Now let’s review the opposite scenario, a development project of horizontal wells with enormous data sets of similar offset wells where the efficiencies are already very high. (For part 1, click here)
Take North America’s Permian Basin as a good example.
YES! The cost can be reduced by achieving a consistent performance. This opportunity is not available only to clients but also to service companies. With the implementation of new downhole tool technologies, more opportunities to drill faster can be implemented.
But how reliable are these technologies? How trustworthy are the different combinations of bits and RSS in any specific basin? This is where AI takes place. It allows the analysis in a single and efficient way, of the combination of drilling parameters, BHA’s configuration and bit selection, in order to determine the proper road map to be implemented in each section/formation. So, this in agreement with the selected BHA, assures tool longevity, hole integrity and maximizes reservoir contact area; which will be reflected as the most important output: the increase on well efficiencies.
The optimization opportunities are available and diverse, since the AI technology is fully editable, replicable and adaptive for any project as any person could imagine. This opens a new question as follows:
As it was mentioned at the beginning, this technology is reaching the entire upstream, and its implementation is a “work in progress” or “in transition period”. Since most of the companies already have processes, workflows and methodologies based on the previous ways to work, the new approach (AI) is under testing, trying to replicate the same usual results the companies are used to have. Early testing is showing that it is possible to obtain similar results and in many cases, better outcomes, with single processing and modeling. Driving the decision to utilize and develop new models based on AI technology.
The final implementation and approach of this technology will take place when diverse teams within the same organization, realize that a single and automated process can be implemented for the entire life cycle of any project. Also, with specific AI & ML models built in, leveraging human expertise. For instance, when the commercialization takes place, the model would be capable of providing the required outputs of each area: geology, reservoir, digital drilling, completions, and production, in order to create a unique environment in terms of planning, execution and evaluation; exactly what the ADA AI™ Digital Ecosystem offers.