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Synthetic modelling of downhole resistivity data to improve interpretation of basin morphology from magnetotelluric inversion
Earth, Planets and Space ( IF 3.362 ) Pub Date : 2020-05-14 , DOI: 10.1186/s40623-020-01178-2
Janelle M. Simpson , Graham Heinson

Prospective Proterozoic units in the southern Mount Isa Province are concealed by a poorly defined extent of younger basin cover, leading to poor exploration success. Collection of a magnetotelluric (MT) survey in the area containing 809 broadband MT (BBMT) and 855 audiomagnetotelluric (AMT) stations in 2014–2015, offers an opportunity to better model the depth to basement to enable effective exploration. MT inversion models are inherently non-unique, requiring independent geophysical and geological constraint to reduce model uncertainty. Where data are not available to constrain inversion, alternative approaches to dealing in inversion variability are required. This study uses synthetic modelling based on well data combined with two kinds of inversion to generate an interpretation and quantify associated uncertainty. Downhole resistivity logs were obtained from three petroleum wells adjacent to the study area, and 1D resistivity models were generated from the downhole data. A suite of 1D and 2D MT inversion algorithms were tested to determine their ability to resolve basin layering and the basement interface. All inversion algorithms reproduced basin layering, but the basement interface was poorly resolved. A combination of Occam2D and 1D rjMcMC inversions were used to produce interpretation of the base of the Eromanga Basin, an intra-Georgina Basin low-resistivity layer and depth to basement, all of which have associated error estimates. This work highlights the importance of understanding inversion variability during interpretation of geological features, particularly in the absence of constraining information. Distribution of uncertainty between the interpretation features is significantly non-uniform, necessitating careful consideration of inversion results. By quantifying uncertainty rather than ignoring it, we produce an interpretation commensurate with data limitations that still provides valuable new information about the geology of the southern Mount Isa Province.

中文翻译:

井下电阻率数据的综合建模以改进大地电磁反演对盆地形态的解释

伊萨山省南部的潜在元古代单元被范围不明确的年轻盆地覆盖所掩盖,导致勘探成功率较低。2014-2015 年在包含 809 个宽带 MT (BBMT) 和 855 个大地电磁 (AMT) 站的区域收集大地电磁 (MT) 调查,提供了更好地模拟地下室深度以实现有效勘探的机会。MT 反演模型本质上是非唯一的,需要独立的地球物理和地质约束来减少模型的不确定性。在没有数据来限制反演的情况下,需要替代方法来处理反演变异性。本研究使用基于井数据的综合建模结合两种反演来产生解释并量化相关的不确定性。井下电阻率测井取自研究区附近的三口油井,并从井下数据生成一维电阻率模型。测试了一套一维和二维 MT 反演算法,以确定它们解析盆地分层和基底界面的能力。所有反演算法都再现了盆地分层,但基底界面解析不佳。Occam2D 和 1D rjMcMC 反演的组合用于解释 Eromanga 盆地的底部、乔治娜盆地内的低电阻率层和到基底的深度,所有这些都具有相关的误差估计。这项工作强调了在解释地质特征期间了解反演变异性的重要性,特别是在缺乏约束信息的情况下。解释特征之间的不确定性分布明显不均匀,需要仔细考虑反演结果。通过量化而不是忽略不确定性,我们产生了与数据限制相称的解释,这些解释仍然提供了有关伊萨山省南部地质的宝贵新信息。
更新日期:2020-05-14
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