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Technical Paper: Geomechanics and Pore Pressure Considerations for Successful Deepwater Exploration Drilling

Society: SPE
Paper Number: 040
Presentation Date: 2011
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Abstract

Operators predominantly use geomechanics analysis and pore pressure prediction for well planning or when they have experienced serious drilling problems in a development field. The impact of non-productive time (NPT) on deepwater projects can seriously impact project economics and the ability to drill exploration wells successfully to their intended targets. Industry statistics show that even deepwater experienced operators can reach 25% NPT project time, whereby geomechanics-type events account for almost 40% of the total NPT. Pre-drill geomechanics studies and pore pressure prediction work can significantly reduce the risks and potentially reduce the costs for drilling exploration wells. In this paper, we show how a pre-drill geomechanics study can impact the well design and drilling performance. We present two exploratory deepwater case studies that include a pore pressure prediction study that characterizes the stress and rock strength, a stress-strain analysis for understanding and quantifying the stress concentration around subsalt structures using finite-element numerical modeling, and a 3D mechanical earth model (MEM) to predict the effects of in-situ stresses and induced stress increases due to a salt intrusion. To reduce the geological uncertainties related to the stress directions, a specialized sonic tool that delivers 3D acoustic characterization was run in these exploratory fields that allowed a better understanding of the stress directions and quantification of the maximum horizontal stress using 3D anisotropic elastic rock parameter information. The formation evaluation information obtained from the exploratory well was applied to the geomechanical model and resulted in more accurate prediction, thereby reducing NPT drilling events while drilling the exploratory wells. The process of developing and calibrating the geomechanical and pore pressure models required a multi-disciplinary approach that allowed integration, optimal utilization of acquired formation data, and fast tracking on the deepwater learning curve for the operator’s team members.

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