Abstract: Wellbore instability and subsidence of the offshore wells and platforms are major complications in the oil and gas industry and should be monitored throughout the life of the well. As part of reservoir management, it is essential to know about rock–fluid interaction, rock mechanics, and fracture pressures for drilling horizontal wells and multiple laterals from a single vertical well. There are many reasons for causing wellbore instabilities out of them during drilling through shales is one of the primary reasons. Reservoir geomechanics is a nifty area in the oil industry to understand the wellbore instability, lost circulation, wellbore-breakouts, compaction, and subsidence. Understanding the reservoir geomechanics and the rock properties provide engineers to design suitable casing and eliminate future effects of rock deformation on the casing and platforms. Usually, the geomechanical analysis for a well or field is carried out in parts due to the complete availability of data.
The main objective of this research is to perform a comprehensive geomechanical analysis for an offshore carbonate reservoir block. In this study, we developed a new workflow/methodology by integrating different studies such as seismic inversion, 1D, 3D, and 4D geomechanical models, uniaxial and triaxial compressive tests, rock and fluid reactivity tests, and ultrasonic wave measurements. Rock properties calculated from petrophysical data sets are lithology dependent; we use machine learning methods to classify the electrofacies to generate the rock models. This is a new approach to integrating the ML methods to classify the lithofacies with geomechanical interpretation. Our study provides the complete geomechanical examination to know the wellbore stability, identify weak zones causing drilling problems, the spatial distribution of stresses, and rock properties.
Though we have used Mumbai offshore data for our research, our work is not limited to a particular reservoir. The integrated approach could apply to the oil and gas fields across the world, especially where there is inadequate data to perform full-scale geomechanical analysis. Our work consists of complicated data analysis and processing to fill the missing data from the field to constitute the geomechanical models.