MRC开发战略最优有效井长评价建模方法

A. Shbair, Djamal Kherroubi, Ian Bosivert, F. Noordin, Raphael Melo, Khalid Mohammed Abdalaziz
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引用次数: 0

摘要

油藏最大接触面(MRC)泄液技术作为油藏开发的一种极具吸引力的解决方案,已被引入并实施,以加速生产/注入,同时优化开发成本。本文的主要目的是提供一个评估最佳井长(Lopt)和MRC井评价的工作流程。此外,通过对某大型油田的研究,并结合实际有效井长(Leff)的规划实施方案,强调影响实际有效井长(Leff)的因素,以缓解有效井长较差的井。提出了一种基于流量率与产能指数(PI)的比例关系来预测最佳井长的新方法。该方法使用静态井数据(如轨迹、储层/流体性质、垂直和下部完井)以及动态数据(如地面试井数据和井下温度测量数据)构建的稳态井建模包。输出结果是沿轨迹的油流入速率、PI和生产曲线。为了提高灵敏度,通过Excel-Macro实现了自动井模型基础计算,以方便实现不同的井筒设计、渗透率范围和油管尺寸。其次,利用监测工具综合考虑影响有效井长的几个因素,对水平井进行评价。在实施MRC钻井之前,资产团队必须评估其油藏设置的最佳井长(Lopt),其中水平段的一定限制表明摩擦损失增加,增量(Q, PI)不再有利。理论模型表明,生产力和速率与水平长度成正比。而现场井监测数据显示,有效长度很少达到100%。研究结果证明了该工具在预测Lopt方面的有效性,并能够减少多种情况下的模拟运行/工作量。对于所研究的储层,根据渗透率、流体性质、完井尺寸和地面背压的不同,Lopt的范围在9000到16000英尺之间。研究发现,油管直径对流体通量有重要影响,而井筒直径的影响可以忽略不计。通过对1800 - 10000英尺的常规井和MRC井的现场研究进行工作流程评估,得出了影响实际有效井长的重要因素:井位(多孔/致密)、跟趾效应、钻井时损坏、生产/注入速度、赤脚与完井、钻井后的酸刺激、由于井况和产量限制(Spinner阈值)导致的井可达性。该工具将有助于初步评估,考虑储层环境和多种完井方案,确定MRC的最佳井长。此外,该应用程序可以扩展到与动态模拟集成,作为优化完井设计的强大工具,以适应未来的条件。此外,现场案例设置了一个通用的工作流程,用于确认可能影响Leff和评估MRC性能的因素。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Modelling Approach of Optimum and Effective Well Length Evaluation for MRC Development Strategy.
Maximum Reservoir Contact (MRC) drains have been introduced and implemented as an attractive solution in reservoir developments to accelerate production/injection while optimizing the development costs. The main objective of this paper is to provide a workflow to assess the optimum well length (Lopt) and MRC wells evaluation. In addition, it aims to highlight the factors affecting actual Effective well length (Leff) based on a study performed on a giant oil field and the planned execution plans to mitigate wells with poor effective well length. A new approach is proposed to predict the optimum well length based on the proportionality of flux rates and productivity index (PI). The approach uses steady-state well modelling packages built using the static well data such as trajectories, reservoir/fluid properties, vertical and lower completion tuned with dynamic data such as surface well test data and downhole P& T measurements. Output results are oil influx rates along the trajectory, PI and production profiles. For the sensitivities, an automated well model base calculation was implemented through an Excel-Macro to facilitate performing different realizations of wellbore design, permeability ranges, and tubing sizes. Next, the evaluation of horizontal wells was assessed utilizing surveillance tools with the integration of the several factors affecting the effective well length. Prior to implementing MRC drilling, the asset team must assess the optimum well length (Lopt) for their reservoir settings where a certain limit for horizontal section indicates an increase in frictional losses and increment (Q, PI) is no longer favorable. Theoretical models indicate productivity and rates proportionality with horizontal length. While field case evidence of wells surveillance show effective length is rarely 100%. The findings proved the tool's efficiency to predict Lopt with the capability to reduce simulation runs/efforts for multiple scenarios. For the studied reservoirs, the Lopt was inferred to be in the range of 9000 up to 16,000 ft depending on the permeability, fluid properties, completion size and surface back pressure. Tubing diameter size was found to have a major influence on the flux rate, while wellbore diameter had a negligible impact. The workflow assessment on field studies with average conventional wells and MRC wells length of 1800 ft-10,000 ft inferred significant factors affecting actual well effective length to be: Well placement (Porous/dense), Heel-toe effects, Damage while drilling, production/Injection rate, Barefoot vs. completion, acid Stimulation after drilling, Well accessibility due to hole condition and production rate limits (Spinner threshold). The tool will help in the preliminary assessment to decide the optimum well length for the MRC, considering the reservoir settings and multiple completion options. In addition, the application can be extended to integrate with dynamic simulation as a robust tool to optimize completion design to be fit for future conditions. Furthermore, the field case set a generic workflow for confirming factors that may impact the Leff and evaluate MRC performance.
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