G. Chochua, A. Rudic, Amrendra Kumar, Aurélien Mainy, G. Woiceshyn
{"title":"用于水和气控制的旋风式自动入流控制装置:仿真驱动设计","authors":"G. Chochua, A. Rudic, Amrendra Kumar, Aurélien Mainy, G. Woiceshyn","doi":"10.2118/192723-MS","DOIUrl":null,"url":null,"abstract":"\n Horizontal wells are considered superior to vertical and deviated wells because they increase reservoir contact; however, they can cone unwanted fluids (gas, water) causing reduced oil recovery and early well abandonment. Inflow Control Devices (ICDs) are typically installed along the completion string to delay coning and restrict water/gas influx. Once the coning occurs, conventional ICDs, such as channels and orifices, were found to be inadequate in choking back the unwanted fluids. Thus, new types of \"autonomous\" ICDs, or AICDs, were developed that choke back unwanted fluids more than conventional ICDs. Conversely, such AICDs have limitations related to bulkiness, moving parts, wellsite adjustability, flow performance predictability, and erosion.\n To overcome these limitations, a new AICD, operating on a principle of a cyclone, was developed by a synergy of the latest numerical technologies, such as Computational Fluid Dynamics (CFD) utilizing a high-fidelity Large Eddy Simulation (LES) turbulence model, and Design of Experiments (DOE) techniques. This CFD-driven design optimization involved utilization of high-performance computing (HPC) coupled with experimental validation. A DOE matrix of CFD analyses runs was performed to identify a geometry that would generate significantly higher pressure drop for water and gas than for oil.\n Early multiphase testing on a prototype device validated the concept, and CFD was used to improve the understanding of the operating principle and hence the design. CFD was further used to extrapolate the flow performance to a wider range of operating conditions. An expanded flow performance map and the use of non-dimensional parameters led to the development of a mechanistic AICD performance model which further enhanced our understanding of AICDs and allowed reservoir software programs to evaluate the production performance of wells with AICDs versus wells with conventional ICDs or no inflow control. The overall result is the new cyclonic AICD presented herein which is: 1) relatively compact, 2) without moving parts, 3) erosion resistant, 4) superior in multiphase performance, 5) easily adjustable at the wellsite with many settings, 6) accurately modeled with CFD, and 7) easy to incorporate into state-of-the-art reservoir simulation models.","PeriodicalId":11014,"journal":{"name":"Day 1 Mon, November 12, 2018","volume":"13 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"Cyclone Type Autonomous Inflow Control Device for Water and Gas Control: Simulation-Driven Design\",\"authors\":\"G. Chochua, A. Rudic, Amrendra Kumar, Aurélien Mainy, G. Woiceshyn\",\"doi\":\"10.2118/192723-MS\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Horizontal wells are considered superior to vertical and deviated wells because they increase reservoir contact; however, they can cone unwanted fluids (gas, water) causing reduced oil recovery and early well abandonment. Inflow Control Devices (ICDs) are typically installed along the completion string to delay coning and restrict water/gas influx. Once the coning occurs, conventional ICDs, such as channels and orifices, were found to be inadequate in choking back the unwanted fluids. Thus, new types of \\\"autonomous\\\" ICDs, or AICDs, were developed that choke back unwanted fluids more than conventional ICDs. Conversely, such AICDs have limitations related to bulkiness, moving parts, wellsite adjustability, flow performance predictability, and erosion.\\n To overcome these limitations, a new AICD, operating on a principle of a cyclone, was developed by a synergy of the latest numerical technologies, such as Computational Fluid Dynamics (CFD) utilizing a high-fidelity Large Eddy Simulation (LES) turbulence model, and Design of Experiments (DOE) techniques. This CFD-driven design optimization involved utilization of high-performance computing (HPC) coupled with experimental validation. A DOE matrix of CFD analyses runs was performed to identify a geometry that would generate significantly higher pressure drop for water and gas than for oil.\\n Early multiphase testing on a prototype device validated the concept, and CFD was used to improve the understanding of the operating principle and hence the design. CFD was further used to extrapolate the flow performance to a wider range of operating conditions. An expanded flow performance map and the use of non-dimensional parameters led to the development of a mechanistic AICD performance model which further enhanced our understanding of AICDs and allowed reservoir software programs to evaluate the production performance of wells with AICDs versus wells with conventional ICDs or no inflow control. The overall result is the new cyclonic AICD presented herein which is: 1) relatively compact, 2) without moving parts, 3) erosion resistant, 4) superior in multiphase performance, 5) easily adjustable at the wellsite with many settings, 6) accurately modeled with CFD, and 7) easy to incorporate into state-of-the-art reservoir simulation models.\",\"PeriodicalId\":11014,\"journal\":{\"name\":\"Day 1 Mon, November 12, 2018\",\"volume\":\"13 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 1 Mon, November 12, 2018\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/192723-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, November 12, 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/192723-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Cyclone Type Autonomous Inflow Control Device for Water and Gas Control: Simulation-Driven Design
Horizontal wells are considered superior to vertical and deviated wells because they increase reservoir contact; however, they can cone unwanted fluids (gas, water) causing reduced oil recovery and early well abandonment. Inflow Control Devices (ICDs) are typically installed along the completion string to delay coning and restrict water/gas influx. Once the coning occurs, conventional ICDs, such as channels and orifices, were found to be inadequate in choking back the unwanted fluids. Thus, new types of "autonomous" ICDs, or AICDs, were developed that choke back unwanted fluids more than conventional ICDs. Conversely, such AICDs have limitations related to bulkiness, moving parts, wellsite adjustability, flow performance predictability, and erosion.
To overcome these limitations, a new AICD, operating on a principle of a cyclone, was developed by a synergy of the latest numerical technologies, such as Computational Fluid Dynamics (CFD) utilizing a high-fidelity Large Eddy Simulation (LES) turbulence model, and Design of Experiments (DOE) techniques. This CFD-driven design optimization involved utilization of high-performance computing (HPC) coupled with experimental validation. A DOE matrix of CFD analyses runs was performed to identify a geometry that would generate significantly higher pressure drop for water and gas than for oil.
Early multiphase testing on a prototype device validated the concept, and CFD was used to improve the understanding of the operating principle and hence the design. CFD was further used to extrapolate the flow performance to a wider range of operating conditions. An expanded flow performance map and the use of non-dimensional parameters led to the development of a mechanistic AICD performance model which further enhanced our understanding of AICDs and allowed reservoir software programs to evaluate the production performance of wells with AICDs versus wells with conventional ICDs or no inflow control. The overall result is the new cyclonic AICD presented herein which is: 1) relatively compact, 2) without moving parts, 3) erosion resistant, 4) superior in multiphase performance, 5) easily adjustable at the wellsite with many settings, 6) accurately modeled with CFD, and 7) easy to incorporate into state-of-the-art reservoir simulation models.