Opportunities and Uncertainty Mitigation Base on Survivor Bias in a Mature Field: Cañadón León, San Jorge Basin, Argentina

A. E. Legarreta, Rosina Cristina Barberis, F. Schein, L. Martino, S. Gandi
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Abstract

Survivorship bias is a well-known tendency to overweight available data and underestimate the missing information. Cañadón León in San Jorge basin, Argentina is a waterflooded field with a current water-cut of 95% where innovative recovery strategies such as Chemical Enhanced Oil Recovery (cEOR) become a condition for further development. Data acquisition is often biased towards the best reservoirs, leading to major uncertainty in assessing opportunities in mature fields. After 70 years of primary oil production and water injection, the study aims to evaluate the remaining opportunity, which leads to a double challenge: Estimation of bypassed oil during the inefficient waterflooding process because of poor mobility ratio and the potential of marginal reservoirs. Initial stage field exploitation and data acquisition at early stages of development aimed mainly to characterize the higher oil-saturation zones with better petrophysical properties, leading to a lack of data on marginal reservoirs which become critical targets for mature reservoirs analysis. The data interpretation within a semi regional geological framework to build the static model, allowed a representative construction of poorly characterized reservoirs due to survivorship bias effect. Several hypotheses were evaluated with dynamic simulation to avoid assuming recoverable oil based on survivorship bias due to missing information in secondary targets. Integration of what-if scenarios, both static and dynamic, and assessment of uncertainty provided a better understanding of critical constraints and optimum ranges of variability to analyze cEOR with polymer injection. A wide variety of fluid saturation scenarios, mobility ratios and reservoir properties were considered to quantify the field potential. Sensitivity analysis helped to identify the most relevant uncertainties in history matching and reliability in forecast: Primary gas cap contact and its expansion, water-oil contact, the transition zone (oil-water system), fluid mobility ratios and polymer characteristics. A major benefit from polymer injection is CO2 emissions reduction per barrel of oil by more than 40% compared to water injection, reducing project carbon footprint. Development strategy achieves a short-term incremental recovery factor of 10% with a total of 68 wells in 20 injection patterns (considering a period between 3 to 6 years due to oil production acceleration). This methodology allowed to establish the foundations for development strategies based on multi-modelling within conceptual geological frameworks reflecting the impact of the recognized uncertainties. This technique does not allow to determine the unknowns, but it does allow to estimate their impact.
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成熟油田中基于幸存者偏差的机会和不确定性缓解:Cañadón León, San Jorge盆地,阿根廷
生存偏差是一种众所周知的倾向,即超重现有数据并低估缺失信息。Cañadón León位于阿根廷San Jorge盆地,是一个水淹油田,目前含水率为95%,采用化学提高采收率(cEOR)等创新采收率策略成为进一步开发的条件。数据采集往往偏向于最佳储层,导致在评估成熟油田的机会时存在很大的不确定性。经过70年的一次采油和注水,该研究旨在评估剩余的机会,这带来了双重挑战:由于流动性比差和边际油藏潜力,在低效水驱过程中,如何估计旁路油。初期油田开发和早期数据采集主要是为了描述具有较好岩石物性的高含油饱和度区域,导致缺乏边缘储层数据,而边缘储层是成熟储层分析的关键目标。在半区域地质框架内进行数据解释以建立静态模型,由于生存偏差效应,可以对特征不佳的储层进行代表性构建。为了避免二次目标信息缺失导致的生存偏差,采用动态模拟的方法对多个假设进行了评估。通过对静态和动态假设情景的整合,以及对不确定性的评估,可以更好地理解关键约束条件和最佳变异性范围,从而分析聚合物注入的cEOR。考虑了各种流体饱和度、流度比和储层性质来量化油田潜力。敏感性分析有助于识别历史匹配中最相关的不确定性和预测的可靠性:原生气顶接触面及其膨胀、水-油接触面、过渡区(油水体系)、流体流度比和聚合物特性。与注水相比,聚合物注入的一个主要好处是每桶石油的二氧化碳排放量减少了40%以上,减少了项目的碳足迹。开发策略通过20种注入模式共68口井实现了10%的短期增量采收率(考虑到由于石油生产加速,周期为3至6年)。这种方法可以在反映公认的不确定因素的影响的概念地质框架内建立基于多重模型的发展战略的基础。这种技术不允许确定未知,但它允许估计其影响。
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