Abstract

Prediction of the mechanical characteristics of the reservoir formations, such as static Young’s modulus (Estatic), is very important for the evaluation of the wellbore stability and development of the earth geomechanical model. Estatic considerably varies with the change in the lithology. Therefore, a robust model for Estatic prediction is needed. In this study, the predictability of Estatic for sandstone formation using four machine learning models was evaluated. The design parameters of the machine learning models were optimized to improve their predictability. The machine learning models were trained to estimate Estatic based on bulk formation density, compressional transit time, and shear transit time. The machine learning models were trained and tested using 592 well log data points and their corresponding core-derived Estatic values collected from one sandstone formation in well-A and then validated on 38 data points collected from a sandstone formation in well-B. Among the machine learning models developed in this work, Mamdani fuzzy interference system was the highly accurate model to predict Estatic for the validation data with an average absolute percentage error of only 1.56% and R of 0.999. The developed static Young’s modulus prediction models could help the new generation to characterize the formation rock with less cost and safe operation.

Highlights

  • Prediction of the mechanical characteristics of the reservoir formations, such as Young’s modulus (E), is necessary for the evaluation of the wellbore stability, reservoir compaction, hydraulic fracturing, and formation control [1]

  • Four machine learning techniques were applied in this study to develop models for estimating Estatic for sandstone formations, these machine learning techniques were artificial neural networks (ANN), functional neural networks (FNN), Mamdani fuzzy interference system (M-FIS), and support vector machine (SVM)

  • The machine learning models were trained to evaluate Estatic based on conventional well log data of the RHOB, DTs, and DTc

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Summary

Introduction

Prediction of the mechanical characteristics of the reservoir formations, such as Young’s modulus (E), is necessary for the evaluation of the wellbore stability, reservoir compaction, hydraulic fracturing, and formation control [1]. Static Young’s modulus (Estatic) is a critical parameter needed to build the earth geomechanical model [3]. It is used for fractures’ designing and mapping [4,5]. Estatic is needed with other mechanical and petrophysical properties to make a full description of the in-situ stresses to ensure wellbore stability [6]. It is between 55.16 and 82.74 GPa, and for sandstone, it is between 13.79 and 68.95 GPa [7] These ranges confirm the wide difference in Estatic from one formation type to another and the huge change within the same lithology. It is necessary to estimate Estatic along the whole drilled hydrocarbon well

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