Petrophysical evaluation of clastic formations in boreholes with incomplete well log dataset by using joint inversion technique and machine learning algorithms

A succesful petrophysical evaluation of shaly-sand formations requieres: 1) the availability of high quality well log data and, 2) a petrophysical model that successfully represents the geological conditions of the rocks. Unfortunately, it is not always possible to fulfill these conditions, and in m...

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Bibliografische Detailangaben

Hauptverfasser:	Felipe Santana-Román, Ambrosio Aquino López, Manuel Romero Salcedo (+), Raúl del Valle García, Oscar Campos Enriquez
Format:	Artigo
Sprache:	Inglês
Veröffentlicht:	Universidad Nacional Autónoma de México, Instituto de Geofísica 2025-07-01
Schriftenreihe:	Geofísica Internacional
Schlagworte:	clastic formations well logs, petrophysical joint inversion machine learning
Online-Zugang:	https://revistagi.geofisica.unam.mx/index.php/RGI/article/view/1803
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