Project Summary

 

There is a limited and outdated set of well data that provides information on the South Surat Basin. It has been proposed to use this little information to predict the petrophysical properties at the EPQ10 well locations. This project will use machine learning (ML) algorithms trained on existing wells to predict fluid and petrophysical properties of future exploration wells. The first EPQ10 exploration well data will also be part of the training material when they become available. The expected outcome will help address current information gaps, including reservoir fluid properties, rock properties variation between the two wells, and injectivity.

 

 

Available Reports

Uncertainty Analysis of Diverse Petrophysical Data for Injectivity Prediction Using Machine Learning Methods

Project Name:
Uncertainty analysis of diverse petrophysical data for injectivity prediction

Research Organisation:
Curtin University

Status:
Finalised

Authors:
R Rezaee

Reference:
7-0320-C329

Research Program: EPQ10, Machine learning, Petrophysical analysis, south Surat
Demonstration: Surat Basin
Research Focus: Exploration R&D assessment, Machine Learning, Petrophysical Analysis, Modelling Errors & Uncertainties

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