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所在平台: Udemy |
课程主页: https://www.udemy.com/course/practice-oil-reservoir-simulation-using-black-oil-model/
课程评论：没有评论
**课程名称：** 使用 Petrel RE 进行油藏模拟：油藏 **课程概述：** 本课程采用黑油模型，提供全面、实践性的油藏模拟方法。学员将学习构建、校准和优化油藏模型以进行准确产量预测和油田开发规划的必要步骤。课程涵盖从数据导入和模型设置到历史拟合、插井和案例比较的整个工作流程。 **主要学习目标：** * 导入和准备油藏数据，包括完井和生产数据。 * 使用 .vol 文件和输入表（相对渗透率、PVT 等）构建和验证油藏模型。 * 进行历史拟合，使模型与观测到的生产数据保持一致。 * 估算原始油藏含油量 (OOIP) 并分析油藏性能。 * 设计和评估含水层模型（自下而上和边缘含水层）。 * 生成有利可图的插井图，并优化井位。 * 模拟和比较不同的开发方案，包括插井和注水井改动。 * 使用 HCPV 图和流线可视化油藏动态。 * 进行案例比较，以评估经济和生产成果。 **适合人群：** * 油藏工程师 * 石油工程师 * 从事油藏建模的地质科学家 * 寻求黑油模拟实践经验的专业人士 **课程成果：** 完成本课程后，学员将能够熟练地将黑油模拟技术应用于实际油藏挑战，从而能够做出以数据为驱动的油田开发和提高采收率的决策。
This course provides a comprehensive, hands-on approach to oil reservoir simulation using the black oil model. Participants will learn the essential steps to build, calibrate, and optimize reservoir models for accurate production forecasting and field development planning. The course covers the entire workflow, from data import and model setup to history matching, infill well placement, and case comparison.Key Learning Objectives:Import and prepare reservoir data, including completion and production data.Construct and validate reservoir models using.vol files and input tables (relative permeability, PVT, etc.).Perform history matching to align the model with observed production data.Estimate Original Oil in Place (OOIP) and analyze reservoir performance.Design and evaluate aquifer models (bottom-up and edge aquifers).Generate opportunity maps for infill drilling and optimize well placement.Simulate and compare different development scenarios, including infill wells and injector conversions.Visualize reservoir dynamics using HCPV maps and streamlines.Conduct case comparisons to assess economic and production outcomes.Who Should Attend:Reservoir engineersPetroleum engineersGeoscientists involved in reservoir modelingProfessionals seeking practical experience in black oil simulationCourse Outcome:By the end of this course, participants will be proficient in applying black oil simulation techniques to real-world reservoir challenges, enabling them to make data-driven decisions for field development and enhanced oil recovery.
