Uncertainty management in stratigraphic well correlation and stratigraphic architectures: A training-based method

Edwards, Jonathan; Lallier, Florent; Caumon, Guillaume; Carpentier, Cédric

doi:10.1016/j.cageo.2017.10.008

Cited by 18 publications

(18 citation statements)

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“…A better integration of concepts is the topic of recent research. In particular, due to the difficulty of determining the exact age of sediments, uncertainty about stratigraphic history may be described using several possible stratigraphic columns built from the data at hand and from various depositional concepts (Borgomano et al, 2008;Lallier et al, 2012;Edwards et al, 2018).…”

Section: Stratigraphy and Representations Of Geological Timementioning

confidence: 99%

“…Similar methods have also been applied in stratigraphic settings to simulate the possible location of stratigraphic unconformities from sparse borehole data (Lallier et al, 2012(Lallier et al, , 2016Wu and Caumon, 2017;Edwards et al, 2018). As the location and number of gaps in the stratigraphic record vary, this amounts to changing the number of units and relationships between units in the stratigraphic column.…”

Section: Topological Uncertainties and Data Association (M φ κ β Amentioning

confidence: 99%

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3-D Structural geological models: Concepts, methods, and uncertainties

Wellmann

Caumon

2018

Advances in Geophysics

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163

103

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The Earth below ground is the subject of interest for many geophysical as well as geological investigations. Even though most practitioners would agree that all available information should be used in such an investigation, it is common practice that only a fraction of geological and geophysical information is used. We believe that some reasons for this omission are (a) an incomplete picture of available geological modeling methods, and (b) the problem of the perceived static picture of an inflexible geological representation in an image or geological model. With this work, we aim to contribute to the problem of subsurface interface detection through (a) the review of state-of-the-art geological modeling methods that allow the consideration of multiple aspects of geological realism in the form of observations, information and knowledge, cast in geometric representations of subsurface structures, and (b) concepts and methods to analyze, quantify, and communicate related uncertainties in these models. We introduce a formulation for geological model representation and interpolation and uncertainty analysis methods with the aim to clarify similarities and differences in the diverse set of approaches that developed in recent years. We hope that this chapter provides an entry point to recent developments in geological modeling methods, helps researchers in the field to better consider uncertainties, and supports the integration of geological observations and knowledge in geophysical interpretation, modeling and inverse approaches.

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Section: Stratigraphy and Representations Of Geological Timementioning

confidence: 99%

Section: Topological Uncertainties and Data Association (M φ κ β Amentioning

confidence: 99%

3-D Structural geological models: Concepts, methods, and uncertainties

Wellmann

Caumon

2018

Advances in Geophysics

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163

103

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“…10.1029/2020JB020022 The experiment shows that the formalism and the chosen metric are favorable when relatively few pieces of fault evidence are available. This may seems counterintuitive; however, when pieces of evidence are added, the difficulty to explore a larger search space increases in a non-polynomial way, as also observed by Edwards et al (2018) for well correlation.…”

Section: Journal Of Geophysical Research: Solid Earthmentioning

confidence: 99%

Multi‐scenario Interpretations From Sparse Fault Evidence Using Graph Theory and Geological Rules

2021

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The characterization of geological faults from geological and geophysical data is often subject to uncertainties, owing to data ambiguity and incomplete spatial coverage. We propose a stochastic sampling algorithm which generates fault network scenarios compatible with sparse fault evidence while honoring some geological concepts. This process is useful for reducing interpretation bias, formalizing interpretation concepts, and assessing first-order structural uncertainties. Each scenario is represented by an undirected association graph, where a fault corresponds to an isolated clique, which associates pieces of fault evidence represented as graph nodes. The simulation algorithm samples this association graph from the set of edges linking the pieces of fault evidence that may be interpreted as part of the same fault. Each edge carries a likelihood that the endpoints belong to the same fault surface, expressing some general and regional geological interpretation concepts. The algorithm is illustrated on several incomplete data sets made of three to six two-dimensional seismic lines extracted from a three-dimensional seismic image located in the Santos Basin, offshore Brazil. In all cases, the simulation method generates a large number of plausible fault networks, even when using restrictive interpretation rules. The case study experimentally confirms that retrieving the reference association is difficult due to the problem combinatorics. Restrictive and consistent rules increase the likelihood to recover the reference interpretation and reduce the diversity of the obtained realizations. We discuss how the proposed method fits in the quest to rigorously (1) address epistemic uncertainty during structural studies and (2) quantify subsurface uncertainty while preserving structural consistency. Plain Language Summary This paper presents a way to generate interpretation scenarios for geological faults from incomplete spatial observations. The method essentially solves a "connect the dots" exercise that honors the observations and geological interpretation concepts formulated as mathematical rules. The goal is to help interpreters to characterize how the lack of data affects geological structural uncertainty. The proposed method is original in the sense that it does not anchor the scenarios on a particular base case but rather uses a global characterization formulated with graph theory to generate possible fault network interpretations. The application on a faulted formation offshore Brazil where observations have been decimated shows that the method is able to consistently generate a set of interpretations encompassing the interpretation made from the full data set. It also highlights the computational challenge of the problem and the difficulty to check the results in settings where only incomplete observations exist. The proposed method, however, opens novel perspectives to address these challenges.

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“…Automated correlation is often regarded as a helpful tool and several methods have been proposed and published (Olea, 1994;Lisiecki and Lisiecki, 2002;Pälike, 2002;Huybers and Aharonson, 2010;Lin et al, 2014;Kotov et al, 2016;Edwards et al, 2018), and used (e.g. Lisiecki and Raymo, 2005;Pälike et al, 2006b;Necula and Panaiotu, 2008;Lang and Wolff, 2011;Liebrand et al, 2011).…”

Section: Introductionmentioning

confidence: 99%

Taner filter settings and automatic correlation optimisation for cyclostratigraphic studies

Zeeden

Kaboth

Hilgen

et al. 2018

Computers & Geosciences

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Cyclostratigraphy and astronomical tuning utilize the imprint of quasi-cyclic insolation changes in geological records to establish chronologies. In this context, filtering of time series in specific frequency bands is commonly applied to extract information on astronomical forcing from geological datasets. This approach is performed on specific insolation components (precession, obliquity or eccentricity) and sometimes also their amplitudes either in depth or time domain. In this study, we design and apply a simulation technique to determine the optimal Taner filter settings to extract precession-, obliquity-and eccentricity-related interference signals from astronomically tuned geological datasets. This is done by testing a variety of filter settings on several astronomical and artificial datasets. Based on our results, we propose specific filter designs (cut-off frequencies and roll-off rates) for the best extraction of astronomical (interference) signals from tuned geological datasets. Focus here lies on datasets shorter than ca. 1 million years and interference patterns between astronomical components. A second step utilizes these filter settings for an automated alignment, where geological data on a tuned time scale are matched to a suite of astrochronologic correlation targets. This is done by aligning filter minima and maxima to astronomical targets. This approach is particularly useful for the determination of the relative contributions of astronomical parameters in a specific dataset and allows for the automatic determination of phase shifts between well expressed insolation components in datasets.

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Uncertainty management in stratigraphic well correlation and stratigraphic architectures: A training-based method

Cited by 18 publications

References 67 publications

3-D Structural geological models: Concepts, methods, and uncertainties

3-D Structural geological models: Concepts, methods, and uncertainties

Multi‐scenario Interpretations From Sparse Fault Evidence Using Graph Theory and Geological Rules

Taner filter settings and automatic correlation optimisation for cyclostratigraphic studies

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