Muzaffar Mohamdally, M. Soroush, M. Zeidouni, D. Alexander, Donnie Boodlal
{"title":"基于电容模型的故障泄漏评估","authors":"Muzaffar Mohamdally, M. Soroush, M. Zeidouni, D. Alexander, Donnie Boodlal","doi":"10.2118/191250-MS","DOIUrl":null,"url":null,"abstract":"\n Fault transmissibility and leakage have significant implications for field development during both primary and post-primary recovery. Whether the fault is sealing or not can directly determine the sweep efficiency and the fate of injected fluids. In addition, fault transmissivity affect the accuracy of in-place volume calculations from material balance techniques. In this paper dynamic data was used to determine transmissibility and leakage of the faults via Capacitance Model (CM).\n The CM has been developed from linear productivity model and material balance equation. Its inputs are production/injection rates and bottomhole pressure data (if available). The CM has weight factor for each well pair which determines the degree of connectivity between that pair. These weight factors were used and correlated to the fault transmissibility in this paper. Also, the CM was modified to incorporate the leakage in the system. New term, called leakage factor, was added for each well in the equation.\n The model was examined through applying to several synthetic field data generated by CMG software. In synthetic fields, different faults with different throw and transmissibility were built and across the fault transmissibility was evaluated by the model. For creating leaking fault, upward leakage and flow along the fault were examined. Estimated zero leakage factor means no leakage and one means maximum leakage for the wells. The leakage factors not only identified where the leakage was happening, but also determined the amount of leakage by multiplying leakage factor to the net accumulation.\n In reservoirs with complex geology and several faults, commonly encountered in Trinidad, all geological and geophysical complexities might not be accurately known. Using alternative methods such as the CM can complement, validate or better determine fault properties such as leakage and transmissibility for proper application of EOR schemes.","PeriodicalId":415543,"journal":{"name":"Day 2 Tue, June 26, 2018","volume":"46 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-06-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Fault Leakage Assessment Using the Capacitance Model\",\"authors\":\"Muzaffar Mohamdally, M. Soroush, M. Zeidouni, D. Alexander, Donnie Boodlal\",\"doi\":\"10.2118/191250-MS\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Fault transmissibility and leakage have significant implications for field development during both primary and post-primary recovery. Whether the fault is sealing or not can directly determine the sweep efficiency and the fate of injected fluids. In addition, fault transmissivity affect the accuracy of in-place volume calculations from material balance techniques. In this paper dynamic data was used to determine transmissibility and leakage of the faults via Capacitance Model (CM).\\n The CM has been developed from linear productivity model and material balance equation. Its inputs are production/injection rates and bottomhole pressure data (if available). The CM has weight factor for each well pair which determines the degree of connectivity between that pair. These weight factors were used and correlated to the fault transmissibility in this paper. Also, the CM was modified to incorporate the leakage in the system. New term, called leakage factor, was added for each well in the equation.\\n The model was examined through applying to several synthetic field data generated by CMG software. In synthetic fields, different faults with different throw and transmissibility were built and across the fault transmissibility was evaluated by the model. For creating leaking fault, upward leakage and flow along the fault were examined. Estimated zero leakage factor means no leakage and one means maximum leakage for the wells. The leakage factors not only identified where the leakage was happening, but also determined the amount of leakage by multiplying leakage factor to the net accumulation.\\n In reservoirs with complex geology and several faults, commonly encountered in Trinidad, all geological and geophysical complexities might not be accurately known. Using alternative methods such as the CM can complement, validate or better determine fault properties such as leakage and transmissibility for proper application of EOR schemes.\",\"PeriodicalId\":415543,\"journal\":{\"name\":\"Day 2 Tue, June 26, 2018\",\"volume\":\"46 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-06-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 2 Tue, June 26, 2018\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/191250-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 2 Tue, June 26, 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/191250-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fault Leakage Assessment Using the Capacitance Model
Fault transmissibility and leakage have significant implications for field development during both primary and post-primary recovery. Whether the fault is sealing or not can directly determine the sweep efficiency and the fate of injected fluids. In addition, fault transmissivity affect the accuracy of in-place volume calculations from material balance techniques. In this paper dynamic data was used to determine transmissibility and leakage of the faults via Capacitance Model (CM).
The CM has been developed from linear productivity model and material balance equation. Its inputs are production/injection rates and bottomhole pressure data (if available). The CM has weight factor for each well pair which determines the degree of connectivity between that pair. These weight factors were used and correlated to the fault transmissibility in this paper. Also, the CM was modified to incorporate the leakage in the system. New term, called leakage factor, was added for each well in the equation.
The model was examined through applying to several synthetic field data generated by CMG software. In synthetic fields, different faults with different throw and transmissibility were built and across the fault transmissibility was evaluated by the model. For creating leaking fault, upward leakage and flow along the fault were examined. Estimated zero leakage factor means no leakage and one means maximum leakage for the wells. The leakage factors not only identified where the leakage was happening, but also determined the amount of leakage by multiplying leakage factor to the net accumulation.
In reservoirs with complex geology and several faults, commonly encountered in Trinidad, all geological and geophysical complexities might not be accurately known. Using alternative methods such as the CM can complement, validate or better determine fault properties such as leakage and transmissibility for proper application of EOR schemes.