In this chapter, we will explore the idea of building an end-to-end cloud-based machine learning system to identify lithofacies based on well log measurements. This is a crucial step in all drilling applications. First, we will start by introducing the problem and the dataset. Next, we will explain the types of preprocessing and post processing needed for such a use case. Finally, a complete solution will be built using machine learning services, Python, and IBM Watson Studio.
The following topics will be covered in this chapter:
- Understanding lithofacies
- Exploring the data
- Training the classifier
- Evaluating the classifier
