{"title":"Advancement in Waterflood and EOR Performance Assessment and Optimization with Capacitance-Resistance Model in the Largest Oil Field, Thailand","authors":"R. Laochamroonvorapongse","doi":"10.2523/iptc-22862-ms","DOIUrl":null,"url":null,"abstract":"\n The main mechanism of waterflooding and enhanced oil recovery (EOR) is oil displacement by injected fluid; however, complexity in the geological system, limited understanding of interwell connectivity, vertical heterogeneity, and lack of injection and production controls lead to lower-than-expected flood performance. This study is aimed to assess and optimize the ongoing waterflood and polymer flooding performance in a mature S1 oil field in Thailand.\n The capacitance resistance model (CRM) is a physics-based reservoir model that derives interwell connectivity and reservoir properties solely from the input of production, injection, and pressure data. In this study, the rigorous workflow of CRM model coupled with fractional flow model was built by using Python language to dynamically perform the reservoir analysis focusing on the polymer pilot and mature waterflood areas. The reservoir connectivity map and reservoir properties were obtained from the CRM model matching, and the flood optimization plan was the output after coupling those two models.\n The CRM model provides good fittings of well production rates in case there is sufficient production data and the derived interwell connectivity is in good agreement with the interwell tracer results, the regional sedimentary supply direction, and waterflood analysis by reservoir engineers. The input of bottomhole pressure data from electric submersible pump (ESP) sensors can enhance the quality of CRM fittings, especially when reservoir is in the under-injection state. For the optimization study, well injection rates were adjusted with the objective function to maximize oil reserves, and the results signified a total incremental oil gain of 1 MMSTB approximately. The recommended waterflood optimization plan was implemented and is being evaluated in the field.\n The integrated CRM workflow could replace the 3D-conventional reservoir simulation model where it may contain high uncertainty of geological structures and characteristics. The CRM also enables the intensive waterflood and EOR assessment as well as flood performance optimization. This application would be a key to ensuring the success of the waterflood and EOR journey.","PeriodicalId":153269,"journal":{"name":"Day 2 Thu, March 02, 2023","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 2 Thu, March 02, 2023","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2523/iptc-22862-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
Abstract
The main mechanism of waterflooding and enhanced oil recovery (EOR) is oil displacement by injected fluid; however, complexity in the geological system, limited understanding of interwell connectivity, vertical heterogeneity, and lack of injection and production controls lead to lower-than-expected flood performance. This study is aimed to assess and optimize the ongoing waterflood and polymer flooding performance in a mature S1 oil field in Thailand.
The capacitance resistance model (CRM) is a physics-based reservoir model that derives interwell connectivity and reservoir properties solely from the input of production, injection, and pressure data. In this study, the rigorous workflow of CRM model coupled with fractional flow model was built by using Python language to dynamically perform the reservoir analysis focusing on the polymer pilot and mature waterflood areas. The reservoir connectivity map and reservoir properties were obtained from the CRM model matching, and the flood optimization plan was the output after coupling those two models.
The CRM model provides good fittings of well production rates in case there is sufficient production data and the derived interwell connectivity is in good agreement with the interwell tracer results, the regional sedimentary supply direction, and waterflood analysis by reservoir engineers. The input of bottomhole pressure data from electric submersible pump (ESP) sensors can enhance the quality of CRM fittings, especially when reservoir is in the under-injection state. For the optimization study, well injection rates were adjusted with the objective function to maximize oil reserves, and the results signified a total incremental oil gain of 1 MMSTB approximately. The recommended waterflood optimization plan was implemented and is being evaluated in the field.
The integrated CRM workflow could replace the 3D-conventional reservoir simulation model where it may contain high uncertainty of geological structures and characteristics. The CRM also enables the intensive waterflood and EOR assessment as well as flood performance optimization. This application would be a key to ensuring the success of the waterflood and EOR journey.