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Stratigraphic correlation uncertainty : On the impact of the sediment transport direction in computer-assisted multi-well correlation

Baville, Paul ORCID iD icon

Abstract:

Subsurface modeling is a way to predict the structure and the connectivity of stratigraphic units by honoring subsurface observations. These observations are commonly be sampled along wells at a large and sparse horizontal scale (kilometer-scale) but at a fine vertical scale (meter-scale). There are two types of well data: (1) well logs, corresponding to quasi-continuous (regular sampling) geophysical measurements along the well path (e.g., gamma ray, sonic, neutron porosity), and (2) regions, corresponding to categorical reservoir properties and defined by their top and bottom depths along the well path (e.g., biozones, structural zones, sedimentary facies). Markers are interpreted along the well path and can be associated in order to generate a consistent set of marker associations called well correlations. These well correlations may be generated manually (deterministic approach) by experts, but this may be prone to biases and does not ensure reproducibility. Well correlations may also be generated automatically (deterministic or probabilistic approach) by computing with an algorithm a large number of consistent well correlations and by ranking these realizations according to their likelihood. ... mehr


Zugehörige Institution(en) am KIT Institut für Angewandte Geowissenschaften (AGW)
Publikationstyp Hochschulschrift
Publikationsjahr 2022
Sprache Englisch
Identifikator KITopen-ID: 1000155649
Art der Arbeit Dissertation
Prüfungsdaten Lorraine, Univ., 12.04.2022
Schlagwörter Multi-Well correlations, Sequence stratigraphy, Sediment transport direction, Coastal sedimentary depositional environments, Uncertainty assessment, Dynamic Time Warping Algorithm
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