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<p>Wellbore stability is a primary objective in the the oil and gas industry, as it significantly reduces drilling risks and operational costs. In recent years, numerous studies have utilized geomechanical approaches to address this issue. However, due to insufficient and limited availability of necessary data, geomechanical studies remain a major challenge. This paper has tried to investigate wellbore stability conditions and the optimal mud weight in the Lali field using a geomechanical model to ensure efficient drilling operations in the field. In this regard, shear wave velocity estimation using the adaptive neuro-fuzzy inference system (ANFIS), was evaluated in comparison with two other approaches, multilayer perceptron (MLP) and radial basis function (RBF). To predict failure occurrence in well walls and assess stress conditions, failure criteria such as Mohr-Coulomb, Mogi-Coulomb, and Hoek-Brown were compared. A three-dimensional (3D) geomechanical model was implemented and analyzed in Petrel software based on the one-dimensional (1D) geomechanical model, considering the importance of the region’s geomechanical characteristics. The results indicate that the Mohr-Coulomb failure criterion provides reliable predictions of instabilities occurring in the Lali field. It was found that the stress regime in the field is predominantly of a reverse fault nature, occasionally transitioning to strike-slip faulting. Furthermore, the findings reveal that zones 6 and 7 of the Asmari reservoir have the narrowest safe mud weight windows, with averages of 23.64&#xa0;MPa and 31.87&#xa0;MPa, respectively.</p>

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Geomechanical modeling for well stability to determining the bottom hole pressure and optimal mud weight using adaptive neuro-fuzzy inference system

  • 期刊论文

  • 发表日期：

    2025年2月10日

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  • Asaad Sattar Manduf Al- Hasan,
  • Ehsan Moosavi,
  • Reza Shirinabadi

摘要

Wellbore stability is a primary objective in the the oil and gas industry, as it significantly reduces drilling risks and operational costs. In recent years, numerous studies have utilized geomechanical approaches to address this issue. However, due to insufficient and limited availability of necessary data, geomechanical studies remain a major challenge. This paper has tried to investigate wellbore stability conditions and the optimal mud weight in the Lali field using a geomechanical model to ensure efficient drilling operations in the field. In this regard, shear wave velocity estimation using the adaptive neuro-fuzzy inference system (ANFIS), was evaluated in comparison with two other approaches, multilayer perceptron (MLP) and radial basis function (RBF). To predict failure occurrence in well walls and assess stress conditions, failure criteria such as Mohr-Coulomb, Mogi-Coulomb, and Hoek-Brown were compared. A three-dimensional (3D) geomechanical model was implemented and analyzed in Petrel software based on the one-dimensional (1D) geomechanical model, considering the importance of the region’s geomechanical characteristics. The results indicate that the Mohr-Coulomb failure criterion provides reliable predictions of instabilities occurring in the Lali field. It was found that the stress regime in the field is predominantly of a reverse fault nature, occasionally transitioning to strike-slip faulting. Furthermore, the findings reveal that zones 6 and 7 of the Asmari reservoir have the narrowest safe mud weight windows, with averages of 23.64 MPa and 31.87 MPa, respectively.