Novel in-Field Technique to Monitor and Optimize Asphaltene Remediation and Inhibition Job with Direct Field-to-Laboratory Correlation

A. Punase, Claudia Mazzeo, R. Garan, E. Vita, Ryan Kristensen, J. Wylde
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Abstract

Asphaltene precipitation and deposition is a major flow assurance issue faced by the oil and gas industry. The complex nature and non-uniform molecular structure of asphaltenes complicates efforts to accurately assess their stability. Moreover, developing test methodologies with strong laboratory-to-field correlation presents additional challenges. The focus of this study is to discuss the successful validation and application of a novel test method for determination and monitoring of asphaltene stability in a Gulf of Mexico deepwater field. Remediation and stimulation procedures were performed on a deep-water field in the Gulf of Mexico experiencing severe asphaltene deposition problems in the wellbore and near-wellbore region. This study evaluates the correlation between the thermo-electric properties as determined by Asphaltene Differential Aggregation Probe Testing (ADAPT) and dispersion tendencies of asphaltenes in treated and untreated crude oil samples at both laboratory and field environments. The remediation job was conducted through a multi-step process involving a coiled tubing clean out, solvent-soak, and continuous AI injection through downhole chemical injection tubing following the stimulation. Samples were collected prior to the start of treatment, during the initial flow-back of stimulation fluids, and over the course of one year following the stimulation. Field ADAPT measurements were performed to monitor the effect of continuous Asphaltene Inhibitor (AI) injection over time and validate the direct laboratory-to-field relationship. Higher ADAPT readings are indicative of a better dispersion state of the polar asphaltene fraction within the test sample. Hence, the pre-treatment samples were observed to have lower ADAPT values as compared to the flow-back samples collected after the solvent-soak stage. Stabilized higher readings were recorded for the samples analyzed in the next three months and a step-down trend was observed with reduction in AI dosage. Additionally, the amount of asphaltenes that precipitated from the field samples were also measured and followed an inverse relationship with the ADAPT values, corroborating the expected asphaltene stability behavior. Furthermore, differential pressure across the flowline was also monitored for this well to confirm the absence of asphaltene deposition throughout the assessment period. A strong correlation between the laboratory and field results obtained from this thermo-electric technique and its validation with other industry standard methods highlight the reliability and high degree of accuracy of the novel ADAPT method. With this study, an innovative method of assessing and monitoring the stability of asphaltenes and efficiency of an AI within the native crude oil medium is presented. The effectiveness of the technique to decipher and record variations during different stages of an asphaltene remediation job demonstrates its robustness and applicability as an efficient monitoring tool with great laboratory-to-field correlation.
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新的现场技术监测和优化沥青质修复和抑制工作与直接现场与实验室的相关性
沥青质的沉淀和沉积是油气行业面临的主要流动保障问题。沥青质复杂的性质和不均匀的分子结构使准确评估其稳定性的工作复杂化。此外,开发具有很强的实验室到现场相关性的测试方法提出了额外的挑战。本研究的重点是讨论一种新的测试方法的成功验证和应用,以确定和监测墨西哥湾深水油田的沥青质稳定性。在墨西哥湾的一个深水油田,井筒和近井区域出现了严重的沥青质沉积问题,进行了修复和增产作业。本研究评估了沥青质差异聚集探针测试(ADAPT)确定的热电性质与实验室和现场环境下处理和未处理原油样品中沥青质的分散趋势之间的相关性。该修复作业是一个多步骤的过程,包括连续油管清洗、溶剂浸泡和增产后通过井下化学注入油管连续注入AI。在压裂作业开始前、压裂液初始返排期间以及压裂作业结束后一年的时间内采集了样品。现场进行了ADAPT测量,以监测连续注入沥青烯抑制剂(AI)的效果,并验证实验室与现场的直接关系。ADAPT读数越高,表明极性沥青质馏分在测试样品中的分散状态越好。因此,与溶剂浸泡阶段后收集的回流样品相比,观察到预处理样品具有较低的ADAPT值。在接下来的三个月里,分析的样品记录了稳定的较高读数,并且随着人工智能剂量的减少,观察到下降趋势。此外,还测量了从现场样品中析出的沥青质量,并与ADAPT值呈反比关系,从而证实了预期的沥青质稳定性行为。此外,还对该井的整个流线上的压差进行了监测,以确认在整个评估期间没有沥青质沉积。从该热电技术获得的实验室和现场结果之间的强相关性及其与其他工业标准方法的验证突出了新型ADAPT方法的可靠性和高度准确性。通过这项研究,提出了一种评估和监测沥青质稳定性和人工智能在天然原油介质中的效率的创新方法。该技术能够有效地破译和记录沥青质修复工作不同阶段的变化,证明了它作为一种有效的监测工具的鲁棒性和适用性,具有很强的实验室到现场的相关性。
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