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Norwegian AI Directory

Application of predictive data analytics to wellbore geomechanics on the Norwegian continental shelf


Despite significant progress, borehole instabilities and well control incidents are still major challenges in drilling wells across the globe. On the Norwegian continental shelf about 40% of the wells encountered issues related to borehole stability or overpressure, leading to costly delays and the need for contingency measures affecting safety. Most of these problems can be avoided with a better understanding of the conditions in the subsurface and adjusted drilling practices, leading to more efficient and safer drilling. By introducing drilling mechanics data, geomechanical modelling, and advanced data analytics, more reliable predictions of stress and pore-pressure can be obtained. Applying data analytics and machine learning solves problems with data irregularity and allows joint analysis of a higher number of wells, allowing the datasets to “learn from each other”. Combining geophysical logs and drilling mechanics data allows for a more precise determination of the top and base limits of overpressured zones in the subsurface. Furthermore, a quantified analysis of drilling mechanics data allows pressure prediction in non-shale lithologies, which has been a major challenge in the industry. In the project, the geomechanical methodology developed by Geoprovider will be scientifically verified and improved, resulting in higher cost efficiency and improved safety for drilling operations. Using the wealth of data available on the Norwegian continental shelf, a number of case studies will be presented demonstrating the progress and applicability of the methods. The algorithms can be used globally, and the results of this project will be specifically tested for application in geothermal energy using data from high pressure high temperature wells.

Project leader: Wim Lekens

Started: 2020

Ends: 2024

Category: Næringsliv

Sector: Næringsliv

Budget: 1798000


Address: Stavanger