{"title":"裂缝高度增长研究:库柏盆地概率分析","authors":"J. Griffiths","doi":"10.2118/192060-MS","DOIUrl":null,"url":null,"abstract":"\n A probability graph was developed to describe height growth potential when performing hydraulic fracture stimulation operations in the Cooper Basin, Central Australia. This graph has led to improvements in setting completion strategies.\n Multiple data sources were used to define the probability graph, including proppant tracers, microseismic, downhole tiltmeter data as well as pressure interference and production data. Each dataset has known uncertainties, so the empirically derived probability graph has an intrinsic range of uncertainty.\n The observed data shows instances of fracture propagation across changes in lithology which were previously thought to be highly confining. In other instances, field data closely matched model predictions. Likewise, the observed data indicates that typical levers used to induce or reduce height growth (such as fluid viscosity, pump rate and job size) may have limited influence. These insights led decision makers to question the validity of deterministic fracture models.\n This study highlights that fracture height growth predictions should carry a range of uncertainty. An appreciation of this range has proven beneficial by fostering ‘what-if’ discussions during the project planning phase. The derived probability graph can be used to run sensitivity analyses to determine the optimal path when several completion methods are available.\n This graph has proven to be an informative and practical tool for use in the Cooper Basin by promoting deeper thought and collaboration amongst stakeholders. Similar tools could be developed to characterise fracture height growth within other petroleum basins.","PeriodicalId":11182,"journal":{"name":"Day 3 Thu, October 25, 2018","volume":"17 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2018-10-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Fracture Height Growth Study: Cooper Basin Probability Analysis\",\"authors\":\"J. Griffiths\",\"doi\":\"10.2118/192060-MS\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n A probability graph was developed to describe height growth potential when performing hydraulic fracture stimulation operations in the Cooper Basin, Central Australia. This graph has led to improvements in setting completion strategies.\\n Multiple data sources were used to define the probability graph, including proppant tracers, microseismic, downhole tiltmeter data as well as pressure interference and production data. Each dataset has known uncertainties, so the empirically derived probability graph has an intrinsic range of uncertainty.\\n The observed data shows instances of fracture propagation across changes in lithology which were previously thought to be highly confining. In other instances, field data closely matched model predictions. Likewise, the observed data indicates that typical levers used to induce or reduce height growth (such as fluid viscosity, pump rate and job size) may have limited influence. These insights led decision makers to question the validity of deterministic fracture models.\\n This study highlights that fracture height growth predictions should carry a range of uncertainty. An appreciation of this range has proven beneficial by fostering ‘what-if’ discussions during the project planning phase. The derived probability graph can be used to run sensitivity analyses to determine the optimal path when several completion methods are available.\\n This graph has proven to be an informative and practical tool for use in the Cooper Basin by promoting deeper thought and collaboration amongst stakeholders. Similar tools could be developed to characterise fracture height growth within other petroleum basins.\",\"PeriodicalId\":11182,\"journal\":{\"name\":\"Day 3 Thu, October 25, 2018\",\"volume\":\"17 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-10-19\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Day 3 Thu, October 25, 2018\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2118/192060-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 3 Thu, October 25, 2018","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/192060-MS","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Fracture Height Growth Study: Cooper Basin Probability Analysis
A probability graph was developed to describe height growth potential when performing hydraulic fracture stimulation operations in the Cooper Basin, Central Australia. This graph has led to improvements in setting completion strategies.
Multiple data sources were used to define the probability graph, including proppant tracers, microseismic, downhole tiltmeter data as well as pressure interference and production data. Each dataset has known uncertainties, so the empirically derived probability graph has an intrinsic range of uncertainty.
The observed data shows instances of fracture propagation across changes in lithology which were previously thought to be highly confining. In other instances, field data closely matched model predictions. Likewise, the observed data indicates that typical levers used to induce or reduce height growth (such as fluid viscosity, pump rate and job size) may have limited influence. These insights led decision makers to question the validity of deterministic fracture models.
This study highlights that fracture height growth predictions should carry a range of uncertainty. An appreciation of this range has proven beneficial by fostering ‘what-if’ discussions during the project planning phase. The derived probability graph can be used to run sensitivity analyses to determine the optimal path when several completion methods are available.
This graph has proven to be an informative and practical tool for use in the Cooper Basin by promoting deeper thought and collaboration amongst stakeholders. Similar tools could be developed to characterise fracture height growth within other petroleum basins.