针对在变压条件下生产的致密油藏应用递减曲线分析的新方法

IF 3.2 3区 工程技术 Q1 ENGINEERING, PETROLEUM
SPE Journal Pub Date : 2023-11-17 DOI:10.2118/218016-pa
Leopoldo Matias Ruiz Maraggi, Mark P. Walsh, Larry W. Lake
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引用次数: 0

摘要

递减曲线模型本质上假定井底流动压力(BHP)是恒定的。对于许多非常规油井来说,这一假设并不可靠。因此,应用递减曲线模型可能会导致不正确的流态识别和最终采收率(EUR)估算。本研究提出了一种将可变 BHP 条件与递减曲线模型相结合的新技术,并将其结果与传统的递减曲线分析(DCA)进行了比较。不过,我们使用含有误差的井底压力和初始储层压力对该技术进行了验证。该算法包括三次连续优化。在每次优化中,该算法都会估算 (1) 井下曲线模型参数、(2) BHP 和 (3) 初始储层压力。合成示例的结果导致了精确的生产历史匹配以及对初始储层压力和 BHP 历史的修正估计。最后,我们比较了该技术与传统 DCA 在以下方面的结果:(a) 模型参数;(b) 流态识别;(c) 生产历史匹配;(d) 使用三种递减曲线模型的致密油井欧元:对于合成情况,该算法对模型参数和真实初始储层压力的估计误差不超过 2%。此外,该方法还能重新生成真实的必发888官网登录入口历史,并提供出色的生产历史匹配。对致密油井的分析表明,新方法可以清楚地识别出油井中存在的流态,而当 BHP 发生变化时,使用传统 DCA 很难检测到这些流态。相比之下,应用传统的 DCA 方法在估计模型参数时会出现相当大的误差,而且生产数据的历史匹配性很差。最后,这项工作表明,与仅使用速率时间数据相比,将可变 BHP 纳入衰退曲线模型可获得更准确的生产历史匹配和 EUR 值。此外,该方法还能处理 BHP 和初始储层压力的误差,并提供这些变量的修正估计值。该技术计算速度快,与传统 DCA 相比,能更准确地匹配和预测非常规井的产量。这项工作的主要贡献在于,我们的变压 DCA 解决方案具有显著的简便性和稳健性。最后,我们开发了一个基于网络的应用程序,让读者亲身体验这项新技术。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A New Approach to Apply Decline-Curve Analysis for Tight-Oil Reservoirs Producing Under Variable Pressure Conditions

Decline-curve models inherently assume that the bottomhole flowing pressure (BHP) is constant. This is a poor assumption for many unconventional wells. For this reason, the application of decline-curve models might lead to incorrect flow regime identification and estimated ultimate recovery (EUR). This work presents a novel technique that combines variable BHP conditions with decline-curve models and compares its results with traditional decline-curve analysis (DCA) for both synthetic and tight-oil wells.

Using superposition, we generate a synthetic rate example using the constant-pressure solution of the diffusivity equation for a slightly compressible fluid (decline-curve model) along with a BHP history. However, we validate the technique using bottomhole and initial reservoir pressures that contain errors. The algorithm consists of three sequential optimizations. In each optimization, the algorithm estimates (1) the decline-curve model parameters, (2) the BHP, and (3) the initial reservoir pressure. The result of the synthetic example leads to an accurate production history match and corrected estimates of the initial reservoir pressure and the BHP history. Finally, we compare the results of the technique with traditional DCA in terms of (a) the model parameters, (b) flow regime identification, (c) production history matches, and (d) EUR for tight-oil wells using three decline-curve models: 1D single-phase constant-pressure solution of the diffusivity equation for a slightly compressible fluid, logistic growth model, and Arps hyperbolic relation.

For the synthetic case, the algorithm estimates the model parameters and the true initial reservoir pressure within a 2% error. In addition, the method regenerates the true BHP history and provides an excellent production history match. The analysis of the tight-oil wells shows that the new approach clearly identifies the flow regimes present in the well, which can be difficult to detect using traditional DCA when the BHP varies. In contrast, the application of traditional DCA shows considerable errors in the estimation of the model’s parameters and a poor history match of the production data. Finally, this work shows that incorporating variable BHP into the decline-curve models leads to more accurate production history matches and EUR values compared to using only rate-time data.

This paper illustrates a workflow that incorporates variable BHP conditions for any decline-curve model. Moreover, the approach can handle errors in both the BHP and the initial reservoir pressure and provides corrected estimates of these variables. The technique is computationally fast and history matches and forecasts the production of unconventional wells more accurately than traditional DCA. The major contribution of this work is the remarkable simplicity yet robustness of our solution to variable-pressure DCA. Finally, we developed a web-based application to provide the readers with a hands-on experience of this new technique.

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来源期刊
SPE Journal
SPE Journal 工程技术-工程:石油
CiteScore
7.20
自引率
11.10%
发文量
229
审稿时长
4.5 months
期刊介绍: Covers theories and emerging concepts spanning all aspects of engineering for oil and gas exploration and production, including reservoir characterization, multiphase flow, drilling dynamics, well architecture, gas well deliverability, numerical simulation, enhanced oil recovery, CO2 sequestration, and benchmarking and performance indicators.
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