{"title":"基于纳米通信的地下油藏纳米传感器流路映射","authors":"Liuyi Jin, Zhipei Yan, L. Zuo, R. Stoleru","doi":"10.1145/3411295.3411309","DOIUrl":null,"url":null,"abstract":"Oil reservoir exploration is booming, given the increasing energy demand worldwide. The existence of Impermeable Regions (IR) in the oil reservoir (i.e., underground areas that allow only few hydrocarbons-collecting fluids to pass through) still hinders current production performance to a great extent. Research efforts have been invested into IR detection and mapping. The state of the art solution [1] leverages nanoscale sensor networks to approximately characterize the location of a single IR in the underground oil reservoir. However, the characterization accuracy is rather low. In addition, existing solutions are not applicable to more heterogeneous reservoirs, which reflects, in fact, a more realistic problem scenario. In this paper, we investigate and address the limitations of state of the art solutions in two aspects: 1) we provide a sub-terahertz (THz) communication channel to reflect realism of nanocommunication in the underground; 2) we develop a sensor path (i.e., simulated streamlines along which sensors are assumed to flow) reconstruction workflow to map a more heterogeneous reservoir with more IRs. Through simulations, we show that our proposed solution achieves an improvement of IRs mapping performance, when compared to the state of the art solution.","PeriodicalId":93611,"journal":{"name":"Proceedings of the 7th ACM International Conference on Nanoscale Computing and Communication : Virtual Conference, September 23-25, 2020 : NanoCom 2020. ACM International Conference on Nanoscale Computing and Communication (7th : 2020 :...","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2020-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"NanoCommunication-based flow path mapping for NanoSensors in underground oil reservoirs\",\"authors\":\"Liuyi Jin, Zhipei Yan, L. Zuo, R. Stoleru\",\"doi\":\"10.1145/3411295.3411309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Oil reservoir exploration is booming, given the increasing energy demand worldwide. The existence of Impermeable Regions (IR) in the oil reservoir (i.e., underground areas that allow only few hydrocarbons-collecting fluids to pass through) still hinders current production performance to a great extent. Research efforts have been invested into IR detection and mapping. The state of the art solution [1] leverages nanoscale sensor networks to approximately characterize the location of a single IR in the underground oil reservoir. However, the characterization accuracy is rather low. In addition, existing solutions are not applicable to more heterogeneous reservoirs, which reflects, in fact, a more realistic problem scenario. In this paper, we investigate and address the limitations of state of the art solutions in two aspects: 1) we provide a sub-terahertz (THz) communication channel to reflect realism of nanocommunication in the underground; 2) we develop a sensor path (i.e., simulated streamlines along which sensors are assumed to flow) reconstruction workflow to map a more heterogeneous reservoir with more IRs. Through simulations, we show that our proposed solution achieves an improvement of IRs mapping performance, when compared to the state of the art solution.\",\"PeriodicalId\":93611,\"journal\":{\"name\":\"Proceedings of the 7th ACM International Conference on Nanoscale Computing and Communication : Virtual Conference, September 23-25, 2020 : NanoCom 2020. ACM International Conference on Nanoscale Computing and Communication (7th : 2020 :...\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 7th ACM International Conference on Nanoscale Computing and Communication : Virtual Conference, September 23-25, 2020 : NanoCom 2020. 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NanoCommunication-based flow path mapping for NanoSensors in underground oil reservoirs
Oil reservoir exploration is booming, given the increasing energy demand worldwide. The existence of Impermeable Regions (IR) in the oil reservoir (i.e., underground areas that allow only few hydrocarbons-collecting fluids to pass through) still hinders current production performance to a great extent. Research efforts have been invested into IR detection and mapping. The state of the art solution [1] leverages nanoscale sensor networks to approximately characterize the location of a single IR in the underground oil reservoir. However, the characterization accuracy is rather low. In addition, existing solutions are not applicable to more heterogeneous reservoirs, which reflects, in fact, a more realistic problem scenario. In this paper, we investigate and address the limitations of state of the art solutions in two aspects: 1) we provide a sub-terahertz (THz) communication channel to reflect realism of nanocommunication in the underground; 2) we develop a sensor path (i.e., simulated streamlines along which sensors are assumed to flow) reconstruction workflow to map a more heterogeneous reservoir with more IRs. Through simulations, we show that our proposed solution achieves an improvement of IRs mapping performance, when compared to the state of the art solution.