Feature exploration is a critical part of the Petro.ai DSU Design Service (DSUDS) model development. Recommendation reports are presented in live, interactive meetings where the client’s asset team and the Petro.ai team discuss the features that need to be included and interpreted in the model.
Scaling for lateral length, investigation of ISIP picks, the significance of various geologic attributes are all discussion that feed into the modeling process. Other frequently discussed (and even debated!) concepts include balancing fluid per foot with proppant per foot, assessing historical perf erosion issues, and experiential observations of faults or lineaments.
Kyle LaMotta, VP of Analytics comments, “If we’re not getting feedback from the client’s asset team then it’s hard for us to experiment with enhanced model development. We’re not only bringing in subsurface data, but also incorporating the mental models that our clients have. Experiences in a target AOI can be reflected using custom inputs to incorporate these learnings into a model. Alternatively, we can run experiments on our digital twin to investigate how these predictions map to real life experience.
“The more the client is talking,” LaMotta continues, “the more insights they’re giving to us. They’ve spent a lot more time with their wells and their data than we have. There could be things that we’re not aware of or a certain data type that they’ve collected that we don’t know about. Through these discussions we can uncover their nuances. Incorporating these nuances typically comes in the form of geologic variables or petrophysical variables in the form of gridded attributes. These features almost always enhance the model.
“Petro.ai recommendation reports stay current with what our clients are learning. New data is created with each step of well construction. A new DSU means new drainage patterns, as well as new pressure and stress profiles. With DSUDS models updated with each new input, they remain accurate and relevant for ongoing development.
“Petro.ai wants to be part of a client’s team, participating in strategic discussions, bouncing ideas off each other, not just delivering a result. The client conversation, discussing and quality controlling the features included in the model is a critical and exciting part of the Petro.ai DSU Design Service. This back-and-forth builds confidence in the process and ultimately more data-driven shale decision making.”