved recovery rates and reduced operational risks. The proposed framework can be applied to various petroleum reservoirs worldwide, offering a versatile tool for enhancing production optimization and development planning.},
      keywords = {Integrated Production Optimization, Reservoir Management, Decision-Making, Machine Learning, Petroleum Reservoir, Development Planning, Reservoir Simulation, Multi-Criteria Decision Analysis, Optimization Algorithms, Uncertainty Quantification.},
      month = {November},
  }