Cloud-Based Borehole Image Interpretation Workflow Using Machine Learning

Summary We propose a new workflow for borehole image interpretation incorporating machine learning methods and recent cloud technologies. In order to predict facies from borehole image, clean labels, i.e. the borehole image with annotated facies intervals, must be collected. We propose a solution to accelerate the labelling process by introducing an automatic segmentation and unsupervised learning algorithm based on image texture features. We then present a web based application and pipeline from the user interface to the cloud database that allows the user to easily construct and update the digital facies library and we show first results of our automated image recognition.