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Dimensionless Section-Level Cumulative Oil Vs. Pumped Fluid Normalization Plot in Unconventional Development

机译:无量纲级累积油与 在非传统发展中泵送的流体标准化图

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The volume of stimulation fluid injected during hydraulic fracturing is a key performance driver in the horizontal development of the Niobrara formation in the Denver-Julesburg (DJ) Basin, Colorado. Oil production per well generally increases with stimulation fluid volume. Often, operators normalize both production and fluid volume based on stimulated lateral length and investigate relationships using "perft" variables. However, data from well-based approaches commonly display such wide distributions that no useful relationships can be inferred. To improve data correlations, multivariate analysis normalizes for parameters such as thermal maturity, depth, depletion, proppant intensity, drawdown, geology and completion design. Although advancements in computing power have decreased cycle times for multivariate analysis, preparing a clean dataset for thousands of wells remains challenging. A proposed analytical method using publicly available data allows interpreters to see through the noise and find informative correlations. Using a data set of over 5000 wells, we aggregate cumulative oil production and stimulation fluid volumes to a per-section basis then normalize by hydrocarbon pore volume (HCPV) per section. Dimensionless section-level Cumulative Oil versus Stimulation Fluid Plots ("Normalization" or "N-Plot") present data distributions sufficiently well-defined to provide an interpretation and design basis of well spacing and stimulation fluid volumes for multi-well development. When coupled with geologic characterization, the trends guide further refinement of development optimization and well performance predictions. Two example applications using the N-Plot are introduced. The first involves construction of predictive production models and associated evaluation of alternative development scenarios with different combinations of well spacing and completion fluid intensity. The second involves "just-in-time" modification of fluid intensity for drilled but uncompleted wells (DUC's) to optimize cost-forward project economics in an evolving commodity price environment.
机译:在液压压裂期间注射的刺激液的体积是丹佛 - 朱尔斯堡(DJ)盆地的Niobrara形成水平开发中的关键性能驱动器。每次孔的油生产通常随着刺激流体体积而增加。通常,操作员基于刺激的横向长度对生产和流体体积进行正常化,并使用“完善”变量来研究关系。然而,来自基于良好的方法的数据通常显示不可推断出没有有用关系的广泛发行版。为了提高数据相关性,多变量分析标准化为热成熟度,深度,耗尽,支撑剂强度,绘制,地质和完成设计等参数。尽管计算能力的进步减少了多变量分析的周期时间,但是为数千个井的制备清洁数据集仍然具有挑战性。使用公开数据的建议的分析方法允许口译员通过噪声来看并找到信息性相关性。使用超过5000孔的数据集,我们将累积的油生产和刺激流体体积聚集到每条基础上,然后通过每段通过烃孔体积(HCPV)归一化。无量纲级累积油与刺激流体图(“归一化”或“N-Plot”)存在充分明确定义的数据分布,以提供井间距和刺激流体体积的解释和设计基础,用于多孔发育。当加上地质特征时,趋势指导进一步改进了发展优化和良好的性能预测。介绍了使用N-PLOT的两个示例应用程序。第一种涉及用井间距和完井流体强度的不同组合构建预测生产模型和相关评估。第二个涉及“立即”改进钻孔但未完成的井(DUC)的流体强度,以优化在不断变化的商品价格环境中的成本前进项目经济学。

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