通过整合压裂后压力衰减分析和返排诊断裂缝注入测试方法,逐级进行水力裂缝和储层表征

IF 2.1 4区 工程技术 Q3 ENERGY & FUELS
D. Zeinabady, C. Clarkson
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引用次数: 1

摘要

压裂后压力衰减(PFPD)技术是一种低成本的方法,可以逐级进行水力压裂表征。PFPD数据的分析是复杂的,数据受到水力裂缝和储层性质的影响。文献中可用的分析方法过于简化;通常假设储层或裂缝性质沿水平井方向是恒定的,因此压力衰减数据趋势的变化仅归因于水力裂缝或储层性质。此外,通常使用类似于传统诊断性压裂注入测试(dfit)分析的方法,而忽略了主要水力压裂增产的关键机制。本文首先进行了概念数值模拟研究,以了解主段水力压裂的关键机理。然后建立了一个分析模型来解释水力裂缝的动态行为、泄漏、支撑剂分布、多裂缝以及支撑和非支撑关闭事件。该分析模型采用了一种新的直线分析(SLA)方法,可以逐级估算未支撑裂缝表面积与总裂缝表面积的比例。通过数值模拟结果验证了该方法的有效性。此外,为了考虑沿水平井的储层性质变化,PFPD模型与dfit -返排(DFIT-FBA)测试相结合,在水平段的某些点进行测试,以获得可靠的逐级水力压裂和储层表征方法。通过对Montney地层一口22段完井水平井的PFPD和DFIT-FBA数据进行验证,证明了该综合方法的实际应用。数值模拟研究表明,使用支撑剂并注入多个簇(形成多个裂缝)会导致多次闭合事件。在明显高于最小地应力的压力下,泵入期后关闭过程可能会提前开始。使用基于dfit的分析模型,忽略了支撑剂的存在,会导致水力裂缝和储层性质估计出现重大误差。本文研究的PFPD现场数据显示出与数值模拟案例相似的压力趋势。在DFIT-FBA数据的约束下,使用PFPD SLA方法逐级确定未支撑裂缝表面积与总裂缝表面积的比例。工程师可以利用这些信息实时优化水力压裂增产设计,优化井距,预测产量。这种诊断方法的成本和时间优势使其非常有吸引力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Stage-by-Stage Hydraulic Fracture and Reservoir Characterization through Integration of Post-Fracture Pressure Decay Analysis and the Flowback Diagnostic Fracture Injection Test Method
The post-fracture pressure decay (PFPD) technique is a low-cost method allowing for stage-by-stage hydraulic fracture characterization. The analysis of the PFPD data is complex, with data affected by both hydraulic fracture and reservoir properties. Available analysis methods in the literature are oversimplified; reservoir or fracture properties are often assumed to be constant along the horizontal well, and therefore changes in the trend of pressure decay data are attributed to hydraulic fracture or reservoir properties only. Moreover, methods analogous to those applied to the analysis of conventional diagnostic fracture injection tests (DFITs) are often used and ignore critical mechanisms involved in main-stage hydraulic fracture stimulation. A conceptual numerical simulation study was first conducted herein to understand the key mechanisms involved in main-stage hydraulic fracturing. An analytical model was then developed to account for the dynamic behavior of the hydraulic fracture, leakoff, proppant distribution, multiple fractures, and propped- and unpropped-closure events. The analytical model is cast in the form of a new straightline analysis (SLA) method that provides stage-by-stage estimates of the ratio of unpropped fracture surface area to total fracture surface area. The SLA method was validated against numerical simulation results. Moreover, to account for the variation of reservoir properties along the horizontal well, the PFPD model is integrated with DFIT-flowback (DFIT-FBA) tests, performed at some points along the lateral, to obtain a reliable stage-by-stage hydraulic fracture and reservoir characterization approach. The practical application of the proposed integrated approach was demonstrated using PFPD and DFIT-FBA data from a horizontal well completed in 22 stages in the Montney Formation. The numerical simulation study demonstrated that the use of proppant and injection into multiple clusters (creating multiple fractures) results in multiple closure events. The closure process may start early after the pump-in period at a pressure significantly higher than the minimum in-situ stress. Using DFIT-based analytical models, which ignore the presence of proppant, causes significant errors in hydraulic fracture and reservoir property estimation. The PFPD field data examined herein exhibited a similar pressure trend to the numerical simulation cases. The ratio of unpropped fracture surface area to total fracture surface area was determined stage by stage using the PFPD SLA method, constrained by DFIT-FBA data. Engineers can use this information to optimize the hydraulic fracture stimulation design in real time, optimize the well spacing, and forecast the production. The cost and time advantages of this diagnostic method make this approach very attractive.
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来源期刊
CiteScore
5.30
自引率
0.00%
发文量
68
审稿时长
12 months
期刊介绍: Covers the application of a wide range of topics, including reservoir characterization, geology and geophysics, core analysis, well logging, well testing, reservoir management, enhanced oil recovery, fluid mechanics, performance prediction, reservoir simulation, digital energy, uncertainty/risk assessment, information management, resource and reserve evaluation, portfolio/asset management, project valuation, and petroleum economics.
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