Geomechanical Evaluation While Drilling: Using Mud Logging Data for Generate Synthetic UCS and Pore Pressure Logs

Summary Understanding the behavior of geological formations is critical to ensuring the safety and efficiency of drilling operations. Key geomechanical parameters, such as pore pressure gradient and Unconfined Compressive Strength (UCS), are essential for defining the operational pressure window and maintaining wellbore stability. This paper introduces an integrated, analytical approach that correlates drilling efficiency parameters—specifically, Mechanical Specific Energy (MSE), Drilling Strength (DS), and the MSE/DS ratio—with well logging data and lithological information to enhance real-time geomechanical characterization. Offshore wells from the Brazilian Pre-Salt fields were analyzed, covering a variety of lithologies, including marls, shales, sandstones, limestones, and evaporites. The pore pressure gradient was estimated using the Eaton method (1975), while UCS was determined through lithology-specific empirical equations. A case study demonstrated a strong correlation between lithological variations, UCS, and overpressure anomalies. Results indicate that shale zones exhibit higher UCS and MSE values compared to sandstones. In overpressured sandstone intervals, lower resistance and an increasing pore pressure gradient were observed. The proposed methodology was proven to be highly effective for providing real-time decision support during drilling operations, enabling better management of operational risks and optimization of drilling performance.

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Published
2025-01-01
DOI
https://doi.org/10.3997/2214-4609.202535036
Primary Topic
Drilling and Well Engineering
Type
article
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article

Geomechanical Evaluation While Drilling: Using Mud Logging Data for Generate Synthetic UCS and Pore Pressure Logs

G. Medeiros, José António C. Santos, Joaquim Soares da Costa Júnior, Rosilene Rodrigues Santiago et al.
Drilling and Well Engineering
article

Geomechanical Evaluation While Drilling: Using Mud Logging Data for Generate Synthetic UCS and Pore Pressure Logs

G. Medeiros, José António C. Santos, Joaquim Soares da Costa Júnior, Rosilene Rodrigues Santiago, Miguel Piña e Cunha, M. Jacinto, L. Montalvão, Mateus A. S. de S. Goldbarg, T. Kiam
article en

Abstract

Summary Understanding the behavior of geological formations is critical to ensuring the safety and efficiency of drilling operations. Key geomechanical parameters, such as pore pressure gradient and Unconfined Compressive Strength (UCS), are essential for defining the operational pressure window and maintaining wellbore stability. This paper introduces an integrated, analytical approach that correlates drilling efficiency parameters—specifically, Mechanical Specific Energy (MSE), Drilling Strength (DS), and the MSE/DS ratio—with well logging data and lithological information to enhance real-time geomechanical characterization. Offshore wells from the Brazilian Pre-Salt fields were analyzed, covering a variety of lithologies, including marls, shales, sandstones, limestones, and evaporites. The pore pressure gradient was estimated using the Eaton method (1975), while UCS was determined through lithology-specific empirical equations. A case study demonstrated a strong correlation between lithological variations, UCS, and overpressure anomalies. Results indicate that shale zones exhibit higher UCS and MSE values compared to sandstones. In overpressured sandstone intervals, lower resistance and an increasing pore pressure gradient were observed. The proposed methodology was proven to be highly effective for providing real-time decision support during drilling operations, enabling better management of operational risks and optimization of drilling performance.

Kardan University (AF), Universidade Federal do Rio Grande do Norte (BR)
Openalex Percentile: Top 66%
Drilling and Well Engineering
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Geomechanical Evaluation While Drilling: Using Mud Logging Data for Generate Synthetic UCS and Pore Pressure Logs — G. Medeiros, José António C. Santos, et al. · (2025) | TGRS Research Map | TGRS