{"title":"南非Karoo盆地Tanqua沉积中心Skoosteenberg FM深水矿床的虚拟露头、相结构和储层建模","authors":"G. Dolores-Reyes","doi":"10.3997/2214-4609.201900345","DOIUrl":null,"url":null,"abstract":"Summary The fine-grained deep-water deposits of the Skoorsteenberg Formation in the Tanqua depocenter include four fan sand rich units namely 1 to 4. This study characterized the deposits of Fan 3 and 4 to understand the facies architecture of one of the less understood depositional environments: the deep-water deposits. Hammerkranz 1 to 3, Ongeluks River and Klip Fontein Farm outcrops, distributed across the Tanqua depocenter, were studied to gather geometric data, such as thicknesses, NGR, and facies proportions. These data will help to predict the architecture and position of each lobe within a lobe structure. Seven facies models were built to represent the geology and main heterogeneities into a reservoir perspective. A surface-based modelling, and a Sequential Indicator Simulator (SIS) method were adopted in the case of lobe architecture. In the case of channel architecture, object-based modelling and SIS method were applied. The purpose of having different modelling methods is to see which of them best honour the geology. Results showed a better representation applying surface based and object-based modelling in lobe and channel architecture, respectively. However, SIS method displayed a better distribution of small heterogeneities in both cases. A hybrid modelling approach for channel architecture is documented in this study","PeriodicalId":335882,"journal":{"name":"Second EAGE Workshop on Deepwater Exploration in Mexico: Knowledge transfer and collaboration from shelf to deepwater","volume":"210 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-04-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Virtual Outcrops, facies Architecture and Reservoir Modelling of Deep-Water Deposits from the Skoosteenberg FM, Tanqua Depocenter, Karoo Basin, South Africa\",\"authors\":\"G. Dolores-Reyes\",\"doi\":\"10.3997/2214-4609.201900345\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Summary The fine-grained deep-water deposits of the Skoorsteenberg Formation in the Tanqua depocenter include four fan sand rich units namely 1 to 4. This study characterized the deposits of Fan 3 and 4 to understand the facies architecture of one of the less understood depositional environments: the deep-water deposits. Hammerkranz 1 to 3, Ongeluks River and Klip Fontein Farm outcrops, distributed across the Tanqua depocenter, were studied to gather geometric data, such as thicknesses, NGR, and facies proportions. These data will help to predict the architecture and position of each lobe within a lobe structure. Seven facies models were built to represent the geology and main heterogeneities into a reservoir perspective. A surface-based modelling, and a Sequential Indicator Simulator (SIS) method were adopted in the case of lobe architecture. In the case of channel architecture, object-based modelling and SIS method were applied. The purpose of having different modelling methods is to see which of them best honour the geology. Results showed a better representation applying surface based and object-based modelling in lobe and channel architecture, respectively. However, SIS method displayed a better distribution of small heterogeneities in both cases. A hybrid modelling approach for channel architecture is documented in this study\",\"PeriodicalId\":335882,\"journal\":{\"name\":\"Second EAGE Workshop on Deepwater Exploration in Mexico: Knowledge transfer and collaboration from shelf to deepwater\",\"volume\":\"210 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-04-24\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Second EAGE Workshop on Deepwater Exploration in Mexico: Knowledge transfer and collaboration from shelf to deepwater\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.3997/2214-4609.201900345\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Second EAGE Workshop on Deepwater Exploration in Mexico: Knowledge transfer and collaboration from shelf to deepwater","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201900345","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Virtual Outcrops, facies Architecture and Reservoir Modelling of Deep-Water Deposits from the Skoosteenberg FM, Tanqua Depocenter, Karoo Basin, South Africa
Summary The fine-grained deep-water deposits of the Skoorsteenberg Formation in the Tanqua depocenter include four fan sand rich units namely 1 to 4. This study characterized the deposits of Fan 3 and 4 to understand the facies architecture of one of the less understood depositional environments: the deep-water deposits. Hammerkranz 1 to 3, Ongeluks River and Klip Fontein Farm outcrops, distributed across the Tanqua depocenter, were studied to gather geometric data, such as thicknesses, NGR, and facies proportions. These data will help to predict the architecture and position of each lobe within a lobe structure. Seven facies models were built to represent the geology and main heterogeneities into a reservoir perspective. A surface-based modelling, and a Sequential Indicator Simulator (SIS) method were adopted in the case of lobe architecture. In the case of channel architecture, object-based modelling and SIS method were applied. The purpose of having different modelling methods is to see which of them best honour the geology. Results showed a better representation applying surface based and object-based modelling in lobe and channel architecture, respectively. However, SIS method displayed a better distribution of small heterogeneities in both cases. A hybrid modelling approach for channel architecture is documented in this study