{"title":"基于渗流网络的页岩储层导电机理模拟","authors":"Zhao Jun, Dai Xinyun, Lu Yi-fan, Tang Shen-Hua","doi":"10.1002/CJG2.30045","DOIUrl":null,"url":null,"abstract":"The shale gas reservoir storage space mainly includes micro pores and cracks of micron and nano scale. Owing to the complex pore network, as well as high content of kerogen and clay minerals in shale matrix and existence of conductive minerals, especially pyrite, the shale reservoir conductive mechanism is quite different from that of conventional reservoir, and the I-Sw curve obtained by core electricity experiment is non-linear which makes traditional evaluation models such as Archie's law not suitable. Aiming at these issues, according to actual core experiment and CT scan data, a three dimensional percolation network is established with randomized algorithm and the node voltage and current are calculated through over-relaxation iteration algorithm. With this network, the reasons for non-Archie property and the influence factors of shale reservoir are analyzed. Simulation results show that pore structure, shape and size, mineral composition and formation water resistivity have different effects on the reservoir resistivity. By changing the setting value, single-correlation between the reservoir resistivity and these factors can be built, and percolation correction model is also developed to calculate shale reservoir water saturation. The method has achieved a good effect in a certain shale gas field in Sichuan, China, which presents a good application prospect and provides a new thought on solving complex problems in shale gas field exploration and development with network simulation methods.","PeriodicalId":55257,"journal":{"name":"地球物理学报","volume":"60 1","pages":"275-285"},"PeriodicalIF":1.6000,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1002/CJG2.30045","citationCount":"3","resultStr":"{\"title\":\"SHALE RESERVOIR CONDUCTIVE MECHANISM SIMULATION BASED ON PERCOLATION NETWORK\",\"authors\":\"Zhao Jun, Dai Xinyun, Lu Yi-fan, Tang Shen-Hua\",\"doi\":\"10.1002/CJG2.30045\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The shale gas reservoir storage space mainly includes micro pores and cracks of micron and nano scale. Owing to the complex pore network, as well as high content of kerogen and clay minerals in shale matrix and existence of conductive minerals, especially pyrite, the shale reservoir conductive mechanism is quite different from that of conventional reservoir, and the I-Sw curve obtained by core electricity experiment is non-linear which makes traditional evaluation models such as Archie's law not suitable. Aiming at these issues, according to actual core experiment and CT scan data, a three dimensional percolation network is established with randomized algorithm and the node voltage and current are calculated through over-relaxation iteration algorithm. With this network, the reasons for non-Archie property and the influence factors of shale reservoir are analyzed. Simulation results show that pore structure, shape and size, mineral composition and formation water resistivity have different effects on the reservoir resistivity. By changing the setting value, single-correlation between the reservoir resistivity and these factors can be built, and percolation correction model is also developed to calculate shale reservoir water saturation. The method has achieved a good effect in a certain shale gas field in Sichuan, China, which presents a good application prospect and provides a new thought on solving complex problems in shale gas field exploration and development with network simulation methods.\",\"PeriodicalId\":55257,\"journal\":{\"name\":\"地球物理学报\",\"volume\":\"60 1\",\"pages\":\"275-285\"},\"PeriodicalIF\":1.6000,\"publicationDate\":\"2017-05-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1002/CJG2.30045\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"地球物理学报\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://doi.org/10.1002/CJG2.30045\",\"RegionNum\":4,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"GEOCHEMISTRY & GEOPHYSICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"地球物理学报","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1002/CJG2.30045","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOCHEMISTRY & GEOPHYSICS","Score":null,"Total":0}
SHALE RESERVOIR CONDUCTIVE MECHANISM SIMULATION BASED ON PERCOLATION NETWORK
The shale gas reservoir storage space mainly includes micro pores and cracks of micron and nano scale. Owing to the complex pore network, as well as high content of kerogen and clay minerals in shale matrix and existence of conductive minerals, especially pyrite, the shale reservoir conductive mechanism is quite different from that of conventional reservoir, and the I-Sw curve obtained by core electricity experiment is non-linear which makes traditional evaluation models such as Archie's law not suitable. Aiming at these issues, according to actual core experiment and CT scan data, a three dimensional percolation network is established with randomized algorithm and the node voltage and current are calculated through over-relaxation iteration algorithm. With this network, the reasons for non-Archie property and the influence factors of shale reservoir are analyzed. Simulation results show that pore structure, shape and size, mineral composition and formation water resistivity have different effects on the reservoir resistivity. By changing the setting value, single-correlation between the reservoir resistivity and these factors can be built, and percolation correction model is also developed to calculate shale reservoir water saturation. The method has achieved a good effect in a certain shale gas field in Sichuan, China, which presents a good application prospect and provides a new thought on solving complex problems in shale gas field exploration and development with network simulation methods.