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Quantitative basin modeling: present state and future developments towards predictability

机译:盆地定量建模:可预测性的现状和未来发展

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A critique review of the state of quantitative basin modeling is presented. Over the last 15 years, a number of models are proposed to advance our understanding of basin evolution. However, as of present, most basin models are two dimensional (2-D) and subject to significant simplifications such as depth- or effective stress-dependent porosity, no stress calculations, isotropic fracture permeability, etc. In this paper, promising areas for future development are identified. The use of extensive data sets to calibrate basin models requires a comprehensive reaction, transport, mechanical (RTM) model in order to generate the synthetic response. An automated approach to integrate comprehensive basin modeling and seismic, well-log and other type of data is suggested. The approach takes advantage of comprehensive RTM basin modeling to complete an algorithm based on information theory that places basin modeling on a rigorous foundation. Incompleteness in a model can self-consistently be compensated for by an increase in the amount of observed data used. The method can be used to calibrate the transport, mechanical, or other laws underlying the model. As the procedure is fully automated, the predictions can be continuously updated as new observed data become available. Finally, the procedure makes it possible to augment the model itself as new processes are added in a way that is dictated by the available data. In summary, the automated data/model integration places basin simulation in a novel context of informatics that allows for data to be used to minimize and assess risk in the prediction of reservoir location and characteristics.
机译:提出了对定量盆地建模状态的评论。在过去的15年中,提出了许多模型来加深我们对盆地演化的理解。但是,到目前为止,大多数盆地模型都是二维的(2-D)模型,并且受深度或有效应力相关的孔隙率,没有应力计算,各向同性裂缝渗透率等的重大简化。确定未来的发展。要使用广泛的数据集来校准流域模型,就需要一个综合的反应,运输,机械(RTM)模型,以便生成综合响应。建议使用一种自动方法来综合全面的盆地建模以及地震,测井和其他类型的数据。该方法利用全面的RTM盆地建模来完成基于信息论的算法,该算法将盆地建模置于严格的基础上。模型中的不完整性可以通过增加所使用的观察数据量来自洽地予以补偿。该方法可用于校准模型基础的运输,机械或其他定律。由于该过程是完全自动化的,因此随着新的观测数据可用,可以连续更新预测。最终,该过程使得可以通过可用数据指示的方式添加新流程来扩充模型本身。总而言之,自动数据/模型集成将盆地模拟置于新的信息学背景下,从而可以使用数据来最小化和评估储层位置和特征预测中的风险。

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