AUTOMATED WORKFLOW TO INDICATE RESERVOIR CONNECTIVITY THROUGH ASPHALTENE EQUILIBRIUM

Melanie A Jensen, Schlumberger, Lalitha Venkataramanan, Li Chen, S. Bose, P. Tilke, O. Mullins
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Abstract

The evaluation of downhole fluid analysis (DFA) measurements of asphaltene gradients provides the ability to determine the extent of asphaltene equilibrium and the operative reservoir fluid geodynamics (RFG) processes. Typically, equilibrium of reservoir fluids indicates reservoir connectivity, a primary concern in field development planning. Currently, the modeling of asphaltene gradients is done through the manual evaluation of the DFA optical density gradients. The optical density measurements are fit to an equation of state (EOS), such as the Flory-Huggins-Zuo EOS, and evidence for asphaltene equilibrium is concluded if the inferred asphaltene diameter corresponds to that of the Yen-Mullins model for asphaltene composition. In this work, we present an automated Bayesian algorithm that proposes multiple hypotheses for the state of asphaltene equilibrium. The proposed hypotheses honor DFA measurements; physical models for asphaltenes in equilibrium, such as the Yen-Mullins model; and prior domain knowledge of the reservoir, such as geological layers, faults, and flow units. The leading hypotheses are reported, and evidence for or against asphaltene equilibrium is concluded from inferred quantities. Our proposed method provides a faster way for domain experts to explore different reservoir realizations that honor the theory of asphaltenes gradients and previous knowledge about the reservoir. We verify our novel method on three case studies that are undergoing different RFG processes through comparison of the interpretation done by domain experts. While there are many reservoir complexities associated with each case study, we focus on whether the underlying RFG process corresponds to the asphaltenes in equilibrium. The first case study is a light oil reservoir in the Norwegian North Sea that is mostly in fluid equilibrium with exceptions at the flanks. The second case study is a black oil reservoir that has undergone a fault block migration after the reservoir fluids had a chance to achieve equilibrium. The last case study is a black oil reservoir in quasi-equilibrium due to biodegradation in the lower portion of the well.
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自动化工作流程,通过沥青质平衡指示储层连通性
通过对沥青质梯度的井下流体分析(DFA)测量结果进行评估,可以确定沥青质平衡的程度和有效的储层流体地球动力学(RFG)过程。通常,储层流体的平衡表明储层的连通性,这是油田开发规划中主要关注的问题。目前,沥青质梯度的建模是通过人工评估DFA光密度梯度来完成的。光学密度测量符合状态方程(EOS),如Flory-Huggins-Zuo EOS,如果推断的沥青质直径与Yen-Mullins沥青质组成模型相对应,则可以得出沥青质平衡的证据。在这项工作中,我们提出了一种自动贝叶斯算法,该算法提出了沥青质平衡状态的多个假设。提出的假设支持DFA测量;沥青质的平衡物理模型,如Yen-Mullins模型;以及储层的先验领域知识,如地质层、断层和流动单元。报告了主要的假设,并从推断的量中得出了支持或反对沥青质平衡的证据。我们提出的方法为领域专家提供了一种更快的方法,可以根据沥青质梯度理论和先前对储层的了解来探索不同的储层实现。我们通过比较领域专家所做的解释,在三个正在经历不同RFG过程的案例研究中验证了我们的新方法。虽然每个案例研究都有许多油藏的复杂性,但我们关注的是底层的RFG过程是否与平衡的沥青质相对应。第一个案例研究是挪威北海的一个轻油油藏,除侧翼外,该油藏大部分处于流体平衡状态。第二个案例研究是一个黑色油藏,在储层流体有机会达到平衡后,经历了断块运移。最后一个案例研究是由于井下部的生物降解而处于准平衡状态的黑色油藏。
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