利用最小可用数据集地质统计方法和地震属性进行储层逻辑深度建模

Mehdi Rezvandehy
{"title":"利用最小可用数据集地质统计方法和地震属性进行储层逻辑深度建模","authors":"Mehdi Rezvandehy","doi":"10.1016/j.juogr.2014.03.003","DOIUrl":null,"url":null,"abstract":"<div><p>For rational depth modeling of a prominent reservoir layer in north of Iran (Gorgan plain, Chelekan top), geostatistical methods were proposed to use with the minimum available data. This data consisted of ten wells, five 2D seismic lines (three vertical lines perpendicular to two horizontal ones) which covers the area, and one small 3D seismic area, which was applied solely for evaluation of findings and optimizing our choices. Because the expansion of this area was limited as opposed to region aimed for modeling. Hence, for a reasonable geostatistical modeling, an appropriate secondary variable (soft data) was crucial. Initially, the reservoir layer should be pursued in five seismic lines with a suitable seismic attribute and achieved its time model (TWT) all over the Gorgan plain due to existing a few number of lines, linear form of data set (located on the seismic lines) and the smoothing effect of kriging, the estimate and average simulated realizations (E-type) could not give acceptable results in time modeling of the layer based on merely five seismic lines. Therefore, one of 100 realizations related to sequential quassian simulation (SGS) selected as the best secondary data after probing their correlation and similarity with the real 3D seismic data and obtaining a proper correlation coefficient. Moreover, this realization revealed the best correlation with the depth amounts of 10 wells, reproducing geostatistical and statistical parameters of input data. For this reason, it was utilized as secondary data in kriging with an external drift method (KED). Having been applied it, the smoothing effect was diminished dramatically in comparison with one variable model and consequences of final modeling, investigation of uncertainty and estimate error prior to using secondary data and after that, all of them signified the final model was much more reasonable than initial one (without secondary data).</p></div>","PeriodicalId":100850,"journal":{"name":"Journal of Unconventional Oil and Gas Resources","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1016/j.juogr.2014.03.003","citationCount":"2","resultStr":"{\"title\":\"Logical depth modeling of a reservoir layer with the minimum available data-integration geostatistical methods and seismic attributes\",\"authors\":\"Mehdi Rezvandehy\",\"doi\":\"10.1016/j.juogr.2014.03.003\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>For rational depth modeling of a prominent reservoir layer in north of Iran (Gorgan plain, Chelekan top), geostatistical methods were proposed to use with the minimum available data. This data consisted of ten wells, five 2D seismic lines (three vertical lines perpendicular to two horizontal ones) which covers the area, and one small 3D seismic area, which was applied solely for evaluation of findings and optimizing our choices. Because the expansion of this area was limited as opposed to region aimed for modeling. Hence, for a reasonable geostatistical modeling, an appropriate secondary variable (soft data) was crucial. Initially, the reservoir layer should be pursued in five seismic lines with a suitable seismic attribute and achieved its time model (TWT) all over the Gorgan plain due to existing a few number of lines, linear form of data set (located on the seismic lines) and the smoothing effect of kriging, the estimate and average simulated realizations (E-type) could not give acceptable results in time modeling of the layer based on merely five seismic lines. Therefore, one of 100 realizations related to sequential quassian simulation (SGS) selected as the best secondary data after probing their correlation and similarity with the real 3D seismic data and obtaining a proper correlation coefficient. Moreover, this realization revealed the best correlation with the depth amounts of 10 wells, reproducing geostatistical and statistical parameters of input data. For this reason, it was utilized as secondary data in kriging with an external drift method (KED). Having been applied it, the smoothing effect was diminished dramatically in comparison with one variable model and consequences of final modeling, investigation of uncertainty and estimate error prior to using secondary data and after that, all of them signified the final model was much more reasonable than initial one (without secondary data).</p></div>\",\"PeriodicalId\":100850,\"journal\":{\"name\":\"Journal of Unconventional Oil and Gas Resources\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1016/j.juogr.2014.03.003\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Unconventional Oil and Gas Resources\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S2213397614000238\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Unconventional Oil and Gas Resources","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2213397614000238","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2

摘要

为了对伊朗北部(Gorgan平原,Chelekan顶部)某突出储层进行合理的深度建模,提出了利用最小可用数据的地质统计学方法。这些数据包括10口井、覆盖该地区的5条2D地震线(3条垂直于2条水平线)和一个小的3D地震区,该数据仅用于评估发现和优化选择。因为这个区域的扩展是有限的,而不是针对建模的区域。因此,对于合理的地质统计建模,适当的次要变量(软数据)是至关重要的。由于现有的地震线数量少,数据集呈线性形式(位于地震线上),再加上克里格的平滑效应,使得仅基于5条地震线的估计和平均模拟实现(e型)对储层进行时间建模的结果不能令人满意。因此,从100种序列拟模拟(SGS)相关实现中选择一种作为最佳二次数据,对其与实际三维地震数据的相关性和相似性进行探讨,并获得适当的相关系数。此外,这种实现显示了与10口井的深度量的最佳相关性,再现了输入数据的地质统计和统计参数。因此,它被用作克里格外漂移法(KED)的辅助数据。应用后,与单变量模型相比,平滑效果明显减弱,最终建模的结果,不确定性调查和估计误差在使用辅助数据之前和之后,都表明最终模型比初始模型(没有辅助数据)更合理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Logical depth modeling of a reservoir layer with the minimum available data-integration geostatistical methods and seismic attributes

For rational depth modeling of a prominent reservoir layer in north of Iran (Gorgan plain, Chelekan top), geostatistical methods were proposed to use with the minimum available data. This data consisted of ten wells, five 2D seismic lines (three vertical lines perpendicular to two horizontal ones) which covers the area, and one small 3D seismic area, which was applied solely for evaluation of findings and optimizing our choices. Because the expansion of this area was limited as opposed to region aimed for modeling. Hence, for a reasonable geostatistical modeling, an appropriate secondary variable (soft data) was crucial. Initially, the reservoir layer should be pursued in five seismic lines with a suitable seismic attribute and achieved its time model (TWT) all over the Gorgan plain due to existing a few number of lines, linear form of data set (located on the seismic lines) and the smoothing effect of kriging, the estimate and average simulated realizations (E-type) could not give acceptable results in time modeling of the layer based on merely five seismic lines. Therefore, one of 100 realizations related to sequential quassian simulation (SGS) selected as the best secondary data after probing their correlation and similarity with the real 3D seismic data and obtaining a proper correlation coefficient. Moreover, this realization revealed the best correlation with the depth amounts of 10 wells, reproducing geostatistical and statistical parameters of input data. For this reason, it was utilized as secondary data in kriging with an external drift method (KED). Having been applied it, the smoothing effect was diminished dramatically in comparison with one variable model and consequences of final modeling, investigation of uncertainty and estimate error prior to using secondary data and after that, all of them signified the final model was much more reasonable than initial one (without secondary data).

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信