{"title":"MOC - ROZ CO2混合驱ROZ产量预测分析方法","authors":"D. W. Hampton, Ahmed Wagia-Alla","doi":"10.2118/209365-ms","DOIUrl":null,"url":null,"abstract":"\n Residual Oil Zone (ROZ) refers to a formation whose discovery saturation equals the rock's residual oil saturation. The ROZ makes up an excellent target for CO2 flooding since this oil is immovable by primary and secondary production processes. The San Andres ROZ has been recognized as an extensive residual oil saturated fairway in the Permian created during the Leonardian uplift, which caused spillage from the natural traps (Melzer, 2006). It has been developed through CO2 flooding in several fields across the Permian, including the Denver Unit in the Wasson San Andres formation, where it was developed years after the Main Oil Column (MOC). Both zones are producing from commingled producers and are flooded by commingled or dedicated injectors. This commingled configuration presents a challenge in discerning the production coming from each zone. In this paper, we will present an analytical approach to distinguish between MOC and ROZ production without the need for numerical simulation or costly well interventions such as production logging or zonal isolation.\n A sector of the Denver Unit's CO2 flood was used as an example in this paper. Dimensionless analysis, which entails normalizing production and injection to the target pore volume, was used along with the Pulser process (Liu, Sahni, and Hsu, 2014; informal communication with Deepak Gupta, 2019) to history-match MOC production and then extrapolate it using zonal injection obtained from injection profile logs. This calculated MOC production is then subtracted from the total production to calculate ROZ production, with its dimensionless response function fitted with Pulser for forecasting. Additionally, a fully compositional numerical simulation of the same area was history-matched and used to validate the approach mentioned above.\n The results of the analytical approach showed excellent agreement with the numerical simulation results and with historical performance through multiple years. A few challenges presented themselves, such as pattern-to-pattern interference, the quality of injection profile logs, and pattern reconfigurations, which we will discuss below along with limitations and assumptions that must be considered when using this approach.\n The methodology presented in this paper presents a simple method to allocate and forecast MOC and ROZ performance individually despite changes in injection throughput, based on injection distribution without the need for complex simulation or costly well configuration. This approach could also be applied to any commingled flood that meets the criteria outlined in this paper.","PeriodicalId":10935,"journal":{"name":"Day 1 Mon, April 25, 2022","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2022-04-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Analytical Method for Forecasting ROZ Production in a Commingled MOC and ROZ CO2 Flood\",\"authors\":\"D. W. Hampton, Ahmed Wagia-Alla\",\"doi\":\"10.2118/209365-ms\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Residual Oil Zone (ROZ) refers to a formation whose discovery saturation equals the rock's residual oil saturation. The ROZ makes up an excellent target for CO2 flooding since this oil is immovable by primary and secondary production processes. The San Andres ROZ has been recognized as an extensive residual oil saturated fairway in the Permian created during the Leonardian uplift, which caused spillage from the natural traps (Melzer, 2006). It has been developed through CO2 flooding in several fields across the Permian, including the Denver Unit in the Wasson San Andres formation, where it was developed years after the Main Oil Column (MOC). Both zones are producing from commingled producers and are flooded by commingled or dedicated injectors. This commingled configuration presents a challenge in discerning the production coming from each zone. In this paper, we will present an analytical approach to distinguish between MOC and ROZ production without the need for numerical simulation or costly well interventions such as production logging or zonal isolation.\\n A sector of the Denver Unit's CO2 flood was used as an example in this paper. Dimensionless analysis, which entails normalizing production and injection to the target pore volume, was used along with the Pulser process (Liu, Sahni, and Hsu, 2014; informal communication with Deepak Gupta, 2019) to history-match MOC production and then extrapolate it using zonal injection obtained from injection profile logs. This calculated MOC production is then subtracted from the total production to calculate ROZ production, with its dimensionless response function fitted with Pulser for forecasting. Additionally, a fully compositional numerical simulation of the same area was history-matched and used to validate the approach mentioned above.