Luciano Garim Garcia , Vinícius Lôndero , Eric Lubín Cayo , Andressa Bressane , Ariane Santos da Silveira , Paulo Roberto Moura de Carvalho
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In order to refine the model generated by the genetic algorithm, we use indicator kriging to adjust the simulation to the available well data. The methodology was applied to data from the Sapinhoa field-Brazil, focusing on three ages, 113 Ma, 114 Ma, and 115 Ma. The results obtained demonstrate that the simulated facies association maps largely respect the geometries observed in the seismic facies, and at the same time, honor the data from wells along the simulated area. The results demonstrate that the simulated facies association maps largely respect the geometries observed in the seismic facies while honoring well data across the simulated area. This approach addresses the inherent uncertainties and biases in traditional facies modeling, providing a more reliable and automated method for calibrating facies intervals.</div></div>","PeriodicalId":54882,"journal":{"name":"Journal of Applied Geophysics","volume":"230 ","pages":"Article 105524"},"PeriodicalIF":2.2000,"publicationDate":"2024-09-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Facies associations dispersion via rule-based simulation with genetic algorithm and kriging: A methodology conditioned by seismic facies\",\"authors\":\"Luciano Garim Garcia , Vinícius Lôndero , Eric Lubín Cayo , Andressa Bressane , Ariane Santos da Silveira , Paulo Roberto Moura de Carvalho\",\"doi\":\"10.1016/j.jappgeo.2024.105524\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Rule-based simulation of facies is a valuable tool in oil and gas field exploration. The manuscript presents a hybrid methodology for simulating facies associations, using paleobathymetry as the main data and seismic facies as the secondary. A dispersion model of facies, which is based on paleobathymetry and wave energy is proposed, and the parameters of this dispersion are optimized via genetic algorithm, using seismic facies. The relationship between seismic facies e facies associations is quantified in order to construct a fitness function used in genetic algorithm to select good parameters for the dispersion model. In order to refine the model generated by the genetic algorithm, we use indicator kriging to adjust the simulation to the available well data. The methodology was applied to data from the Sapinhoa field-Brazil, focusing on three ages, 113 Ma, 114 Ma, and 115 Ma. The results obtained demonstrate that the simulated facies association maps largely respect the geometries observed in the seismic facies, and at the same time, honor the data from wells along the simulated area. The results demonstrate that the simulated facies association maps largely respect the geometries observed in the seismic facies while honoring well data across the simulated area. This approach addresses the inherent uncertainties and biases in traditional facies modeling, providing a more reliable and automated method for calibrating facies intervals.</div></div>\",\"PeriodicalId\":54882,\"journal\":{\"name\":\"Journal of Applied Geophysics\",\"volume\":\"230 \",\"pages\":\"Article 105524\"},\"PeriodicalIF\":2.2000,\"publicationDate\":\"2024-09-28\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Applied Geophysics\",\"FirstCategoryId\":\"89\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0926985124002404\",\"RegionNum\":3,\"RegionCategory\":\"地球科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"GEOSCIENCES, MULTIDISCIPLINARY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Applied Geophysics","FirstCategoryId":"89","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0926985124002404","RegionNum":3,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
摘要
基于规则的岩相模拟是油气田勘探的重要工具。该手稿介绍了一种以古测深为主要数据、以地震剖面为辅助数据的剖面关联混合模拟方法。文中提出了一种基于古测深和波能的岩层面散布模型,并利用地震岩层面通过遗传算法对该散布模型的参数进行了优化。对地震剖面与剖面关联之间的关系进行量化,以构建遗传算法中使用的拟合函数,为分散模型选择良好的参数。为了完善遗传算法生成的模型,我们使用指标克里金法根据现有油井数据调整模拟。该方法适用于巴西萨宾霍亚油田的数据,重点关注三个年龄段,即 113 Ma、114 Ma 和 115 Ma。结果表明,模拟的岩相关联图在很大程度上尊重了地震岩相中观察到的几何形状,同时也尊重了模拟区域沿线的油井数据。结果表明,模拟面关联图在很大程度上尊重了地震面中观察到的几何特征,同时也尊重了模拟区域内的油井数据。这种方法解决了传统岩相建模中固有的不确定性和偏差,为岩相区间校准提供了更可靠的自动化方法。
Facies associations dispersion via rule-based simulation with genetic algorithm and kriging: A methodology conditioned by seismic facies
Rule-based simulation of facies is a valuable tool in oil and gas field exploration. The manuscript presents a hybrid methodology for simulating facies associations, using paleobathymetry as the main data and seismic facies as the secondary. A dispersion model of facies, which is based on paleobathymetry and wave energy is proposed, and the parameters of this dispersion are optimized via genetic algorithm, using seismic facies. The relationship between seismic facies e facies associations is quantified in order to construct a fitness function used in genetic algorithm to select good parameters for the dispersion model. In order to refine the model generated by the genetic algorithm, we use indicator kriging to adjust the simulation to the available well data. The methodology was applied to data from the Sapinhoa field-Brazil, focusing on three ages, 113 Ma, 114 Ma, and 115 Ma. The results obtained demonstrate that the simulated facies association maps largely respect the geometries observed in the seismic facies, and at the same time, honor the data from wells along the simulated area. The results demonstrate that the simulated facies association maps largely respect the geometries observed in the seismic facies while honoring well data across the simulated area. This approach addresses the inherent uncertainties and biases in traditional facies modeling, providing a more reliable and automated method for calibrating facies intervals.
期刊介绍:
The Journal of Applied Geophysics with its key objective of responding to pertinent and timely needs, places particular emphasis on methodological developments and innovative applications of geophysical techniques for addressing environmental, engineering, and hydrological problems. Related topical research in exploration geophysics and in soil and rock physics is also covered by the Journal of Applied Geophysics.