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Production Analysis of a Niobrara Field Using Intelligent Top-Down Modeling

机译:智能自上而下建模的Niobrara场的生产分析

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Unconventional hydrocarbon resources are going to play an important role in the US energy strategy.Conventional tools and techniques that are used for analysis of unconventional resources include decline curve analysis,type curve matching and sometimes(in the case of prolific assets)reservoir simulation.These methods have not been completely successful due to the fact that fluid flow in unconventional reservoirs does not follow the same physical principles that supports mentioned analytical and numerical methods.Application of an innovative technology,Top-Down Modeling(TDM),is proposed for the analyses of unconventional resources.This technology is completely data-driven,incorporating field measurements(drilling data,well logs,cores,well tests,production history,etc.)to build comprehensive full field reservoir models. In this study,a Top-Down Model(TDM)was developed for a field in Weld County,Colorado,producing from Niobrara.The TDM was built using data from more than 145 wells.Well logs,production history,well design parameters and dynamic production constrains are the main data attributes that were used to perform data driven analysis.The workflow for Top- Down Modeling included generating a high-level geological model followed by reservoir delineation based on regional productivity,reserve and recovery estimation,field wide pattern recognition(based on fuzzy set theory),Key Performance Indicator(KPI)analysis(which estimates the degree of influence of each parameter on the field production),and finally history matching the production data from individual wells and production forecasting.The results of production analysis by Top-Down Modeling can provide insightful guidelines for better planning and decision making.
机译:非常规的碳氢化合物资源将在美国能源战略中发挥重要作用。用于分析非传统资源的转化工具和技术包括衰落曲线分析,曲线匹配,有时(在多产的资产的情况下)水库模拟。这些由于非传统储层中的流体流动不遵循支持提到的分析和数值方法的相同物理原则,方法尚未完全成功。提出了一种创新技术,自上而下建模(TDM)的应用,以进行分析非传统资源。这项技术完全是数据驱动的,包括现场测量(钻取数据,井日志,核心,井测试,生产历史等),以建立全面的全场储层模型。在这项研究中,对焊接县,科罗拉多州的田野开发了一项自上而下的模型(TDM),从Niobrara生产。使用来自145多家Wells.well日志,生产历史,设计参数和动态的数据建造了TDM生产约束是用于执行数据驱动分析的主要数据属性。用于自上而下的建模的工作流程包括生成高级地质模型,然后基于区域生产力,储备和恢复估计,领域广泛模式识别(基于模糊集理论),关键绩效指标(KPI)分析(估计每个参数对现场生产的影响程度),最后历史与各个井和生产预测的生产数据相匹配。生产分析结果自上而下的建模可以提供更好的规划和决策的洞察指南。

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