\\n The results of the analytical approach showed excellent agreement with the numerical simulation results and with historical performance through multiple years. A few challenges presented themselves, such as pattern-to-pattern interference, the quality of injection profile logs, and pattern reconfigurations, which we will discuss below along with limitations and assumptions that must be considered when using this approach.\\n The methodology presented in this paper presents a simple method to allocate and forecast MOC and ROZ performance individually despite changes in injection throughput, based on injection distribution without the need for complex simulation or costly well configuration. This approach could also be applied to any commingled flood that meets the criteria outlined in this paper.\",\"PeriodicalId\":10935,\"journal\":{\"name\":\"Day 1 Mon, April 25, 2022\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-04-18\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 1 Mon, April 25, 2022\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/209365-ms\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 1 Mon, April 25, 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/209365-ms","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
摘要
剩余油带是指发现饱和度等于岩石剩余油饱和度的地层。ROZ是二氧化碳驱油的绝佳目标,因为这种油在一次和二次生产过程中都是不可移动的。San Andres ROZ被认为是在Leonardian隆起期间形成的二叠纪广泛的残余油饱和通道,导致天然圈闭溢出(Melzer, 2006)。在二叠纪盆地的几个油田,包括Wasson San Andres地层的Denver单元,它是在主油柱(MOC)开发多年后开发的。这两个区域都是由混合生产商生产的,并由混合或专用注入器进行注水。这种混合结构给识别每个层的产出带来了挑战。在本文中,我们将提出一种分析方法来区分MOC和ROZ产量,而不需要数值模拟或昂贵的油井干预措施,如生产测井或层间隔离。本文以丹佛机组某部门的CO2洪水为例。无因次分析,需要将生产和注入到目标孔隙体积,与Pulser工艺一起使用(Liu, Sahni, and Hsu, 2014;与Deepak Gupta(2019年)进行非正式沟通,以匹配MOC产量的历史数据,然后使用从注入剖面测井中获得的分层注入进行推断。然后将计算出的MOC产量从总产量中减去,计算出ROZ产量,并将其无因次响应函数拟合为Pulser进行预测。此外,对同一区域进行了历史匹配的全成分数值模拟,并用于验证上述方法。分析方法的结果与数值模拟结果和多年来的历史性能具有很好的一致性。一些挑战出现了,比如模式对模式的干扰、注入剖面日志的质量和模式重新配置,我们将在下面讨论这些问题,以及使用这种方法时必须考虑的限制和假设。本文提出的方法提供了一种简单的方法,可以根据注入分布分别分配和预测MOC和ROZ性能,而不需要复杂的模拟或昂贵的井配置。这种方法也可以应用于任何符合本文概述的标准的混合型洪水。
Analytical Method for Forecasting ROZ Production in a Commingled MOC and ROZ CO2 Flood
Residual Oil Zone (ROZ) refers to a formation whose discovery saturation equals the rock's residual oil saturation. The ROZ makes up an excellent target for CO2 flooding since this oil is immovable by primary and secondary production processes. The San Andres ROZ has been recognized as an extensive residual oil saturated fairway in the Permian created during the Leonardian uplift, which caused spillage from the natural traps (Melzer, 2006). It has been developed through CO2 flooding in several fields across the Permian, including the Denver Unit in the Wasson San Andres formation, where it was developed years after the Main Oil Column (MOC). Both zones are producing from commingled producers and are flooded by commingled or dedicated injectors. This commingled configuration presents a challenge in discerning the production coming from each zone. In this paper, we will present an analytical approach to distinguish between MOC and ROZ production without the need for numerical simulation or costly well interventions such as production logging or zonal isolation.
A sector of the Denver Unit's CO2 flood was used as an example in this paper. Dimensionless analysis, which entails normalizing production and injection to the target pore volume, was used along with the Pulser process (Liu, Sahni, and Hsu, 2014; informal communication with Deepak Gupta, 2019) to history-match MOC production and then extrapolate it using zonal injection obtained from injection profile logs. This calculated MOC production is then subtracted from the total production to calculate ROZ production, with its dimensionless response function fitted with Pulser for forecasting. Additionally, a fully compositional numerical simulation of the same area was history-matched and used to validate the approach mentioned above.
The results of the analytical approach showed excellent agreement with the numerical simulation results and with historical performance through multiple years. A few challenges presented themselves, such as pattern-to-pattern interference, the quality of injection profile logs, and pattern reconfigurations, which we will discuss below along with limitations and assumptions that must be considered when using this approach.
The methodology presented in this paper presents a simple method to allocate and forecast MOC and ROZ performance individually despite changes in injection throughput, based on injection distribution without the need for complex simulation or costly well configuration. This approach could also be applied to any commingled flood that meets the criteria outlined in this paper.