SEG Technical Program Expanded Abstracts 2006 2006
DOI: 10.1190/1.2369932
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Seismostratigraphic Inversion: Appraisal, ambiguity, and uncertainty

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Cited by 2 publications
(3 citation statements)
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“…There are many choices that govern inversion behaviour, including the choice of the algorithm itself. Our chosen approach is purposefully similar to genetic algorithm methods used in prior efforts to infer parameters of SFMs (e.g., Bornholdt et al, 1999; Bornholdt & Westphal, 1998; Cross & Lessenger, 1999; Falivene et al, 2014; Imhof & Sharma, 2006, 2007; Lessenger & Cross, 1996; Yuan et al, 2019), but differs in the details of how successful parameterizations are selected from each generation and perturbed to produce the next. Exploratory testing of different parameter inference algorithm choices did not lead to meaningfully different results.…”
Section: Methods For Inversion Of Passive Margin Stratigraphymentioning
confidence: 99%
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“…There are many choices that govern inversion behaviour, including the choice of the algorithm itself. Our chosen approach is purposefully similar to genetic algorithm methods used in prior efforts to infer parameters of SFMs (e.g., Bornholdt et al, 1999; Bornholdt & Westphal, 1998; Cross & Lessenger, 1999; Falivene et al, 2014; Imhof & Sharma, 2006, 2007; Lessenger & Cross, 1996; Yuan et al, 2019), but differs in the details of how successful parameterizations are selected from each generation and perturbed to produce the next. Exploratory testing of different parameter inference algorithm choices did not lead to meaningfully different results.…”
Section: Methods For Inversion Of Passive Margin Stratigraphymentioning
confidence: 99%
“…Historically, efforts to read the stratigraphic record of passive margins have focused on the study of sediment thickness, volume, texture, lithological/mineralogical make‐up and chemistry, yielding interpretations about past terrestrial erosion dynamics (e.g., Poag & Sevon, 1989). As numerical stratigraphic forward models (SFMs) became more common (e.g., Burgess, 2012; Burgess et al, 2006; Granjeon & Joseph, 1999; Steckler et al, 1993, 1996; Syvitski & Hutton, 2001), stratigraphic modellers began to use inverse techniques to extract environmental forcing information from forward simulation of the stratigraphic record (e.g., Bornholdt et al, 1999; Bornholdt & Westphal, 1998; Cross & Lessenger, 1999; Imhof & Sharma, 2006, 2007; Lessenger & Cross, 1996; Falivene et al, 2014; Zhang et al, 2021). The great potential of that record for revealing past landscape evolution has led to efforts to couple landscape evolution models (LEMs) and SFMs (e.g., Ding, Salles, Flament, Mallard, et al, 2019; Ding, Salles, Flament, & Rey, 2019; Granjeon & Joseph, 1999; Salles, 2019; Salles et al, 2018; Salles & Hardiman, 2016; Yuan et al, 2019; Zhang et al, 2020) to build full source‐to‐sink models, and in some cases to use large ensembles of those models to directly invert observed stratigraphy for terrestrial erosion dynamics (e.g., Yuan et al, 2019).…”
Section: Introductionmentioning
confidence: 99%
“…More recently, inversion techniques (Lessenger & Lerche, 1999) have been applied in conjunction with forward stratigraphic models to extract information about the environmental and tectonic conditions responsible for the development of stratigraphic sections (Bornholdt et al., 1999; Charvin, Gallagher, et al., 2009; Cross et al., 1999; Imhof & Sharma, 2006a; Karssenberg et al., 2007; Lessenger & Cross, 1996), and validated with synthetic or small‐scale data sets (e.g. Charvin, Hampson, et al., 2009; Crombez et al., 2020; Ducros et al., 2023; Imhof & Sharma, 2006b; Karssenberg et al., 2001; Mahmudova et al., 2023; Patani et al., 2021; Sacchi et al., 2015; Wijns et al., 2004). The inverse modelling aligns or calibrates the forward model with target data and produces an estimate of the most probable input parameters.…”
Section: Introductionmentioning
confidence: 99%