Qualitative and quantitative reservoir characterisation using seismic inversion based on global optimization: A comparative case study

IF 1.3 4区 地球科学 Q3 GEOSCIENCES, MULTIDISCIPLINARY
Brijesh Kumar, Ravi Kant, S P Maurya
{"title":"Qualitative and quantitative reservoir characterisation using seismic inversion based on global optimization: A comparative case study","authors":"Brijesh Kumar, Ravi Kant, S P Maurya","doi":"10.1007/s12040-024-02301-7","DOIUrl":null,"url":null,"abstract":"<p>In this study, the focus is on predicting the properties of rocks beneath the Earth’s surface using global optimisation techniques such as genetic algorithms (GA), simulated annealing (SA) and particle swarm optimisation (PSO). The goal is to minimise the difference (error) between actual seismic data and synthetic (computed) seismic traces. Global optimisation is an approach that is independent of the initial model and aims to identify the global minimum of an objective function. In contrast, local optimisation relies on the accuracy of the initial model, and if an accurate initial model is not provided, it may become trapped in a local minimum, leading to an inaccurate representation of the subsurface model. What makes global optimisation powerful is that it does not get stuck in local minima (suboptimal solutions), but seeks the absolute best solution in the entire search space. This property is crucial in seismic inversion, where finding the most accurate representation of subsurface properties is of utmost importance for geophysical applications. The study includes one synthetic example and one real dataset, with a specific emphasis on evaluating acoustic impedance rock properties. While acoustic impedance is characteristic of rock layers, seismic data represents properties at the interfaces between these layers. Consequently, seismic data is highly valuable for gaining detailed insights into the subsurface. The results of the optimisation process provide exceptionally detailed views of the subsurface, aiding in the interpretation of seismic data. GA, SA and PSO algorithms perform well, both with synthetic data and real data. The inversion process identifies a zone with low acoustic impedance, corresponding to a prominent seismic anomaly. The evaluation of the inverted outcomes reveals that the impedance within the area ranges from 4300 to 4700 m/s*g/cc, situated within a specific time range of 900–950 ms in the seismic data of F3-block, Netherland.</p>","PeriodicalId":15609,"journal":{"name":"Journal of Earth System Science","volume":null,"pages":null},"PeriodicalIF":1.3000,"publicationDate":"2024-05-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Earth System Science","FirstCategoryId":"89","ListUrlMain":"https://doi.org/10.1007/s12040-024-02301-7","RegionNum":4,"RegionCategory":"地球科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"GEOSCIENCES, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0

Abstract

In this study, the focus is on predicting the properties of rocks beneath the Earth’s surface using global optimisation techniques such as genetic algorithms (GA), simulated annealing (SA) and particle swarm optimisation (PSO). The goal is to minimise the difference (error) between actual seismic data and synthetic (computed) seismic traces. Global optimisation is an approach that is independent of the initial model and aims to identify the global minimum of an objective function. In contrast, local optimisation relies on the accuracy of the initial model, and if an accurate initial model is not provided, it may become trapped in a local minimum, leading to an inaccurate representation of the subsurface model. What makes global optimisation powerful is that it does not get stuck in local minima (suboptimal solutions), but seeks the absolute best solution in the entire search space. This property is crucial in seismic inversion, where finding the most accurate representation of subsurface properties is of utmost importance for geophysical applications. The study includes one synthetic example and one real dataset, with a specific emphasis on evaluating acoustic impedance rock properties. While acoustic impedance is characteristic of rock layers, seismic data represents properties at the interfaces between these layers. Consequently, seismic data is highly valuable for gaining detailed insights into the subsurface. The results of the optimisation process provide exceptionally detailed views of the subsurface, aiding in the interpretation of seismic data. GA, SA and PSO algorithms perform well, both with synthetic data and real data. The inversion process identifies a zone with low acoustic impedance, corresponding to a prominent seismic anomaly. The evaluation of the inverted outcomes reveals that the impedance within the area ranges from 4300 to 4700 m/s*g/cc, situated within a specific time range of 900–950 ms in the seismic data of F3-block, Netherland.

Abstract Image

利用基于全局优化的地震反演进行定性和定量储层特征描述:案例对比研究
本研究的重点是利用遗传算法(GA)、模拟退火(SA)和粒子群优化(PSO)等全局优化技术预测地表下岩石的属性。其目标是最大限度地减少实际地震数据与合成(计算)地震道之间的差异(误差)。全局优化是一种独立于初始模型的方法,旨在确定目标函数的全局最小值。相比之下,局部优化依赖于初始模型的准确性,如果没有提供准确的初始模型,就可能陷入局部最小值的困境,导致对地下模型的表述不准确。全局优化的强大之处在于它不会陷入局部最小值(次优解),而是在整个搜索空间中寻找绝对最佳的解。这一特性在地震反演中至关重要,因为在地震反演中,找到最准确的地下属性表示对于地球物理应用至关重要。研究包括一个合成示例和一个真实数据集,重点是评估声阻抗岩石特性。声阻抗是岩层的特征,而地震数据则代表这些岩层之间界面的属性。因此,地震数据对于深入了解地下情况非常有价值。优化过程的结果提供了非常详细的地下视图,有助于解释地震数据。GA、SA 和 PSO 算法在使用合成数据和真实数据时均表现出色。反演过程确定了一个低声阻抗区域,该区域与一个突出的地震异常点相对应。对反演结果的评估显示,在荷兰 F3 区块的地震数据中,该区域内的阻抗介于 4300 至 4700 m/s*g/cc 之间,位于 900 至 950 ms 的特定时间范围内。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
Journal of Earth System Science
Journal of Earth System Science Earth and Planetary Sciences-General Earth and Planetary Sciences
CiteScore
3.20
自引率
5.30%
发文量
226
期刊介绍: The Journal of Earth System Science, an International Journal, was earlier a part of the Proceedings of the Indian Academy of Sciences – Section A begun in 1934, and later split in 1978 into theme journals. This journal was published as Proceedings – Earth and Planetary Sciences since 1978, and in 2005 was renamed ‘Journal of Earth System Science’. The journal is highly inter-disciplinary and publishes scholarly research – new data, ideas, and conceptual advances – in Earth System Science. The focus is on the evolution of the Earth as a system: manuscripts describing changes of anthropogenic origin in a limited region are not considered unless they go beyond describing the changes to include an analysis of earth-system processes. The journal''s scope includes the solid earth (geosphere), the atmosphere, the hydrosphere (including cryosphere), and the biosphere; it also addresses related aspects of planetary and space sciences. Contributions pertaining to the Indian sub- continent and the surrounding Indian-Ocean region are particularly welcome. Given that a large number of manuscripts report either observations or model results for a limited domain, manuscripts intended for publication in JESS are expected to fulfill at least one of the following three criteria. The data should be of relevance and should be of statistically significant size and from a region from where such data are sparse. If the data are from a well-sampled region, the data size should be considerable and advance our knowledge of the region. A model study is carried out to explain observations reported either in the same manuscript or in the literature. The analysis, whether of data or with models, is novel and the inferences advance the current knowledge.
文献相关原料
公司名称 产品信息 采购帮参考价格
×
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