Developing a probabilistic compaction model for the Northern Carnarvon Basin using Bayesian inference

IF 2.8 2区 地球科学 Q2 GEOSCIENCES, MULTIDISCIPLINARY Basin Research Pub Date : 2024-11-12 DOI:10.1111/bre.70005
Patrick Makuluni, Juerg Hauser, Stuart Clark
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Abstract

Exhumation affects sedimentary basin evolution by influencing structural, pressure and temperature dynamics, thereby impacting energy resource formation. Compaction‐based methods are widely used to quantify exhumation, utilising sonic and porosity data to track sediment uplift from its maximum burial depths. However, uncertainties arise from applying empirical compaction models developed for specific geological regions, highlighting the need for region‐specific models. Even such region‐specific models contain uncertainties, which can compromise exhumation estimates. We, therefore, develop a probabilistic compaction model for the Northwest Shelf Basins using sonic data from normally compacted and unexhumed shales from the Northern Carnarvon Basin (NCB). The model's robustness is estimated using MCMC, and uncertainty propagation analysis is employed to assess the impact of model uncertainty on the model's predictive applications. The model shows exponential porosity reduction with depth, demonstrating rapid compaction from the surface to ca. 2 km and slower compaction thereafter. The model is then applied to interpret new datasets from the Canning, Gippsland and NCB regions. The results reveal that while some parts of the NCB exhibit normal compaction without exhumation, others were significantly exhumed. Conversely, Canning and Gippsland Basin data indicate signs of significant exhumation, as suggested by previous studies, thereby confirming the model's effectiveness outside the Northwest Shelf. Since the model could not explain data from exhumed regions, we inferred new models incorporating “exhumation” parameters to interpret the complex compaction histories of these areas, and the best‐fitting models were selected using the Bayes Factor method. Uncertainty analysis revealed that the impacts of model uncertainty on exhumation estimates are consistent across wide depth ranges. Our findings highlight the need to refine compaction models for better predictive reliability and informed resource exploration in sedimentary basins.
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利用贝叶斯推断法建立北卡纳冯盆地概率压实模型
吐露作用通过影响结构、压力和温度动态来影响沉积盆地的演化,从而影响能源资源的形成。基于压实的方法被广泛用于量化挤出,利用声波和孔隙度数据来跟踪沉积物从最大埋藏深度的抬升情况。然而,应用为特定地质区域开发的经验压实模型会产生不确定性,因此需要针对特定区域的模型。即使是这种针对特定区域的模型也存在不确定性,可能会影响隆升估算。因此,我们利用北卡纳冯盆地(NCB)正常压实和未脱壳页岩的声波数据,为西北大陆架盆地建立了一个概率压实模型。利用 MCMC 对模型的稳健性进行了估计,并采用不确定性传播分析来评估模型的不确定性对模型预测应用的影响。该模型显示孔隙度随深度呈指数减少,表明从地表到约 2 千米处的压实速度很快,此后压实速度减慢。该模型随后被用于解释来自坎宁、吉普斯兰和 NCB 地区的新数据集。结果表明,虽然北加州盆地的某些部分显示出正常的压实而没有掘起,但其他部分却有明显的掘起。与此相反,坎宁和吉普斯兰盆地的数据则显示出明显的隆起迹象,这与之前的研究结果一致,从而证实了该模型在西北大陆架以外地区的有效性。由于该模型无法解释被 "掘起 "地区的数据,我们推断了包含 "掘起 "参数的新模型,以解释这些地区复杂的压实历史,并利用贝叶斯因子法选出了最佳拟合模型。不确定性分析表明,模型的不确定性对不同深度范围内揭露的影响是一致的。我们的研究结果突出表明,有必要完善压实模型,以提高沉积盆地的预测可靠性和资源勘探的知情度。
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来源期刊
Basin Research
Basin Research 地学-地球科学综合
CiteScore
7.00
自引率
9.40%
发文量
88
审稿时长
>12 weeks
期刊介绍: Basin Research is an international journal which aims to publish original, high impact research papers on sedimentary basin systems. We view integrated, interdisciplinary research as being essential for the advancement of the subject area; therefore, we do not seek manuscripts focused purely on sedimentology, structural geology, or geophysics that have a natural home in specialist journals. Rather, we seek manuscripts that treat sedimentary basins as multi-component systems that require a multi-faceted approach to advance our understanding of their development. During deposition and subsidence we are concerned with large-scale geodynamic processes, heat flow, fluid flow, strain distribution, seismic and sequence stratigraphy, modelling, burial and inversion histories. In addition, we view the development of the source area, in terms of drainage networks, climate, erosion, denudation and sediment routing systems as vital to sedimentary basin systems. The underpinning requirement is that a contribution should be of interest to earth scientists of more than one discipline.
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